Commodity derivatives : markets and applications [Second ed.] 9781119349228, 1119349222, 9781119349259, 1119349257

Table of contents :
Cover
Title Page
Copyright
Contents
Preface
Chapter 1 Fundamentals of Commodities and Derivatives
1.1 Market overview
1.2 Market participants
1.2.1 Physical market participants
1.2.2 Price reporting agencies (PRAs)
1.2.3 Investment banks
1.2.4 Commodity trading houses
1.2.5 Hedge funds
1.2.6 ‘Real money’ accounts
1.3 Traded versus non‐traded commodities
1.4 Forward contracts
1.5 Futures
1.6 Swaps
1.7 Options
1.8 Exotic options
1.8.1 Binary options
1.8.2 Barrier options
1.8.3 Spread options
1.8.4 Average rate options
Chapter 2 Derivative Valuation
2.1 Asset characteristics
2.2 Commodity prices and the economic cycle
2.3 Principles of commodity valuation
2.4 Forward price curves
2.4.1 Forward prices – a market in contango
2.4.2 Forward prices – a market in backwardation
2.4.3 Interpreting forward curves
2.4.4 Commodity arbitrage
2.5 Commodity swap valuation
2.5.1 Single and dual curve discounting
2.6 Principles of option valuation
2.6.1 Black Scholes and Merton
2.6.2 The Black model
2.6.3 Bachelier model
2.6.4 Put‐call parity: the theory
2.6.5 Put‐call parity: the application
2.7 Measures of option risk management
2.7.1 Delta
2.7.2 Gamma
2.7.3 Theta
2.7.4 Vega
2.7.5 Non‐constant volatility
Chapter 3 Risk Management Principles
3.1 Defining risk
3.1.1 Subcategories of risk
3.2 Commodity market participants – the time dimension
3.2.1 Short‐dated maturities
3.2.2 Medium‐dated maturities
3.2.3 Longer‐dated exposures
3.3 Hedging corporate risk exposures
3.4 A framework for analysing corporate risk
3.4.1 Strategic considerations
3.4.2 Tactical considerations
3.5 Hedging customer exposures
3.5.1 Forward risk management
3.5.2 Swap risk management
3.5.3 Option risk management
3.5.4 Correlation risk management
3.5.5 Case study: Managing market and credit – the collapse of Japan Airlines
3.6 Trading risk management
3.6.1 Spot trading strategies
3.6.2 Forward trading strategies
3.6.3 Single period physically settled ‘swaps’
3.6.4 Single or multi‐period financially settled swaps
3.6.5 Option based trades – trading volatility
3.6.6 Case study: Amaranth Advisors and the US natural gas market
3.6.7 Case study: Metallgesellschaft
Chapter 4 Gold
4.1 The market for gold
4.1.1 Physical Supply Chain
4.1.2 Intermediaries
4.1.3 The London Gold Market
4.1.4 The LBMA gold price
4.2 Gold price drivers
4.2.1 The price of gold
4.2.2 Supply of gold
4.2.3 The Demand for gold
4.2.4 Gold price relationships
4.3 The gold leasing and deposit market
4.3.1 Forward price formation
4.3.2 Deriving implied lease rates
4.3.3 Who lends and borrows gold?
4.4 Hedging
4.4.1 Forwards
4.4.2 Swaps
4.4.3 Options
4.5 Trading gold
4.5.1 Gold swaps / FX swaps
4.5.2 Non‐deliverable gold swaps
4.5.3 Deferred margin accounts
4.6 Yield enhancement
4.7 Summary
Chapter 5 Base Metals
5.1 Overview of base metal production
5.2 The copper lifecycle
5.2.1 Copper resources
5.2.2 Uses of copper
5.2.3 The copper supply chain
5.2.4 The role of scrap copper
5.2.5 Trading copper
5.3 Aluminium
5.4 The Steel market
5.4.1 Factors impacting the price of steel
5.4.2 Steel risk management
5.5 The London Metal Exchange
5.5.1 Exchange traded metal futures
5.5.2 Exchange traded metal options
5.5.3 LME prices and contract specification
5.5.4 Trading
5.5.5 Clearing and settlement
5.5.6 Delivery
5.6 Base metal price drivers
5.7 Electric Vehicles
5.7.1 Lithium
5.7.2 Cobalt
5.8 Structure of market prices
5.8.1 Long‐term prices
5.8.2 How do forward curves move?
5.8.3 Are forward prices forecasts?
5.8.4 The role of marginal costs
5.8.5 Premiums
5.9 Hedges for aluminium consumers in the automotive sector
5.9.1 Forward purchase
5.9.2 Carry trades in the base metal market
5.9.3 Vanilla option strategies
5.9.4 Short option positions
5.9.5 Combination option strategies
5.9.6 Structured option solutions
5.9.7 Foreign currency exposures
5.10 Summary
Chapter 6 Crude Oil
6.1 Overview of energy markets
6.2 The value of crude oil
6.2.1 Basic chemistry of oil
6.2.2 Density
6.2.3 Sulfur content
6.2.4 Acidity
6.2.5 Flow properties
6.2.6 Other chemical properties
6.2.7 Examples of crude oil
6.3 An overview of the physical supply chain
6.4 Refining crude oil
6.4.1 What is refining?
6.4.2 What does a refinery produce?
6.4.3 Product yields
6.4.4 How does a refinery work?
6.4.5 Refinery optimisation
6.4.6 Refinery yields and relative crude oil prices
6.4.7 Measuring profitability
6.4.8 Drivers of refinery performance and profitability
6.5 The demand for and supply of crude oil
6.5.1 Proved oil reserves
6.5.2 R/P Ratio
6.5.3 Production of crude oil
6.5.4 Consumption of crude oil
6.5.5 Crude oil trade
6.5.6 Demand for refined products
6.5.7 Security of supply (and demand)
6.6 Price drivers
6.6.1 Macroeconomic issues
6.6.2 Supply chain considerations
6.6.3 Geopolitics
6.6.4 Analysing the forward curve
6.7 The price of crude oil
6.7.1 Defining price
6.7.2 The evolution of crude oil prices
6.7.3 Delivered price
6.7.4 Marker crudes
6.7.5 Pricing sources
6.7.6 Pricing methods
6.7.7 Pricing a cargo of crude oil
6.8 Trading crude oil and refined products
6.8.1 Overview
6.8.2 The Brent complex
6.8.3 US crude oil markets
Notes
6.9 Managing price risk along the supply chain
6.9.1 Producer Hedges
6.9.2 Refiner hedges
6.9.3 Refined product hedges
Chapter 7 Natural Gas
7.1 Formation of natural gas
7.2 Measuring natural gas
7.3 The physical supply chain
7.3.1 Production
7.3.2 Shippers
7.3.3 Transmission
7.3.4 Interconnectors
7.3.5 Storage
7.3.6 Supply
7.3.7 Customers
7.3.8 Non‐physical participants (NPPs)
7.4 Deregulation and re‐regulation
7.4.1 The US experience
7.4.2 The UK experience
7.4.3 Continental European deregulation
7.5 The demand for and supply of natural gas
7.5.1 Relative importance of natural gas
7.5.2 Reserves of natural gas
7.5.3 Production of natural gas
7.5.4 Shale gas
7.5.5 Reserve to production ratio
7.5.6 Consumption of natural gas
7.5.7 Exporting natural gas
7.5.8 Liquefied natural gas (LNG)
7.6 Natural gas prices
7.6.1 Natural gas price definitions
7.6.2 Oil indexation in the natural gas market
7.6.3 Liquefied natural gas (LNG) prices
7.7 Natural gas price drivers
7.7.1 Supply side price drivers
7.7.2 Demand side price drivers
7.7.3 LNG price drivers
7.8 Trading natural gas
7.8.1 Motivations for trading natural gas
7.8.2 Contract types
7.8.3 Delivery points
7.8.4 Trading natural gas in the UK
7.8.5 On‐the‐Day Commodity Market (OCM)
7.9 Natural gas derivatives
7.9.1 Exchange traded futures contracts
7.9.2 Over‐the‐counter natural gas transactions
CHAPTER 8 Electricity
8.1 What is electricity?
8.1.1 Conversion of energy sources to electricity
8.1.2 Primary sources of energy
8.1.3 Commercial production of electricity
8.1.4 Measuring electricity
8.2 The physical supply chain
8.3 Market structure and regulation
8.3.1 The European Experience
8.3.2 Overview of UK regulation
8.3.3 The American Experience
8.3.4 Wholesale markets in the USA
8.4 Price drivers of electricity
8.4.1 Demand for electricity
8.4.2 Supply of electricity
8.4.3 Factors influencing spot and forward prices
8.4.4 Negative prices
8.4.5 Spark and dark spreads
8.4.6 Marginal heat rates
8.5 Trading electricity – an overview
8.5.1 Load shapes
8.5.2 Contract volumes
8.5.3 Contract prices and valuations
8.5.4 Price formation
8.5.5 Optimising production
8.5.6 System imbalances
8.5.7 Timing mismatches
8.5.8 UK trading conventions
8.5.9 US traded markets – an overview
8.6 Electricity derivatives
8.6.1 Electricity forwards
8.6.2 Electricity swaps
8.6.3 Contracts for difference
8.6.4 Swaptions
8.6.5 Spread options
8.6.6 Monetising embedded optionality
8.6.7 Ratio swap on power and aluminium
8.6.8 Monthly and daily power swaps
8.6.9 Options on power swaps
8.6.10 Heat rate derivatives
CHAPTER 9 Plastics
9.1 The chemistry of plastic
9.2 The production of plastic
9.3 Monomer production
9.3.1 Crude Oil
9.3.2 Natural Gas
9.4 Polymerisation
9.5 Applications of plastics
9.6 Summary of the plastics supply chain
9.7 Price determination
9.8 Plastic price drivers
9.9 Forwards and swaps
Price fixing hedge
Offset hedge
Proxy hedges
9.10 Option strategies
CHAPTER 10 Bulk Commodities
10.1 The basics of coal
10.2 The demand for and supply of coal
10.3 Coal – the physical supply chain
10.3.1 Production
10.3.2 Main participants
10.3.3 Factors affecting the price of coal
10.4 Coal derivatives
10.4.1 Exchange traded futures
10.4.2 Over the counter solutions
10.5 Iron ore
10.5.1 Background
10.5.2 Evolution of iron prices
10.5.3 Iron ore derivatives
10.6 Freight markets – the fundamentals
10.6.1 Vessel types
10.6.2 Freight charges
10.6.3 Freight market participants
10.6.4 An overview of dry freight indices
10.6.5 Worldscale
10.6.6 Freight price drivers
10.6.7 Freight Derivatives
CHAPTER 11 Climate and Weather
11.1 The science of climate change
11.1.1 Definitions
11.1.2 Greenhouse Gases
11.1.3 The carbon cycle
11.1.4 Feedback loops
11.2 The consequences of climate change
11.2.1 Fifth assessment report of the IPCC
11.3 The argument against climate change
11.4 History of human action against climate change
11.4.1 Formation of the IPCC
11.4.2 The Earth Summit
11.4.3 The Kyoto Protocol
11.4.4 From Kyoto to Paris
11.5 Price drivers of emissions markets
11.6 EU Emission Trading System
11.6.1 Background
11.6.2 System design
11.6.3 Cap and trade versus carbon taxes
11.7 Emission derivatives
11.7.1 Introduction
11.7.2 Spot transactions
11.7.3 Forwards – fair value pricing
11.7.4 Repurchase agreements
11.7.5 Swaps
11.7.6 Physical and cash‐settled options
Notes:
11.7.7 ‘View driven’ strategies
11.8 Weather derivatives
11.8.1 Potential industries
11.8.2 General characteristics
11.8.3 Exchange traded futures
11.8.4 Over‐the‐counter structures
11.8.5 Swaps
11.8.6 Options
11.8.7 Applications – cattle industry
11.8.8 Applications – power utilities
CHAPTER 12 Agriculture
12.1 Agricultural markets
12.2 Definitions
12.3 Agricultural products
12.3.1 Physical supply chain – wheat
12.3.2 Wheat
12.3.3 Corn
12.3.4 Palm oil
12.3.5 Soybeans
12.4 Soft commodities
12.4.1 Sugar
12.4.2 Coffee
12.4.3 Cocoa
12.5 Ethanol
12.5.1 What is ethanol?
12.5.2 History of ethanol
12.5.3 Supply chain: corn to ethanol
12.6 Price drivers
12.6.1 Physical market factors
12.6.2 Societal factors
12.6.3 Governmental intervention
12.6.4 Financial factors
12.7 Exchange traded agricultural and ethanol derivatives
12.8 Over‐the‐counter agricultural derivatives
Swaps
Vanilla swaps – exotic requirements
Options
Options on spreads
Target Redemption Structures (TARNs)
CHAPTER 13 Commodity‐Linked Financing
13.1 The financing need
13.1.1 Loan structures
13.1.2 Definitions
13.1.3 Financing case studies
13.2 Project finance
13.3 Working capital and the asset conversion cycle
13.3.1 Monetising inventories using repurchase agreements
13.3.2 Tri‐party agreements/margin financing
13.3.3 Prepay structures
13.3.4 Prepaid variable forwards
13.3.5 Lending risks
13.3.6 The commodity carry trade
13.3.7 Supply and offtake agreements
13.4 Longer‐term debt funding solutions
13.4.1 Embedding vanilla optionality into a loan
13.4.2 Commodity‐linked interest rate hybrids
CHAPTER 14 Commodity Investing
14.1 Commodity investors
14.2 Preferred instruments
14.3 Market size
14.4 Rationale for investing in commodities
14.4.1 Return enhancement and diversification
14.4.2 Inflation hedge
14.4.3 Hedge against US dollar
14.5 Commodity indices
14.5.1 Construction
14.5.2 Quoting conventions
14.5.3 Evolution of index construction
14.5.4 The myth of the roll yield
14.6 Total Return Swaps
14.7 Exchange traded products (ETPs)
14.7.1 Exchange traded commodities
14.7.2 Exchange traded fund
14.7.3 Exchange traded note (ETN)
14.8 Structured products
14.8.1 Capital protected notes
14.8.2 Structuring considerations
14.8.3 Basket notes
14.8.4 Income structures
14.8.5 Reverse convertible
14.8.6 Autocallable structures
14.8.7 Outperformance note
14.8.8 ‘Worst of’ structures
Glossary
Bibliography
Biography
Index
EULA

Citation preview

Commodity Derivatives

Founded in 1807, John Wiley & Sons is the oldest independent publishing company in the United States. With offices in North America, Europe, Australia and Asia, Wiley is globally committed to developing and marketing print and electronic products and services for our customers’ professional and personal knowledge and understanding. The Wiley Finance series contains books written specifically for finance and investment professionals as well as sophisticated individual investors and their financial advisors. Book topics range from portfolio management to e-commerce, risk management, financial engineering, valuation and financial instrument analysis, as well as much more. For a list of available titles, visit our Web site at www.WileyFinance.com.

Commodity Derivatives Markets and Applications NEIL C. SCHOFIELD

Second Edition

This edition first published 2021 Copyright © 2021 by Neil C. Schofield. Registered office John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher. Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at http://booksupport.wiley.com. For more information about Wiley products, visit www.wiley.com. Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book. Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. It is sold on the understanding that the publisher is not engaged in rendering professional services and neither the publisher nor the author shall be liable for damages arising herefrom. If professional advice or other expert assistance is required, the services of a competent professional should be sought. Library of Congress Cataloging-in-Publication Data Names: Schofield, Neil C., author. | John Wiley & Sons, publisher. Title: Commodity derivatives : markets and applications / Neil C. Schofield. Description: Second edition. | [Hoboken, NJ] : Wiley, 2021. | Includes index. Identifiers: LCCN 2021002135 (print) | LCCN 2021002136 (ebook) | ISBN 9781119349105 (hardback) | ISBN 9781119349228 (adobe pdf) | ISBN 9781119349259 (epub) Subjects: LCSH: Commodity futures. | Commodity exchanges. | Derivative securities. Classification: LCC HG6024.A3 S364 2021 (print) | LCC HG6024.A3 (ebook) | DDC 332.64/57—dc23 LC record available at https://lccn.loc.gov/2021002135 LC ebook record available at https://lccn.loc.gov/2021002136 Cover Design: Wiley Cover Images: Oil refinery © Thatree Thitivongvaroon/ Moment Open/Getty Images, Airplane © cate_89/Shutterstock, Copper rods © Aksenenko Olga/Shutterstock, Silver © BestPix/Shutterstock, Gold bars © boykung/Shutterstock Set in 10/12pt STIXTwoText by SPi Global, Chennai, India Printed in 10 9 8 7 6 5 4 3 2 1

TO REGGIE, BRENNIE, ROBERT, AND GILLIAN TO NICKI

Contents

Preface

xi

CHAPTER 1 Fundamentals of Commodities and Derivatives 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8

Market overview Market participants Traded versus non-traded commodities Forward contracts Futures Swaps Options Exotic options

CHAPTER 2 Derivative Valuation 2.1 2.2 2.3 2.4 2.5 2.6 2.7

Asset characteristics Commodity prices and the economic cycle Principles of commodity valuation Forward price curves Commodity swap valuation Principles of option valuation Measures of option risk management

CHAPTER 3 Risk Management Principles 3.1 3.2 3.3 3.4 3.5 3.6

Defining risk Commodity market participants – the time dimension Hedging corporate risk exposures A framework for analysing corporate risk Hedging customer exposures Trading risk management

CHAPTER 4 Gold 4.1 4.2

1 2 3 6 8 8 10 11 14

18 18 18 19 21 32 39 44

58 58 60 61 62 63 66

76 The market for gold Gold price drivers

76 81

vii

viii

CONTENTS

4.3 4.4 4.5 4.6 4.7

The gold leasing and deposit market Hedging Trading gold Yield enhancement Summary

91 96 106 111 112

CHAPTER 5 Base Metals

114

5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10

114 115 119 120 122 130 133 134 139 157

Overview of base metal production The copper lifecycle Aluminium The Steel market The London Metal Exchange Base metal price drivers Electric Vehicles Structure of market prices Hedges for aluminium consumers in the automotive sector Summary

CHAPTER 6 Crude Oil 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9

159 Overview of energy markets The value of crude oil An overview of the physical supply chain Refining crude oil The demand for and supply of crude oil Price drivers The price of crude oil Trading crude oil and refined products Notes Managing price risk along the supply chain

159 159 163 165 172 179 189 195 209 212

CHAPTER 7 Natural Gas

237

7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9

237 238 238 242 245 250 257 260 263

Formation of natural gas Measuring natural gas The physical supply chain Deregulation and re-regulation The demand for and supply of natural gas Natural gas prices Natural gas price drivers Trading natural gas Natural gas derivatives

ix

Contents

CHAPTER 8 Electricity

280

8.1 8.2 8.3 8.4 8.5 8.6

280 283 285 291 301 313

What is electricity? The physical supply chain Market structure and regulation Price drivers of electricity Trading electricity – an overview Electricity derivatives

CHAPTER 9 Plastics 9.1 9.2 9.3 9.4 9.5 9.6 9.7 9.8 9.9 9.10

332 The chemistry of plastic The production of plastic Monomer production Polymerisation Applications of plastics Summary of the plastics supply chain Price determination Plastic price drivers Forwards and swaps Option strategies

CHAPTER 10 Bulk Commodities 10.1 10.2 10.3 10.4 10.5 10.6

The basics of coal The demand for and supply of coal Coal – the physical supply chain Coal derivatives Iron ore Freight markets – the fundamentals

CHAPTER 11 Climate and Weather 11.1 11.2 11.3 11.4 11.5 11.6 11.7 11.8

The science of climate change The consequences of climate change The argument against climate change History of human action against climate change Price drivers of emissions markets EU Emission Trading System Emission derivatives Weather derivatives

332 333 334 334 335 336 336 337 338 340

341 341 343 346 349 353 355

368 368 371 372 373 376 379 384 388

x

CONTENTS

CHAPTER 12 Agriculture

394

12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8

394 394 395 403 409 412 421 426

Agricultural markets Definitions Agricultural products Soft commodities Ethanol Price drivers Exchange traded agricultural and ethanol derivatives Over-the-counter agricultural derivatives

CHAPTER 13 Commodity-Linked Financing 13.1 13.2 13.3 13.4

The financing need Project finance Working capital and the asset conversion cycle Longer-term debt funding solutions

CHAPTER 14 Commodity Investing 14.1 14.2 14.3 14.4 14.5 14.6 14.7 14.8

Commodity investors Preferred instruments Market size Rationale for investing in commodities Commodity indices Total Return Swaps Exchange traded products (ETPs) Structured products

433 433 437 440 454

463 463 465 465 466 469 478 481 487

Glossary

499

Bibliography

507

Biography

510

Index

511

Preface

S

ince the start of this century, the commodity markets have fallen in and out of favour with the financial community. Throughout the preparation of the manuscript for the second edition, I would often see headlines that made me wonder whether my target audience would still exist by the time of publication! Having been in finance for over 30 years, one thing I have seen is the way in which history tends to repeat itself, so fingers crossed. My original motivation for writing the book, however, stemmed from my time working at Barclays Investment Bank, where I had tremendous difficulty in finding people who could provide classroom training on the various commodity products. Although many companies were able to provide training that described the physical market for each commodity, virtually no one provided training on over-the-counter (OTC) derivative structures. As they say, if you want a job done properly . . . While doing research for the first edition I felt that much of the available documentation either had a very narrow focus concentrating on just one product, or were general texts on trading commodity futures with a lot of coverage of subjects like technical analysis with little insight into the underlying markets. As a result, I have tried to write a book that documents in one place the main commodity markets and their associated derivatives. Within each chapter, I have tried to keep the structure fairly uniform. Typically, there will be a short section explaining what the commodity is in non-technical terms. For those with a background in any one specific commodity, this may appear somewhat simplistic, but is included to ensure a reader has sufficient background to place the subsequent discussion within some context. Typical patterns of demand and supply are considered as well as the main factors that will influence the price of the commodity. The latter part of each chapter focuses on the physical market of the particular commodity before detailing the main exchange traded and OTC products. One of the issues I faced when writing each chapter was to determine which products should be included. I was concerned that I might end up repeating ideas that had been covered in earlier chapters. Therefore, I have tried to document structures that are unique to each market in each particular chapter, while the more generic structures have been spread throughout the text. So why a second edition? While considering the prospect of writing a second edition, I came across this wonderful quote. ‘Writing as a profession is a sequence of failed ambitions. You never succeed in writing the book you want, or you’d never bother to write the next. So for writers, ambition is irrelevant. All you can do is write as well as your talent will allow’. —Faye Weldon, Financial Times, weekend magazine, 28/29 July 2012

xi

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PREFACE

Upon reflection, I pondered whether the first edition achieved a good balance between the markets and the derivatives, and so I decided to include more example transactions. I also took the opportunity to update the original text and expand the product coverage. For those of you who are wondering if it is worth upgrading to the second edition, here is a quick snapshot of the major changes. The first edition ran to about 100,000 words, while this shiny new version is twice the size. New topics include: ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪

Dual curve swap valuation. Option valuation within a negative price environment (the Bachelier model). Volatility skews, smiles, smirks, and term structures for the major commodities. Case studies on corporate failures linked to commodity risk management. Implications of growing interest in electric vehicles on commodity markets. Increased coverage of oil refiners and the challenge of output optimisation. Expanded sections on the Brent and WTI physical markets. Expanded section on the trading of electricity. Inclusion of iron ore and freight markets alongside coal in a chapter renamed as ‘bulk commodities’. New section on weather derivatives. Expanded content in the agriculture chapter. New chapter on commodity financing covering areas such as project finance, working capital management, and commodity-linked debt structures. Significant rewriting of the chapter on investment structures with new content illustrating why the concept of ‘roll yield’ is widely misunderstood.

Chapter 1 provides an overview of commodity markets and then outlines the main derivative building blocks. Chapter 2 considers the main principles of derivative valuation. This sets the scene for a discussion on the concept of risk management in Chapter 3. Two different perspectives are taken, that of a corporate with a desire to hedge some form of exposure and an investment bank that will take on the risk associated by offering any solution. Chapter 4 looks at the market for gold while Chapter 5 develops the metal theme to cover base metals. Some readers may complain that there is no coverage of other precious metals such as silver, platinum, and palladium, but I felt that including sections on these metals would amount to overkill and that gold was sufficiently interesting in itself to warrant an extended discussion. The next three chapters cover the core energy markets, the first of which is crude oil in Chapter 6. Chapter 7 covers natural gas markets while Chapter 8 looks at electricity. Chapter 9 describes the market for plastic, which at the time of the first edition was ‘the new kid on the block’. This has been rewritten to reflect how it has changed in the subsequent years. Chapter 10 has been renamed as ‘bulk commodities’ with the coverage widening to include iron ore and freight. Chapter 11 looks at the continuing interest in the trading of carbon emissions but also includes a discussion on weather derivatives. Chapter 12 covers agricultural products and has been expanded to cover more markets and a greater number of transactions. Chapter 13 is new and looks at different aspects of commodity finance. The book concludes by looking at the use of commodities within an investment portfolio.

Preface

xiii

As ever, it would be arrogant of me to assume that this was entirely my own work. The book is dedicated to the late Paul Roth, who was taken from us far too early in life. In the decade that I knew him, I benefited considerably from his insight into the world of derivatives. It never ceased to amaze how after days of pondering on a problem, I could half explain something I half understood to him and he would be able to explain it back to me perfectly in simple and clear terms. Thanks to the team at Wiley who were very patient and understanding while I was preparing the manuscript. I am sorry it took so long. General thanks go to my late father Reg Schofield who offered to edit large chunks of the original manuscript to tidy up ‘the English what I wrote’. Rachel Gillingham deserves a special mention for helping me express the underlying chemistry of a number of commodities within the book. Her input added considerable value to the overall manuscript. At Barclays Capital I would like to thank Arfan Aziz, Natasha Cornish, Lutfey Siddiqui, Benoit de Vitry, and Troy Bowler. They all endured endless requests for help and have given generously of their time without complaint. In relation to specific chapters, thanks go to Matt Schwab and the late Jon Spall (Gold); Angus Mcheath, Frank Ford, and Ingrid Sternby (Base Metals); David Paul and Nick Smith (Plastics); Thomas Wiktorowski-Schweitz, Orrin Middleton, Suzanne Taylor, and Jonathon Taylor (Crude Oil); Simon Hastings, Rob Bailey, David Gillbe (Electricity); Paul Dawson and Rishil Patel (Emissions); Rachel Frear and Marco Sarcino (Coal); Maria Igweh (Agricultural). Thanks also to Steve Hochfeld who made some valuable comments on the agricultural chapter. With respect to the second edition, John Fry and Neil Scurlock at ICE were generous in their time helping me out with crude oil EFPs. All of them contributed fantastic insights into the different markets and often reviewed drafts of the manuscript, which enhanced it no end. Very special thanks to Nicki, who never once complained about the project and has always been very interested and supportive of all I do. If I have missed anyone, then please accept my apologies, but rest assured I am grateful. Although I did receive a lot of help in compiling the materials, any mistakes that are in the text are entirely my responsibility. I am always interested in any comments or suggestions on the text and I can be contacted at: [email protected] Neil C. Schofield P.S. Hi to Alan and Roger, who dared me to include their names. You still owe me tea and toast from the first edition!

CHAPTER

1

Fundamentals of Commodities and Derivatives

A

fter the publication of the first edition of this text, many of the author’s friends not involved with financial markets often asked, ‘what are commodities’? Like many innocent questions, they are often very difficult to answer. In one sense, they are largely unprocessed or semi-processed goods, which are either consumed or can be processed and then resold. However, this definition will not always universally apply; for example, freight and carbon emission markets do not easily fall within this category. In general terms, commodities can be classified under different headings: Energy markets ▪ Crude oil and refined products (e.g. WTI/Brent, gasoline) ▪ Power and natural gas ▪ Natural gas liquids (e.g. propane and butane) ▪ Coal Industrial metals ▪ Copper, aluminium Precious metals ▪ Gold, silver Agricultural products ▪ Grains ▪ Softs (e.g. coffee) ▪ Livestock ‘Specialty’ markets ▪ Forest products (e.g. pulp and recovered paper) ▪ Carbon emissions ▪ Weather ▪ Freight

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

1.1

MARKET OVERVIEW

Figure 1.1 is a ‘big picture’ overview of commodity markets. In this diagram there are two main segments, the physical and the financial markets. The diagram was designed without a specific product in mind, but if the reader prefers some context, it may be helpful to think of a popular commodity such as crude oil. Within the physical side of the market there will be three main participants: producers, refiners, and consumers. In addition, trading houses will perform a variety of tasks, which are detailed in a subsequent section. The financial side of the market will incorporate those entities offering financing and risk management services as well as investors seeking to earn a return from the asset class. One aspect that is central to commodities is price discovery, and so the role of futures exchanges is key. To get a sense of the generic market flows associated outlined in Figure 1.1, consider the following issues faced by market participants: ▪ Commodities are not homogeneous – it is not particularly helpful to speak in general terms about commodities. For example, the phrase ‘crude oil’ is meaningless as the chemical properties of crude extracted in one location will vary from those in a different location. Trafigura (2016) argues that over 150 types of crude oil are traded worldwide.

TRADING HOUSES Risk management

HEDGE FUNDS

INSTITUTIONAL INVESTORS Strategic commodity exposure

View driven strategies

FINANCIAL MARKET

COMMERCIAL BANKS • Own physical assets • Financing • Risk management

FUTURES EXCHANGE • Benchmark price • Risk management • Source of supply

REFINERS

PRODUCERS

Commercial contracts

PHYSICAL MARKET

FIGURE 1.1 Commodity market overview.

CONSUMERS

Commercial contracts

TRADING HOUSES • Own physical assets • Trade physical commodity • Risk management

Fundamentals of Commodities and Derivatives

3

▪ Commodities need to be transformed into consumer goods – for example, oil needs to be refined to produce gasoline. ▪ Benchmarks help participants agree on a price for non-homogeneous products – so with respect to crude oil, a particular grade of oil could be priced relative to an agreed benchmark such as a futures contract that references Brent Blend. ▪ Production and consumption may not take place in the same geographical location – this means that there is a need for transportation. The mode of this transportation can vary for a single commodity. For example, in the USA, crude oil is typically moved by pipeline or train. In other areas such as Europe, sea-borne transport may be more common. ▪ Consumption and production may not occur simultaneously – a consumer may not need to take immediate delivery of a commodity, therefore storage and inventories are key factors. When there is a geographic element to the issue, it takes time for a commodity to be transported.

1.2

MARKET PARTICIPANTS

Market participants are able to manage the respective price risks using derivatives. Although risk management will be considered in greater detail in Chapter 3, it is worth considering some related motivations. Participants can: ▪ ▪ ▪ ▪ ▪

Avoid risk, Retain risk, Transfer risk, Reduce risk, Increase risk.

One of the key roles of derivatives is that they allow different market participants with different risk profiles and objectives to obtain a desired risk exposure. With respect to commodity derivatives the main participants will be physical market participants, price reporting agencies (PRAs), investment banks, commodity trading houses, hedge funds, or ‘real’ money accounts.

1.2.1

Physical market participants

Individual product supply chains will be considered in the respective chapter. In general terms, the commodity will need to be produced, refined, and then transformed into a product that can be consumed by the end user. Admittedly this general description does not capture all the different types of commodity supply chains, but the key point is that the participant will typically have some form of price risk at most points along the supply chain In simple terms, producers will be exposed to falling prices, consumers will be exposed to rising prices, and refiners, processors, and utilities will be exposed to

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

margins (e.g. the income generated from selling gasoline less the cost of buying crude oil). These participants are also faced with a variety of other risks which include: ▪ ▪ ▪ ▪

Credit, i.e. the unwillingness or inability of a customer to pay their debts. Logistical risks surrounding the movement of the commodity. Sourcing the right quality of commodity. Being able to finance day-to-day operations.

1.2.2

Price reporting agencies (PRAs)

One of the problems faced by various commodity markets over the years is one of price discovery. How does a market participant know if they are achieving fair market value? Consider the following quote from a market participant in 2011 with respect to the metal Rhodium, which was about to be used in the creation of an exchange traded fund aimed at the retail market: ‘With no futures benchmark . . . all the spot price transparency of molasses . . . and a risk reward with which only a supremely knowledgeable professional or those wet behind the ears would be comfortable . . . guess the target audience?’ (Financial Times, 2011) Since commodities are heterogeneous products, establishing a fair price has always been a challenge for market participants and the main conventions used either involve exchange traded prices (where available) or index values determined by PRAs. IOSCO (2012) defines a PRA as: ‘Publishers and information providers who report prices transacted in physical and some derivative markets and give informed assessment of price levels at distinct points in time’. They defined a crude oil assessment as: ‘The process of applying a methodology and/or judgement to market data and other information to reach a conclusion about the price of oil’. In response to IOSCO, one of the PRAs, Platts (2012) described their activities in relation to crude oil as follows: ‘Platts publishes assessments of spot prices for crude oil and refined products in various geographic regions based on a range of factual inputs including information on individual transactions supplied by market participants . . . Given the heterogeneous nature of the underlying transactions (in terms of trading parties, product quality, location, timing, delivery terms and other factors), the analysis conducted by Platts in determining its published price assessments is essentially qualitative, albeit based on a range of quantitative and factual inputs’.

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Fundamentals of Commodities and Derivatives

Price indexes can be used as the basis for settling commercial supply contracts (as could futures prices) or, in some cases used to determine the value of cash-settled futures transactions.

1.2.3

Investment banks

The services offered by investment banks will vary according to the business model that they adopt. Some banks may consider themselves to be a ‘full service’ entity, offering the ability to deal not just in derivatives, but to become counterparty to a physical trade. Other banks may offer more limited services, such as having a derivative service without the capability to execute physical transactions. A ‘full service’ bank will be able to offer several solutions to physical participants with some hypothetical examples shown in Table 1.1.

1.2.4

Commodity trading houses

The commodity trading house Glencore Xstrata describe themselves as follows (Glencore, 2011): ‘(the company) is a leading integrated producer and marketer of commodities, with worldwide activities in the marketing of metals and minerals, energy products and agricultural products and the production, refinement, processing, storage and transport of these products. Glencore operates globally, marketing and distributing physical commodities sourced from third party producers and own production to industrial consumers’. Traditionally, commodity trading houses would have simply bought commodities from producers and then sold them to consumers. However, the definition presented by Glencore Xstrata suggests that over time these entities have evolved to own and operate significant parts of various commodity supply chains. So, the notion of one company being fully integrated along a supply chain is no longer the norm. Indeed, many of the investment banking services highlighted in Table 1.1 could conceivably be offered by trading houses. A report by the Financial Times (2013) highlighted the extent of trading house involvement in the market: TABLE 1.1 Examples of services that could be provided by banks to facilitate commodity production and consumption. Sector

Problem

Solution

Crude oil and refined products Natural gas

Inventory is working capital intensive Cold weather creates increased demand, but there are delivery constraints with existing pipeline infrastructure Consumers seek favourable payment terms

Bank agrees to own inventory

Base metals

Banks buy pipelines or own storage facilities

Banks provide finance along the logistics chain or act as an intermediary between consumers and producers

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

▪ Those trading oil handled more than 15m barrels of oil a day. ▪ The main agricultural trading houses handled about half of the world’s grain and soybean trade flows. ▪ Two trading houses controlled about 60% of the zinc market. ▪ Relatively unknown companies can dominate smaller niche markets such as coffee. Their growth was attributed to four main factors: ▪ The economic boom after 2000 in several emerging economies. ▪ A strategic decision to acquire physical assets. ▪ Their ability to exploit price arbitrage opportunities because of their increasing presence along the supply chain. ▪ Consolidation in the period prior to 2000 which reduced competition.

1.2.5

Hedge funds

There is no single definition of a hedge fund given the wide range of structures and strategies used in this section of the market. However, they can be defined in terms of their characteristics: ▪ ▪ ▪ ▪

Investment ‘vehicles’ that pool the proceeds of their investor base. Access tends only to be available to a limited group of investors. Proceeds are actively managed. They aim to generate a return irrespective of underlying market conditions.

They are often associated with aggressive ‘view driven’ strategies and Chapter 3 includes a case study of the commodity hedge fund Amaranth that failed when its strategy in the US natural gas markets resulted in substantial losses.

1.2.6

‘Real money’ accounts

A real money participant is usually classified as an entity that is not able to borrow money to boost their available investment proceeds. Typically, this could include entities such as pension funds and insurance companies. Their participation in the commodity market is primarily for investment purposes. Also within this category it may be possible to include private and commercial banks that are offering commodity investment products to their retail customers.

1.3

TRADED VERSUS NON-TRADED COMMODITIES

One of the subtle characteristics of commodity markets is the difference between traded and non-traded commodities. What is the difference? An interesting case study that illustrates the key differences is the market for iron ore. Iron ore is used in the production of steel and, combined with steel, represents the world’s second largest commodity bloc by value (ICE, 2009). Macquarie Bank (2013)

Fundamentals of Commodities and Derivatives

7

points out that prior to 2003 the concept of a spot market for the metal did not exist in any meaningful sense. At this time, the traditional buyers were Japanese and Korean steel producers who purchased their metal using annual, fixed price, bilateral contracts with suppliers based mainly in Brazil and Australia. The annual benchmark price typically ran from 1 April–31 March in the following year. Emerging new consumers such as China struggled to purchase the required amount of metal under this market mechanism as the traditional sources of supply could not keep pace with the extra demand. This coincided with a new source of supply from India that was able to react quickly. This led to more ‘one-off’ transactions that resulted in the emergence of a spot market. At the same time commodities that were inputs to the steel making process, which already had developed spot markets, became more volatile. This increased the pressure on iron ore to respond accordingly. However, the phrase ‘spot’ within the context of commodities can sometimes be applied ambiguously. For example, in certain markets (e.g. gold), spot transactions will have a similar maturity to those seen in traditional financial markets (e.g. trade date plus two good business days). In other instances (e.g. crude oil), delivery is unlikely to occur in such a short time frame. ‘Spot pricing’ could also indicate that the contract is for short-term delivery with prices possibly referencing exchange traded futures prices. The increase in spot transactions meant that price-reporting companies now disseminated information on physical transactions on a more regular basis. One of the characteristics noted earlier is that commodity markets lack homogeneity and therefore pricing from a single benchmark has become the accepted practice. For iron ore a popular benchmark that has emerged is iron ore with a grade of 62%1 . The development of pricing benchmarks is an important step in the development of a commodity’s tradable status: ▪ They represent a standard reference point, which is based on actual market activity and is understood by market participants. ▪ Participants can enter commercial contracts or reference financial contracts to a price that is transparent, representative of the most liquid market, and is determined by a publicly available process. ▪ The benchmark price is the price of the commodity if it is used by many and varied participants. ▪ Once a benchmark price emerges, market participants can trade different grades of the commodity as a differential. So, iron ore with a grade of 58% would trade below the benchmark price, while a 65% grade would trade above the price. These differentials may also reflect the products’ country of origin and its availability. ▪ The emergence of a benchmark may result in the development of financial markets (e.g. derivatives) that can facilitate the hedging of underlying exposures.

1

Ore is essentially the rock that is extracted from through the mining process, which is then refined to extract the desired elements, such as iron. The ores may be classified by the amount of desired element that they contain. For example, iron ore ‘fines’ (heavy grains) can vary in grade from 30% to the mid 60%. (ICE, 2009)

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

The increased reporting of iron ore prices meant that the spot price provided a reference point for those entities still using the annual benchmark negotiations. Indeed, because of the financial crisis the spot price of the metal fell below the annual benchmark. This resulted in several consumers defaulting on their fixed price agreements in order to take advantage of the lower spot price. Once price assessments started to appear daily, which reported a standard grade of iron ore, financial products began to emerge. Exchange traded iron ore swaps were the first derivative that referenced this product. Thereafter, a forward curve for iron ore started to form, which was later boosted by the emergence of over-the-counter swaps and iron ore futures.

1.4

FORWARD CONTRACTS

A forward contract will fix the price today for delivery of an asset in the future. Gold sold for spot value will involve the exchange of cash for the metal in two days’ time. However, if the transaction required the delivery in, say, one month’s time, it would be classified as a forward transaction. Forward contracts are negotiated bilaterally between the buyer and seller and are often characterized as being ‘over-the-counter’ (OTC). The forward transaction represents a contractual commitment and so, if gold is bought forward at USD 1,430.00 an ounce, but the price of gold in the spot market is only USD 1,420.00 at the point of delivery, one cannot walk away from the forward contract and try to buy it in the underlying market. However, it is possible for both parties to mutually agree to terminate the contract early. This could be achieved by agreeing upon a ‘break’ amount, which would reflect the current economic value of the contract. Typically, this is done using a process that is referred to generically as ‘marking to market’. An easier way to understand the issue is to use the concept of an exit price. This is typically taken to be the amount for which an asset could be sold, or a liability settled in an ‘arm’s length’ transaction. A variation on the standard contract is a floating forward. In this type of transaction, a market participant commits to buy or sell the underlying at a future date, but the applicable price is only set at the point of delivery. The final price that is agreed upon may be based on some pre-agreed formula. For example, the price could be the average of daily spot prices in the month prior to settlement.

1.5

FUTURES

A futures contract is traded on an organised exchange, with the CME Group being one example. Economically, a future achieves the same result as a forward by offering price certainty for a period in the future. However, the key difference between the contracts is in how they are traded. The contracts are uniform in their trading size, which is set by the exchange. For example, the main features of the contract specification for the gold future appear in Table 1.2.

Fundamentals of Commodities and Derivatives

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TABLE 1.2 Gold futures contract specification. Trading unit

100 troy ounces

Price quotation Trading months

US dollars and cents per troy ounce Trading is conducted for delivery during the current calendar month; the next two calendar months; any February, April, August, and October falling within a 23-month period; and any June and December falling within a 72-month period beginning with the current month. USD 0.10 (10c) per troy ounce (USD 10.00 per contract) Trading terminates at the close of business on the third to last business day of the maturing delivery month. Deliverable The first delivery day is the first business day of the delivery month. The last delivery day is the last business day of the delivery month. Margins are required for open futures positions.

Minimum price fluctuation Last trading day Settlement method Delivery period

Margin requirements Source: CME Group

Traditionally, there are some fundamental differences between commodity and financial products traded on an exchange basis. Historically, one of the key differences is that futures require collateral to be deposited when a trade is executed (known as initial margin). As a rule of thumb, the initial margin will be about 5% of the market value of the contract. Although different exchanges will work in different ways, the remittance of profits and losses may take place on an ongoing basis (variation margin) rather than at the maturity of the contract. However, financial markets have evolved such that OTC forward contracts will now have very similar margining requirements to futures contracts. Another difference between forwards and futures relates to the grade and quality specification. If one is delivering a currency, the underlying asset is homogenous – a dollar is always a dollar. However, because metals vary in shape, grade, and quality, it is important to ensure an element of standardisation so the buyer knows what they are receiving. Some of the criteria that CME Group apply include: ▪ ▪ ▪ ▪

The seller must deliver 100 troy ounces (+/-5%) of refined gold. The gold must be of a fineness of no less than 0.995. It must be cast either in one bar or three one-kilogram bars. The gold must bear a serial number and identifying stamp of a refiner approved and listed by the Exchange.

Anecdotal estimates suggest that the vast majority (ca. 95%) of futures contracts are terminated prior to their expiry date. This is perhaps a reflection that most participants will use the instruments for risk management purposes rather than as a source of supply.

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1.6

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

SWAPS

In a swap transaction two parties agree to exchange cash flows, whose size are based on different price indices. Typically, this is represented as an agreed fixed rate against a variable or floating rate. Swaps are traded on an agreed notional amount, which is not exchanged but establishes the magnitude of the fixed and floating cash flows. Swap contracts are typically of longer-term maturity (i.e. greater than one year) but the exact terms of the contract will be open to negotiation. For example, in many base metal markets a swap transaction is often nothing more than a single period forward. This is because the forward transaction may be cash settled which would involve the payment of the agreed forward price against the spot price at expiry. The exact form may vary between markets, with the following merely a sample of how they may be applied in a variety of different commodity markets. ▪ Gold – Pay fixed lease rate vs. receive variable lease rate ▪ Base metals – pay fixed aluminium price vs. receive average price of near dated aluminium future ▪ Oil – pay fixed West Texas Intermediate (WTI) price vs. receive average price of near dated WTI future Swaps will usually be spot starting and so become effective two days after they are traded. However, it is also possible for the swap to become effective sometime in the future – a forward starting swap. The frequency with which the cash flows are settled is open to negotiation but they could vary in tenor between 1–12 months. Where the payments coincide, there is a net settlement between the two parties. One of the features of commodity swaps not shared by financial swaps is the use of an average rate for the floating leg. This is because many of the underlying exposures that commodity swaps are designed to hedge will be based on some form of average price. The motivation for entering a swap will differ between counterparties. For a corporate entity one of their main concerns is risk transference. Take a company that purchases a particular commodity at the market price at regular periods in the future. To offset the risk that the underlying price may increase, they would receive a cash flow under the swap based on movements in the market price of the commodity and pay a fixed rate. If the counterparty to the transaction were an investment bank, the latter would now have the original exposure faced by the corporate. The investment bank would be receiving fixed and paying a variable rate, leaving them exposed to a rise in the price of the underlying commodity. In turn, the investment bank will attempt to mitigate this exposure by entering some form of offsetting transaction. The simplest form of this offsetting deal would be an equal and opposite swap transaction. To ensure that the bank makes some money from this second transaction, the amount they receive from the corporate should offset the amount paid to the offsetting swap counterparty.

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Fundamentals of Commodities and Derivatives

Swaps are typically traded on a bid-offer spread basis. From a market maker’s perspective (that is the institution giving the quote) the trades are quoted as follows: Bid

Offer

Pay fixed Receive floating Buy Long

Receive fixed Pay floating Sell Short

Although the terms buy and sell are often used in swap quotes, the actual meanings are often confusing to anyone looking at the market for the first time. In the author’s opinion, the most unambiguous way to trade these instruments is to state who is the payer and who is the receiver of the fixed rate. The convention in all swap markets is that the buyer is receiving a stream of variable cash flows for which the price is a single fixed rate. Selling a swap requires the delivery of a stream of floating cash flows for which the compensation is a single fixed rate.

1.7

OPTIONS

A forward contract offers price certainty to both counterparties. However, the buyer of a forward is locked into paying a fixed price for a particular commodity. This transaction will be valuable if the price of the commodity subsequently rises, but will be unprofitable in the event of a fall in price. An option contract offers the best of both worlds. It will offer the buyer of the contract protection if the price of the underlying moves against them, but allows them to walk away from the deal if the underlying price moves in their favour. This leads to the definition of an option as the right, but not the obligation, to either buy or sell an underlying commodity sometime in the future at a price agreed upon today. An option that allows the holder to buy the underlying asset is referred to as a call. Having the right to sell something is referred to as a put. The price at which the two parties will trade if the option is exercised is referred to as either the strike price or the exercise price. The strike can be set at any level and is negotiated between the option buyer and seller. Options may be either physically settled (that is, the commodity is delivered/ received) or cash settled. The process of cash settlement removes the need to make or take delivery of the underlying asset, but retains the economics of a physically settled option. Cash settlement involves the seller paying the buyer the difference between the strike and the spot price at the point of exercise. The payoff for a cash-settled call option is: MAX (underlying price − strike price, 0)

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Where: MAX means ‘the maximum of’ The payoff for a cash-settled put option is: MAX (strike price − underlying price, 0) Options come in a variety of styles relating to when the holder can exercise their right. A European style option allows the holder to exercise the option only on the final maturity date. An American style option allows the holder to exercise the option at any time prior to final maturity. A Bermudan option allows the holder to exercise the option on a pre-agreed set of dates prior to maturity. An option that is in-the-money (ITM) describes a situation where it would be more advantageous to trade at the strike rather than the underlying market price. Take for example an option to buy gold at USD 1,400 an ounce when the current spot price is say, USD 1,425. The option to buy at the strike is more attractive than the current market price. Where the option is out-of-the-money (OTM), the strike is less attractive than the market price. If the same option had a strike rate of USD 1,430, the higher strike makes the option less attractive than buying the underlying at a price of USD 1,420. Finally, an option where the strike is equal to the current market price is referred to as an at-the-money (ATM). Since options confer rights to the holder, a premium is payable by the buyer. Typically, this is paid upfront, but certain option structures are constructed to be zero premium or may involve deferment of the premium to a later date. Premiums on options are quoted in the same units as the underlying asset. So, since physical gold is quoted in dollars per troy ounce, the premium will be quoted in the same manner. Many of the derivatives strategies based on options that are discussed within the text are illustrated based on the value of the option at maturity. These are illustrated as follows: In the upper left-hand of Figure 1.2, the purchase of a call option is illustrated. If at expiry the option market price is lower than the strike, the option is not exercised, and the buyer loses the premium paid. If the underlying price is higher than the strike price, the option is exercised and the buyer receives the underlying asset (or its cash equivalent), which is now worth more in the underlying market than the price paid (i.e. the strike price). This profit profile is shown to the right of the strike price. On the other side of the transaction there is the seller of a call option (top right quadrant of Figure 1.2). The profit and loss profile of the seller must be the mirror of that of the buyer. So, in the case of the call option, the seller will keep the premium if the underlying price is less than the strike price, but will face increasing losses as the underlying market price rises. The purchase of a put option is illustrated in the bottom left quadrant of Figure 1.2. Since this type of option allows the buyer to sell the underlying asset at a given strike price, this option will only be exercised if the underlying price falls. If the underlying price rises, the buyer loses the premium paid. Again, the selling profile for the put is the mirror image of that faced by the buyer. That is, if the underlying price falls, the seller will be faced with increasing losses. However, if the market price rises, the seller will keep the premium.

13

Fundamentals of Commodities and Derivatives Buy Call

Sell Call

Profit

Profit Strike Strike Underlying price

Loss

Underlying price

Loss

Buy Put

Sell Put

Profit

Profit

Strike Underlying price

Loss

Underlying price

Loss

FIGURE 1.2 Profit and loss profiles for options at expiry. Options arguably offer great flexibility to the end user. Depending on their motivation, it can be argued that option usage are categorised in four different ways. Firstly, they can be used to take a directional exposure to the underlying market. For example, if a user thought the underlying price of gold might increase, they could buy physical gold, a future, or a call option. Buying physical gold requires the outlay of proceeds, which may need to be borrowed. Buying a future reduces the initial outlay of the physical but will incur a loss if the future’s price falls. Buying a call option involves some outlay in the form of premium but allows for full price participation above the strike and limited downsides if the price falls. The second usage for options is an asset class in its own right. Options possess a unique feature in implied volatility, and this can be isolated and traded. The focus of this type of strategy is how the option behaves prior to its maturity. The third motivation, which is particularly relevant to the corporate world, is as a hedging vehicle that allows a different profile than that of the forward. With a little imagination it is possible to structure solutions that will offer differing degrees of protection against the ability to profit from a favourable movement in the underlying price. The final motivation is options as a source of outperformance. For example, if an end user owns the underlying asset (e.g. central bank holdings of gold) they can use options to exceed some performance benchmark such as money market deposit rates. From a hedger’s perspective, options could be used to outperform an ordinary forward rate.

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1.8

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

EXOTIC OPTIONS

Exotic options are a separate class of options where the profit and losses upon exercise do not correspond to the plain vanilla American and European styles. Although there is a proliferation of different types of exotic options, it is worth introducing some of the key building blocks, which feature prominently in derivative structures.

1.8.1

Binary options

A binary option (sometimes referred to as a digital) is very similar to a simple bet. The buyer pays a premium and agrees to receive a fixed return. Very often the strike rate on the digital is referred to (somewhat confusingly) as a barrier. With a European style call option, the holder will deliver the strike price to the seller and receive a fixed amount of gold. However, the value of the gold will depend on where the value of gold is trading in the spot market upon exercise. With a binary option the buyer will receive a fixed sum of money if the option is exercised, irrespective of the final spot level. An example of a long digital call and a long digital put is shown in Figure 1.3.

1.8.2

Barrier options

The purchaser of a barrier option will either: 1. Start with a conventional ‘plain vanilla’ option that could subsequently be cancelled prior to maturity (known as a knock out), or, 2. Start with nothing and be granted a conventional option prior to the maturity of the transaction (known as a knock in). Profit

Profit

Underlying price

Underlying price

Loss

Digital Call

FIGURE 1.3 Digital calls and puts.

Loss

Digital Put

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Fundamentals of Commodities and Derivatives

The cancellation or granting of the option will be conditional upon the spot level in the underlying market reaching a certain level, referred to either as a barrier or trigger level. The position of the barrier could either be placed in the out-of-the money region or in the in-the-money region. This will be above or below the current spot price, as we will show below. The former are referred to as standard barriers with the latter known as reverse barriers. This could result in what may initially seem like a bewildering array of possibilities. Figure 1.4 summarises the concepts. To illustrate the concept further let us return to the option example illustrated earlier and concentrate on analysing a call option. We will assume the option is out-of-the-money and the current market conditions exist: Spot Strike Maturity

USD 1,425 USD 1,430 Three months

The purchaser of a standard knock in barrier option would be granted a European style option if spot hit a certain trigger. Since it is a standard barrier option, the trigger must be placed in the out-of-the-money region so it would be set at say, USD 1,420. Consequently, spot must reach USD 1,420 or below before the option is activated (knocked in), hence the name a down and in. If the purchaser started with a standard barrier call option with the trigger at USD 1,420, it would be a down and out. That is, if spot were to fall to USD 1,420 or lower the option contract would be cancelled. A reverse knock in call option would have the barrier placed in the money at, say, USD 1,435. A purchaser of such an option would have a contract that would grant a call option with a strike of USD 1,430 if spot hits USD 1,435. The final example would be a reverse knock out call option, with the trigger again set at USD 1,435. Here the purchaser starts the transaction with a regular call option, which would be cancelled if spot reached USD 1,435 – an up and out contract.

Barrier options

Standard barriers Knock in options Call option ‘down and in’

Put option ‘up and in’

Reverse barriers Knock out option

Call option ‘down and out’

Put option ‘up and out’

FIGURE 1.4 Taxonomy of barrier options.

Knock in option Call option ‘up and in’

Put option ‘down and in’

Knock out option Call option ‘up and out’

Put option ‘down and out’

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Spread options

A spread option pays off based on the difference between the price of two underlying assets, relative to a pre-agreed strike. A call option will pay off if the spread is greater than the strike, while a put option will pay off if the spread is lower than the strike. Call payoff = MAX (Price of asset 1 − price of asset 2 − strike, 0) Put payoff = MAX (Strike − price of asset 1 + price of asset 2, 0) Spread options are relatively more popular in commodities than in traditional financial assets. For example, a participant may wish to hedge or take exposure between: ▪ The cost of an input and the revenue earned from an output (e.g. cost of crude oil and revenue from gasoline). ▪ The prices between a commodity traded at two different locations. ▪ The price of a single commodity future for two different delivery dates. These examples will be discussed in detail in their respective chapters. From a valuation perspective, these options require an additional valuation input and that is the correlation that exists between the two asset prices. To illustrate this, consider a spread option structured as a call, which will pay off if the spread between two asset prices increases beyond a pre-agreed strike. If the two asset prices are negatively correlated, an increase in asset price 1 will be associated with a decrease in asset price 2. This relationship increases the probability that the option will end up more deeply in the money and as such the seller will charge a higher price.

1.8.4

Average rate options

Anecdotally, average rate options (‘avros’) are the most common type of commodity option. Regular or ‘vanilla’ option payoffs will reference a single underlying asset price at maturity, with the payoff being made relative to the strike. However, an average rate option will pay out based on an average of prices covering a pre-agreed period prior to maturity. The expiry payoffs of average rate options are: Call option = MAX (average underlying price − strike price, 0) Put option = MAX (strike price − average underlying price, 0) One of the reasons for the popularity of such contracts in commodities is that it reflects the way in which physical supply contracts are structured. A refiner who agrees to buy crude oil from a producer will avoid paying a potentially high price if the terms of the deal reference market prices on a single date. Although averaging prices will dampen the effect of volatile price movements it also means that the refiner will not be able to benefit if the price of the commodity suddenly falls. A common feature of

Fundamentals of Commodities and Derivatives

17

commodity derivatives is that the payoff on the instrument should match that of the commercial contract to avoid a cash flow mismatch. One of the characteristics of an average rate option is that they will show a premium reduction over the equivalent European option; it is not really a cheap alternative to a vanilla option. As an example, the cost of a six-month call option on a crude oil future with an at-the-money strike price of USD 50.00 and an implied volatility of 30%. The cost of a vanilla option on this asset is USD 4.20/barrel, but if the terms of the contract are altered such that the final settlement price is an average of the futures prices over the last three months of the transaction, the cost of the option falls to USD 3.96. This is because the implied volatility of the average rate option references an average price series which will be lower than a non-averaged equivalent. Another way of thinking about the problem is that since the premium of an option is a function of payoff received by the buyer, a payoff based on an average price series will always be lower than a non-averaged equivalent.

CHAPTER

2

Derivative Valuation

T

he individual demand and supply dynamics for each commodity will be analysed within the respective chapter. This section considers some of the bigger picture issues that will influence prices.

2.1

ASSET CHARACTERISTICS

Greer (1997) argues that there are three different types of asset class. ▪ Capital assets – examples include bonds, which pay an investor a stream of fixed cash flows and equities, which would normally pay a stream of dividends. These types of assets can be valued using discounted cash flow (DCF) techniques. For example, for bonds, value is determined by present valuing the fixed cash flows. For equities, techniques such as the dividend discount model can also be used for valuation purposes. ▪ Consumable/transformable assets – According to Greer: ‘You can consume it. You can transform it into another asset. It has economic value. But it does not yield an ongoing stream of value’. Examples of this type of asset would include most commodities such as agriculture, metals, and energy. Greer’s comment is significant: ‘the profound implication of this distinction is consumable/transformable (C/T) assets . . . cannot be valued using net present value (NPV) analysis. C/T assets must be valued more often based on the particular supply and demand characteristics of their specific market.’ ▪ Store of value assets – this type of asset cannot be consumed, nor does it generate income. However, it does have value. One example given by Greer is fine art. Auctions of fine art at substantial prices are often reported in the press.

2.2

COMMODITY PRICES AND THE ECONOMIC CYCLE

Figure 2.1 illustrates in a stylised manner the different parts of the economic cycle as it relates to commodities and the likely price reaction. The diagram is based on Macquarie (2015) reported in Commodities Now (2015).

18

19

Derivative Valuation

Strong demand push or deficit market

Pricing to encourage supply

Prices stable

Demand destruction / capex accelerating

Supply constraint / Capex lagging

Stocks drawing / limited new supply

Prices stabilise at low level

High stocks / strong supply reaction

Price acceleration

Price peaking

Market in balance / capex peaking

Strong supply growth / stocks building

Prices falling

Severe price decline

FIGURE 2.1 Commodity prices and the economic cycle. Source: Macquarie

2.3

PRINCIPLES OF COMMODITY VALUATION

Within the context of commodities, analysts who have gravitated from traditional financial assets have tried to apply NPV techniques to value commodities. However, the application of these models has proved to be problematic because, as Greer points out, commodities are not bonds and equities. Barclays (2011) argues, ‘Most financial assets can be understood and valued through a cash flow discounting technique approach. Commodities are different – they are not capital assets and are subject to unique supply and demand forces that lead to complex valuation dynamics’. Examples of some of these dynamics are given below: Inventories One subtle fact of commodity price behaviour relates to the balance of supply that is either above or below ground. Typically for gold there is substantial above ground inventories and as such, short-term prices are not significantly influenced by changes in either fundamental demand or supply (e.g. a change in mine supply). However, for a metal such as copper, the dynamics tend to be different with lower levels of inventories being common resulting in greater short-term price sensitivity to changes in fundamental demand and supply. Seasonality The demand and supply for certain commodities may only occur at certain times in the year. So, the demand for heating oil may be greater in winter than in summer. This would result in higher prices for winter delivery and lower prices for summer delivery.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Price inelasticity One of the ways to understand commodity price formation is to appreciate that short demand and supply are relatively inelastic (Morgan Stanley, 2009). Inelasticity describes how easily prices will respond to changes in demand and supply factors. Inelastic demand occurs when a change in price does not immediately impact the demand for a product: ▪ The cost of the commodity is a small component of the final product – if the price of coffee beans were to increase, the price of a consumer’s daily caffeine drink may not change significantly. ▪ The commodity is an essential input – planes need jet fuel to fly; gold rings require gold as an input. For example, during periods of increased energy prices, airlines have been able to increase fares by adding a fuel surcharge fee to tickets. It may well be that people decide to economise, but this is an example of the cost being passed to the consumer. ▪ Product substitution – Another key theme within commodity price formation is the ability to substitute a cheaper alternative commodity for the more expensive input. This may be difficult with respect to airplanes, which are configured to burn a specific type of fuel. ▪ New technology – prices of commodities will evolve as new technology is implemented. However, this factor will have a greater impact in the longer rather than shorter term. ▪ Product and brand loyalty – the author confesses to being a coffee addict. He does not care how much his Americano will cost as part of the pleasure of the coffee shop environment (and the free Wi-Fi). Inelastic supply occurs when output cannot respond quickly to a change in price: ▪ There may be a finite supply of the product, e.g. carbon-based energy sources. ▪ There may be a finite amount of a related production input, e.g. land or water supplies. ▪ There may be a lack of infrastructure within the country of supply that will make it difficult to increase supply on a short-term basis. ▪ Geopolitical issues may have an adverse impact on future supply. ▪ New technology to increase supply will take time to have an effect. Marginal cost Marginal cost describes how the total cost of producing a commodity changes with each incremental unit. Within the context of commodity valuation, it is sometimes described as ‘cost support’. Theoretically, the marginal cost of producing a commodity should represent the minimum selling price for a commodity, but this condition may not always hold in the short term. ‘While costs remain a critical variable in forecasting commodity price, they are more relevant for gauging long-term pricing; in the short term, there is much less rigid support in bear markets than many expect.’ (Credit Suisse, 2013). They also make the following points as to why this situation may arise: – In the short term, many costs are fixed, and so excess supply may lead to prices falling below the cost of production.

Derivative Valuation

21

– A producer may be willing to suffer short-term losses in anticipation that their fortunes may improve rapidly. Mean reversion Mean reversion is the tendency for prices to revert to some long-term average value. Casual empiricism suggests that commodity prices do not continually rise or fall although they are certainly volatile. However, this is an imprecise concept as there is no standard definition of what constitutes long-term.

2.4

FORWARD PRICE CURVES

A forward (or futures) price is a value that a participant can fix today that will apply to some future time. It is a representation of the value in the future attributed by the market to a commodity at a single point in time based on trading activities. For example, if crude oil prices have fallen, a refinery may take the opportunity to fix the price for oil to be delivered in say, six months’ time. Arguably, understanding how commodity forward curves move is central to understanding market behaviour. Figure 2.2 illustrates the forward price curve for West Texas Intermediate. The chart illustrates some interesting features of forward price behaviour: ▪ In some circumstances short-dated forward prices are higher than long-dated prices and vice versa. These conditions are referred to as backwardation and contango respectively and are analysed in greater detail in the next section. ▪ Shorter-dated contracts are more volatile than longer-dated contracts. ▪ At low prices, the forward price curve slopes upward. As prices rise, the curve flattens and eventually inverts.

2.4.1

Forward prices – a market in contango

Within the commodities world, there are two ways of describing the state of a forward market: contango or backwardation. Contango describes a situation where the price for forward delivery is higher than the price for spot delivery, while backwardation exists when the forward price is below the spot price. Although both of these states exist in the pricing of traditional financial products, the role of the underlying physical markets in commodities is much more important, particularly when demand exceeds supply. It is very rare for financial products to experience prolonged periods where the principles of ‘no arbitrage valuation’ do not hold. Consider for a moment the world of equity indices. The fair forward value of an equity index is determined using a technique that is sometimes referred to casually as ‘cash and carry’ pricing. Suppose that an investment banking client wishes to buy a basket of equities that exactly matches the composition of the domestic equity index for delivery in one year’s time. To hedge this exposure, the bank will immediately buy all of the stocks according to their respective weights in the index, which is assumed to be trading at a spot value of 100 points. To finance the purchase of these shares the bank borrows the equivalent of 100 index points at its cost of funding which is assumed to be 3% p.a. This would result in a funding cost equivalent of three index points. While holding the stocks for one year, it is assumed that the

22

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS 120.00 110.00 100.00 90.00 80.00 70.00 60.00 50.00 40.00 30.00

Spot 2009

1 year 2011

2 year 2013

3 year 4 year 5 year 2014 2015

6 year 2016

FIGURE 2.2 Forward price curves. Source: CME Group stocks will pay a dividend equivalent to 1% p.a., i.e. one index point. Since the stocks are not required for 12 months, they can be lent out to earn some fee income, which is assumed to be the equivalent of 0.5 index points. This means that the fair value of the index constituents at maturity will be: Forward price = spot price + financing cost − dividend income − securities lending fee = 100 + 3 − 1 − 0.5 = 101.5m So, 101.5 index points is the minimum that the bank will charge for this transaction. It is important to realise that this forward is not a forecast. It is a mechanical breakeven calculation, not ‘the market’s best guess of where the future spot price will be’. Now imagine a slightly different scenario, but based on the same observed values. Suppose a trader sees another bank quoting a 12-month forward on the index of 101. This would suggest that this forward is trading below ‘fair value’ of 101.5. Ignoring all transaction costs and bid offer spreads, the trader could profit from this mispricing by executing the following transaction: ▪ Buy the index forward for delivery in 12 months at an agreed cost of 101 from the other bank. ▪ Borrow the constituent shares and sell them for spot value raising the equivalent of 100 index points.

Derivative Valuation

23

▪ Place the proceeds of the sale on deposit for 12 months to earn three index points of interest. ▪ Pay the lender of the shares the one index point of dividend income received during the year1 . The bank will also have to pay a borrowing fee, which is assumed to be 0.5 index points. ▪ The net result of these trades is that the forward purchase incurs a cost of 101 index points while the combination of the spot trades results in income of 101.5 (+100 + 3 − 1 − 0.5). Overall, the bank has been able to lock in an arbitrage profit of 0.5 index point. Within the equities market such anomalies would be very short-lived given the liquidity of the market and the speed with which trades can be executed. Although generally speaking commodities are different, the forward valuation of certain commodities will follow the time value of principles outlined above. One such example is gold, which is often traded like a financial commodity. We will use the example of a gold producer who approaches a bank asking for a price for delivery of gold in, say, six months. The price quoted by the bank is not a guess and neither is it a forecast of where it thinks the price of gold will be at the time of delivery. Rather the price quoted will be driven by the cost of hedging the bank’s own exposure. This illustrates one of the key maxims of derivative pricing – the cost of the product is driven by the cost of the hedge. This approach to valuation is sometimes referred to as a ‘cash and carry’ trade. If the bank does not hedge its price exposure then in six months’ time it will take delivery of gold at the pre-agreed price and will then be holding an asset whose market value could be lower (or higher) than the price paid to the producer. To avoid the risk of a fall in the gold price, the bank executes a series of transactions on the trade date to mitigate the risk. Since the bank is agreeing to receive a fixed amount of gold in the future, it sells the same amount in the spot market to another institution, say, another investment bank. However, the bank has sold a quantity of metal today that it will not take delivery of for six months. To fulfill this spot commitment, it can borrow the commodity until it receives the gold from the producer. The gold could be borrowed from a central bank that would be paid interest at the maturity of the loan. Having sold the gold spot and borrowed to cover the sale, the bank is now holding dollar proceeds. Since the bank would be looking to manage its cash balances, these dollars would now be invested until the producer delivers the gold. As a result, it is possible at the inception of the forward trade to identify all of the associated cash flows, allowing the bank to quote a ‘fair value’ of theoretical price that will ensure no loss at the point of delivery, irrespective of the prevailing price. In this example the maximum amount the bank will pay the producer cannot exceed: ▪ Proceeds received from the spot sale plus, ▪ The interest received from the dollar deposit less, ▪ The interest paid to the lender of gold. 1

In a securities lending deal market convention dictates that the lender of the share will retain any dividends paid during the life of the loan.

24

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

A simple example may help illustrate the point. We will assume that the producer asks for a six-month (182 days) forward price. For simplicity we will calculate the forward price for a single ounce. In the cash market, gold is trading at USD 1,425.40 per ounce, so the dealer agrees to sell one ounce. In order to complete the spot delivery, he borrows the same amount from the local central bank for 6 months at a lease rate of 0.11570% per annum. The dollars received from the spot sale are put on deposit for 6 months at a LIBOR to earn, say, 3.39% per annum. The interest cost of borrowing the metal is USD 0.8333 (spot x lease rate x 182/360) and that USD 24.43 is earned from the cash deposit (spot sale proceeds x 6-month LIBOR x 182/360). So, the maximum amount he can afford to pay the producer is USD 1,449.10 (rounded). This is calculated as spot sale proceeds plus interest on LIBOR deposit minus the borrowing fee (USD 1,425.40 + USD 24.43 − USD 0.8338). This fair value is a breakeven price for the trader and so may be adjusted to build in an element of profit. So the forward price is the spot price plus the cost of carrying an underlying hedge. It is important to note that the shorter the time to maturity, the smaller will be the differential between the spot and forward price since the hedge is carried for a shorter period. Indeed, if we were to recalculate the forward price applicable for a single fixed date in the future on a daily basis, the differential would reduce (all other things being equal) until the final calculation when spot and forward becomes the same thing and the two prices will have converged. The observed forward price of a commodity is kept in line with its fair value by the possibility of arbitrage similar to the principles outlined in the equity example. In the previous example where the fair value of gold for six-month delivery was USD 1,449.10, it is unlikely that the market price would be significantly different. Say that a forward market price of USD 1,440 was observed. With the fair value the instrument calculated at USD 1,449.10, the commodity would be described as being ‘cheap to fair value’. In this situation an arbitrager could: ▪ ▪ ▪ ▪

Buy the commodity forward, paying USD 1,440 upon delivery. Short the gold in the spot market to earn the spot price of USD 1,425.40. Invest the cash proceeds at LIBOR earning 3.39% for six months to earn USD 24.43. Borrow gold in the lease market to fulfill the short spot sale paying a six-month lease rate, which equates to a cash amount of USD 0.8333. ▪ Repay the gold borrowing upon receipt of the metal under the terms of the forward contract. The arbitrager would end up with a net profit of USD 9.10 the difference between the theoretical value of the forward contract (USD 1,449.10) and the market value of the forward (USD 1,440).

2.4.2

Forward prices – a market in backwardation

Backwardation describes a situation where the prices for shorter-dated forward contracts are higher than those of longer-dated forward contracts. Forward pricing theory dictates that the market maker quotes a forward price such that all expenses incurred, as well as any income benefits they may have derived from carrying an underlying hedge,

Derivative Valuation

25

are passed on to the customer. With respect to gold, storage on an unallocated basis is not considered to be a significant expense, and is therefore traditionally not included in forward pricing considerations. However, with base metals and energy products, storage and insurance costs are included. Based on conventional time value of money principles, this should give a forward price relationship of: Forward price = Spot price + LIBOR + storage and insurance costs From this relationship it follows that the fair value of a forward contract should always be greater than the spot value. However, many commodity markets experience conditions of backwardation (e.g. some base metals, crude oil), which suggests that the previous equation is incorrectly specified. To explain this apparent anomaly some analysts adjust the equation to include a term referred to as the ‘convenience yield’. So now the forward price equation reads: Forward price = Spot price + LIBOR + warehousing and insurance costs − convenience yield The convenience yield can be defined as the “flow of services and benefits that accrues to an owner of a physical commodity, but not to an owner of a contract for future delivery of the commodity. This can come in the form of having a secure supply of raw materials and hence, eliminating the costs associated with stock outs.” The magnitude of the convenience yield will vary according to the physical balance of demand and for the underlying commodity. If the commodity is in very short supply, its value will rise, moving towards zero in ‘normal’ supply conditions. If, however, the minimum value of the convenience yield is zero, there is no maximum as its value is driven by the consumer’s need to obtain the physical commodity immediately. Initially, the author found the concept of convenience yield as particularly strange. Over the years anecdotal conversations with market practitioners have suggested one common theme: In the real world no one uses convenience yield. Some of the anecdotal comments made to the author include: ▪ There is no such thing as convenience yield. Commodities yield nothing: they do not carry coupons and they do not pay dividends. ▪ It is a financial mathematician’s tool to try and describe a market behaviour that they never witness in traditional financial products and so cannot explain. ▪ It is just a number that makes the traditional forward pricing formula work. In the case of a backwardated market the forward market price is lower than the spot price suggesting that the contract is mispriced or trading ‘cheap to fair value’. If this were the case a speculator should be able to buy the cheap forward contract, sell it for spot value and hold the combined position to maturity to realise a profit. This strategy, outlined in the previous section covering contango markets, would allow the arbitrager to earn the difference between the mispriced forward and its theoretical value. The reason this cannot happen and also why the market will remain in a prolonged state of

26

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

backwardation is that when selling the contract in the spot market, the participant will need to obtain the commodity to fulfill the short commitment. Since the availability of the commodity in a backwardated market is by definition very scarce, supplies for spot delivery are simply not available. Hence this apparent mispricing will persist for prolonged periods, as there is no mechanism to exploit the potential arbitrage, i.e. there is no deep and liquid market to borrow and lend certain commodities. An alternative approach that avoids the use of discounting cash flows is suggested by Greer (2005). He argues that on average a producer tends to have larger operations, greater inventories, and higher fixed costs than a consumer and so needs greater price risk protection. Consider the price risk faced by a producer of crude oil looking to sell in six months’ time. The producer’s current marginal cost is assumed to be USD 45.00, so this would need to be the minimum he would want to receive in order to break even. He knows from experience that oil prices can be volatile and difficult to predict. Nonetheless, he has an expectation that the price of crude oil will be USD 50.00 at that time. The producer approaches a commodities trading house to see if they would be interested in a forward transaction. The trader happens to share the producer’s opinion on the expected future spot price and so agrees to a trade. However, he is unwilling to pay USD 50.00 and offers USD 49.00. This is not unreasonable. If the price does evolve as per the market, the trader will not make any profit. He will buy it from me, the producer, at USD 50.00 and would sell it in the open market at the same price making zero return. The USD 1.00 ‘discount’ that he suggests is his potential return and is sometimes referred to as a ‘risk premium’. It is a satisfactory deal for the producer as they have covered at least their marginal cost of production. This suggests an alternative way of deriving forward prices (Barclays, 2011): Forward price = Spot price + expected future spot price appreciation∕depreciation + risk premium However, it is instructive to consider the convenience yield as a proxy for the level of inventories and the availability of storage. To illustrate this principle, the returns an investor could earn from a commodity index position that references a portfolio of futures is: Total returns = spot return + roll yield + collateral yield

(2.1)

The traditional time value of money relationship between the spot and forward price can be expressed as: Forward price = spot price + interest rate − (convenience yield − storage)

(2.2)

Rearranging 2.2 to solve for convenience yield gives: Convenience yield = (Spot − forward) + storage cost + interest cost

(2.3)

27

Derivative Valuation

Within the context of commodity index investing the difference between a spot and forward price is the roll yield2 . This results in a formula that allows for the estimation of the convenience yield based on observable values: Convenience yield = Roll yield + storage cost + interest cost

(2.4)

Using market prices and industry estimates for storage, Lewis (2005) calculates the average convenience yield for a range of commodities for the period 1989 to 2004. These values range from 35.88% for crude oil to -0.84% for gold. He then compares these values to the average number of days of above ground inventories (for example 20 for crude oil and 16,500 for gold). He argues that convenience yields tend to increase as the level of inventories decline. In some respects, this is logical; a shortage of supply in the short-term will cause short-term prices to increase. He describes convenience yield as an indication of ‘market precariousness’. He goes on to show that there is a positive relationship between convenience yield and volatility, for those markets that suffer from lower levels of inventory and hence display a higher convenience yield have the highest levels of volatility. Equally, products that have high levels of inventory, which is associated with lower convenience yields, have a lower volatility. An interesting alternative is offered by Barclays (2008). They suggest that taking the robot or toddler approach are the two ways to view price determination. In the robot approach: The view of prices as being the deterministic output of a calculating device might just be applicable in a market with close to perfect information, where the flow of data was rapid and reliable and where the underlying relationships between fundamentals and prices were well known and stable. Those conditions could just happen in some markets. However, the oil market does not fit that template, nor is it ever likely to. They suggest however, that the toddler approach is a more representative view: [The market] behaves something like a toddler, constantly in search of defining where the boundaries of behaviour should be, and then constantly pushing towards those boundaries until it finds them and gets a reaction. Unless there is something acting in loco parentis that dictates what those boundaries are in advance, (i.e. normally OPEC), the market will tend to find them for itself.

2.4.3

Interpreting forward curves

Prices for future delivery as represented by the forward curve will experience either contango (forward prices higher than spot prices) as well as backwardation (forward prices lower than spot prices). 2

This is covered in Chapter 14.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Although something of a generalisation, commodity sectors such as crude oil and base metals are more prone to backwardation. This contrasts with precious metals, which mostly experience contango. One explanation of this is the availability of the commodity above ground. In the gold market a large amount of gold is held above ground, and storage costs are relatively small. However, with crude oil it is relatively expensive to store the commodity (about 20% of the cost of a barrel), which discourages holding the commodity. As a result, an increase in demand may not be met from existing stocks, as it will need to be extracted and refined. Given the time lag, spot prices rise relative to forward prices and may push the market into backwardation. Backwardated markets are characterised by: ▪ ▪ ▪ ▪ ▪

A scarcity of the commodity. Low inventories. Volatile prices because of low inventories. A strongly rising price. A “fear” premium. Contango markets are characterised by:

▪ ▪ ▪ ▪ ▪

A glut of the commodity. High levels of inventory. Relative price stability. General price weakness. A “complacency” discount.

2.4.4

Commodity arbitrage

Within commodity markets it is perhaps possible to differentiate between three types of arbitrage: ▪ Geographic ▪ Time ▪ Technical or quality Geographic arbitrage One popular example of cross-market arbitrage exists in the metals market between the London Metal Exchange (LME) and the Shanghai Futures Exchange (SHFE). If the metal is deliverable to satisfy a futures commitment in either of the markets, then it may be possible to lock in a profit by buying in one location and selling into the other. In one sense, this profit opportunity should not happen because if the metal is fungible between the exchanges, any price differential should be small. However, markets are not perfect, and as such, differences exist due to demand and supply dynamics, tax regimes, exchange rates, freight costs, interest rates, and premiums and discounts.

Derivative Valuation

29

The LME (2020) set out the arbitrage formula: [(LME + ∕ − ADJ + CIF) ∗ USD∕RMB ∗ (1 + VAT) ∗ (1 + TARIFF) + ADMIN] − SHFE = Arbitrage level Where: LME = LME metal price (i.e. three-month future) ADJ = contango / backwardation adjustment to align the expiry dates of the LME and SHFE expiration CIF = any physical premium associated with metal as well as all transport costs to China USD / RMB = the exchange rate expressed as the amount of RMB per 1 USD VAT = value added tax TARIFF = any import or export taxation ADMIN = administrative charges SHFE = equivalent expiration month price quoted on Shanghai Futures Exchange So, looking at the arbitrage formula, everything within the square brackets would represent the ‘all in’ cost of exporting the metal to China. Subtracting the price of the equivalent contract in Shanghai would return the arbitrage amount. So, the arbitrage would work if the price of metal for delivery on the SHFE exceeds the all-in cost of delivering it from the LME. It is also possible to reverse the direction of this arbitrage by buying on the SHFE and selling into the LME.

Time arbitrage This type of arbitrage seeks to exploit the shape of the forward curve and would yield a profit if the forward price were trading away from the price implied by a ‘cash and carry’ trade. Suppose that aluminium for ‘cash’ (i.e. immediate) delivery is trading at USD 2,000 per tonne. A trader believes she can store the metal for a week at a cost of, say, USD 3.00 and the cost of financing the position is, say, USD 0.50. Using cash and carry principles this implies a ‘fair value’ forward price of USD 2,003.50. However, she notices that the one-week forward is trading at USD 2,005. She executes the following trade: ▪ She buys the metal for cash delivery at a price of USD 2,000 with the intention of selling it in a week’s time at the prevailing spot price. ▪ She sells a one-week forward at a price of USD 2,005, which will be closed out shortly before expiry.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

At the end of the period consider the profit or loss on the position in the following two scenarios: Cash price has increased to USD 2,010 The physical position is sold back into the market resulting in a gross profit of USD 10.00 (USD 2,010 − USD 2,000). After substituting carry costs of USD 3.50, the profits are USD 6.50. It is assumed that the futures position is closed at the prevailing cash price resulting in a loss of USD 5.00 (USD 2,005 − USD 2,010). The net profit is USD 1.50. Cash price has fallen to USD 1,990 The physical position is sold back into the market resulting in a gross loss of USD 10.00 and so the net loss incorporating the carry increases this to USD 13.50. Since the price of the metal has fallen, the short futures position will show a profit of USD 15.00 (USD 2,005 − USD 1,990) resulting in a net profit of USD 1.50. Note that on both occasions the net profit is USD 1.50, which is equal to the difference between the initial ‘cash and carry’ implied forward price of USD 2,003.50 and the observed forward price of USD 2,005. Although some readers may be tempted to suggest that this example is somewhat theoretical, consider the following: In February 2010, a newspaper report first suggested that between 75–90% of the world’s physical aluminium stocks were tied up in financial arbitrage deals designed to exploit the difference between spot and forward prices. In aluminium, physical stock levels on the London Metal Exchange had quadruped over an 18-month period to about 4.5 m tonnes, largely because of excess supply relative to actual demand. However, estimates suggested the amount of aluminium available for consumption was roughly half that amount. At the time, the aluminium price was steeply in contango so longer-dated forward prices were higher than shorter-dated prices. The steepness of the forward curve allowed the traders to exploit a lucrative arbitrage opportunity. Using 2010 prices, the profitability of the trade could be calculated as follows: ▪ ▪ ▪ ▪

Buy the metal for spot delivery at USD 2,076. Finance the purchase of the metal for 92 days at 0.5% (i.e. 3M LIBOR + 0.25%). Warehousing costs of USD 0.15 per tonne per day. Sell the metal for three-month forward delivery at USD 2,108.

The difference between the spot cost and forward income is USD 32.00 a tonne. The financing cost is USD 2.65 and the warehousing amounts to USD 13.80. This resulted in ‘carry costs’ of USD 16.45 and so generated a net profit of USD 15.55 per tonne or an annualised return of about 3%. It would be logical to suggest that profits on such a lucrative trade should disappear rapidly, but this profitability was consistently reported for about the next five years. Theory suggests that through demand and supply dynamics, more and more spot purchases and forward sales would erode the profitability. For the arbitrage to continue,

Derivative Valuation

31

it would require equal and opposite pressure from other market participants. It would be reasonable to suggest that spot prices would be kept low if producers had excess inventory to sell, and that forward prices would remain high if consumers were still buying on a forward basis. Traders engaging in these arbitrage deals were then being ‘rewarded’ for intermediating between the different transactional maturities of the physical counterparties. It is not only in metal markets that such arbitrage exists. In December 2008, BP decided to exploit the shape of the forward crude oil curve by booking supertankers to store oil at sea. BP booked the Eagle Vienna, a vessel that can store two million barrels of oil, which is about 10% of America’s daily demand. It was filled with Brent and transported for storage in the Gulf of Mexico for later release to the US market. Although the company would neither confirm nor deny it, some market participants believed the oil had been sold on a forward basis. In December 2008, the spot price of crude was quoted as USD 47.00/barrel while the 12-month forward price was USD 60.00/barrel, so it is possible to illustrate the economics of the trade using these values. At the time other market participants such as Royal Dutch Shell and Koch (a petrochemical company) had done the same, leading to suggestions that about 10 million barrels of oil were being stored in a similar fashion. Estimates suggested that each barrel would cost about USD 6.00–7.20 a year to store on board the tankers. To purchase the crude oil, it would cost USD 94 m (2 million barrels * USD 47.00/barrel) while the revenues received from selling the oil forward would be USD 120 m (2 million barrels * USD 60.00/barrel). This would result in a gross profit (before expenses) of USD 26 m. This period coincided with a substantial collapse in freight prices and interest rates, which made the transaction attractive. The cost of using the vessel, as a storage facility would be USD 14.4 m (2 million barrels * USD 7.20), while the cost of financing the purchase of the oil and the hire of the ship would be USD 271,000 (USD 94 m + USD 14.4m * 0.25%)3 . The net profit would therefore be USD 11,329,000 (USD 26 m − USD 14.4 m − USD 271,000). It may be possible that the profits were even higher if BP had extracted the oil from their own facilities at a marginal cost of production lower than the spot price. This is clearly an attractive profit and so should encourage other participants to execute a similar trade. This would force the spot price up and the forward price down, removing the profits. By April 2009, the amount stored offshore had risen to 100–120 m barrels on 56 ships; in a normal year about 5–7 tankers would be used in this manner. However, the number of barrels stored in this manner had fallen to 50–60m by September 2009 as the differential between spot and 12-month forward prices had fallen to USD 5.45 making the trade less attractive. Technical or quality arbitrage Trafigura (2015) gives an example of this. In the USA, gasoline typically contains some amount of ethanol. It may be possible for an entity to source and blend the individual components to earn an attractive margin.

3

An actual / actual day basis is assumed.

32

2.5

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

COMMODITY SWAP VALUATION

To illustrate the mechanics of a commodity swap, consider the following crude oil example. Maturity Frequency of cash flow exchange Notional amount Floating price Fixed price

One year Monthly 10,000 barrels Near-dated WTI futures price on settlement date USD 57.59

Irrespective of the underlying asset class, the price of any swap is the fixed component of the transaction. To calculate the theoretical price of a crude oil swap, the starting point is to appreciate that all swaps should be considered an equitable exchange of cash flows on the day they are traded. That is, the present value of the expected payments must equal the present value of the expected receipts. A reader new to the world of swaps may find this odd as it suggests the transaction does not have any profit. However, note that the fair price of the swap was described in terms of expected cash flows. Profits and losses will arise as actual payments are crystallised – these could be substantially different than those expected at the start of the transaction. Since we are trying to solve for an unknown fixed rate, our analysis of swap prices starts with the floating or variable cash flows. The aim on the floating side is to calculate the present value of the future cash flows, which are linked to a series of yet to be determined prices. To derive an initial value for each of the floating cash flows it is market practice to use the futures curve that prevails on the transaction date. Table 2.1 illustrates all the cash flows associated with the swap. The starting point is the fourth column that lists the applicable futures prices (floating prices) for the underlying commodity. Although these values are based on the current futures curve, an element of interpolation is needed, as the futures settlement date will differ from that of the swap. These floating prices are then applied to the notional amount (i.e. 10,000 barrels) to determine the magnitude of the floating cash flows (fifth column). Although Table 2.1 approaches this in a different way, the next step would be to present value and then sum the floating cash flows. The fixed price could then be solved for iteratively. It is the single value, which when applied to the notional amount will return a set of present-valued cash flows whose sum equals that of the present-valued floating cash flows. The result will be a structure where the initial net present value (NPV) of the cash flows is zero (column seven). By looking at the single fixed rate in relation to the floating prices, the former is a weighted average of the latter. Viewing the fixed rate in this manner gives an insight into the essence of swaps. Ignoring any underlying economic exposure, an entity paying fixed must believe that over the life of the swap they will receive more from the floating cash flows. In other words, the fixed rate payer must believe that actual crude futures prices will rise faster than those currently implied by the market. The opposite would

33

Derivative Valuation

TABLE 2.1 Swap cash flows on trade date. Payment dates

Fixed price

Fixed cash flows

Floating prices

Floating cash flows

Net cash flows

Discounted cash flows

20 Jan 21 Feb 20 Mar 20 Apr 22 May 20 Jun 20 July 21 Aug 20 Sept 20 Oct 20 Nov 20 Dec

57.59 57.59 57.59 57.59 57.59 57.59 57.59 57.59 57.59 57.59 57.59 57.59

575,884.80 575,884.80 575,884.80 575,884.80 575,884.80 575,884.80 575,884.80 575,884.80 575,884.80 575,884.80 575,884.80 575,884.80

56.20 56.80 57.22 57.62 57.87 57.96 57.97 57.96 57.92 57.88 57.86 57.82

−561,966.67 −568,025.00 −572,238.71 −576,228.57 −578,654.55 −579,600.00 −579,735.48 −579,564.52 −579,224.14 −578,837.50 −578,566.67 −578,214.29

13,918.14 7,859.80 3,646.09 −343.77 −2,769.74 −3,715.20 −3,850.68 −3,679.71 −3,339.34 −2,952.70 −2,681.86 −2,329.48

13,909.21 7,843.55 3,633.92 −342.12 −2,752.76 −3,687.57 −3,816.69 −3,641.67 −3,299.93 −2,913.25 −2,641.71 −2,290.97

be true of a fixed rate receiver; that is, they expect actual futures prices to be below those currently implied by the market. In this example, the cash flows are present valued using interest rates derived from the interest rate swap market. The present valuing is done in terms of discount factors, which have a value between 0 and 1. The discount factor can be applied to a future cash flow using the following simple relationship: Present Value = Future Value x Discount Factor In its simplest form a discount factor can be represented by the following formula: Discount factor =

1 (1 + zero coupon interest rate)n

Where n is the number of years from the effective date to the cash flow settlement date Where the period relates to less than 1 year the formula becomes: Discount factor =

1 1 + (zero coupon interest rate x

days ) basis

Where ‘days’ is the number of actual days in the cash flow period and ‘basis’ is either 360 or 365 depending on the money market convention associated with the swap’s currency4 . 4

USD, EUR will take a 360-day convention, GBP will be 365.

34

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

The interest rate used to calculate a discount factor should be a zero coupon in style and should have the same degree of credit risk as the cash flow to which they will be applied. A zero coupon instrument pays no cash flow until maturity with the buyer’s return usually in the form of a capital gain. However, interest-bearing deposits may also be in zero coupon form if they only have two cash flows – the initial and final movement of funds. This means that an investor’s exact return for a given holding period can be calculated. This zero coupon return is different than that offered by an interest-bearing instrument that pays a series of cash flows prior to maturity. Although a yield to maturity can be calculated for an interest-bearing instrument, it would not be a true measure of the overall return as this measure requires the interim interest payments to be reinvested at the yield that prevailed at the start of the transaction. This is referred to as reinvestment risk. One problem with zero coupon yields is the lack of available market observations and as such an analyst is often forced to use mathematics to transform the yield on an interest-bearing instrument into a zero coupon equivalent. A comprehensive treatment of this subject can be found in Galitz (2013).

2.5.1

Single and dual curve discounting

Broadly speaking there are two approaches that could be used to value a swap: LIBOR or Overnight Index Swap (OIS) discounting. To illustrate the difference between the two techniques, consider the following stylised example. Examples of ‘real world’ swap transactions will be illustrated in subsequent chapters. Notional amount: Maturity: Fixed price payer: Floating price payer: Fixed price: Floating price: Frequency of payments:

10,000 barrels Six months Client Bank USD 51.44 Average of front month crude oil futures settlement price Monthly for both fixed and floating

At the time of writing the ICE Brent futures contract would cease trading on the last business day of the second month that precedes the relevant contract month. For example, the March contract expires on the last business day of January. So, based on Table 2.1, the first cash flow on 20 January will reference the average of the maturity that was the front month contract for that period. From the trade date until the 29 December this would have been the February maturity; the period from then until the cash flow settlement date would reference the March contract. For the purposes of the following examples, suppose the following interest rates are observed in the market. For ease of illustration each month is assumed to have 31 days.

35

Derivative Valuation

TABLE 2.2 LIBOR rates and their associated discount factors Months

LIBOR rate

Discount factor

1 2 3 4 5 6

1.00% 1.25% 1.50% 1.75% 2.00% 2.25%

0.999140 0.998925 0.998710 0.998495 0.998281 0.998066

The applicable crude oil futures prices appear in Table 2.3. TABLE 2.3 Crude oil futures prices

2.5.1.1

Month

Price (USD/barrel)

1 2 3 4 5 6

50.00 50.25 50.50 50.75 51.00 51.25

LIBOR discounting

It was argued earlier that on the trade date a swap should be an equitable exchange of cash flows. Expressed more formally this means that the present value (PV) of the cash flows to be paid must equal the present value of the cash flows to be received. If the swap were structured so that the fixed cash flows are received and the floating cash flows paid, this would suggest that: PV of fixed cash flows less PV of floating cash flows = 0 The PV of the fixed cash flows (FXD) can be calculated using a series of discount factors (DFn ): =FXD ∗ DF1 + FXD ∗ DF2 + FXD ∗ DF3 + FXD ∗ DF4 + FXD ∗ DF5 + FXD ∗ DF6 =FXD ∗ (DF1 + DF2 + DF3 + DF4 + DF5 + DF6 )

(2.5)

The PV of the floating cash flows (FLTn ) can be calculated in a similar manner: = FLT1 ∗ DF1 + FLT2 ∗ DF2 + FLT3 ∗ DF4 + FLT5 ∗ DF5 + FLT6 ∗ DF6

(2.6)

36

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

It may be obvious to state that these equations can only be solved if we know the value of the various inputs. Arguably, the easier input to determine is the value of the discount factor, which can be derived from observed LIBOR rates. The next step is to calculate the floating cash flows. However, the cash flows that will be settled will be based on prices that prevail at some future date. The challenge is to determine a series of values that will apply at the inception of the transaction. Rather than forecast what these cash flows are likely to be the swap trader could hedge these cash flows using futures. In our example the floating cash flows are to be paid by the trader and so they could be hedged by buying a series of futures contracts. So, if the price of crude oil rises and the trader is faced with increased payments on the floating leg of the swap, an offsetting long position in a futures position should show a corresponding profit. On this basis the convention is to use prevailing futures prices to assign a value to the floating swap cash flows on the trade date. This highlights a key aspect of derivative valuation – the price of a transaction is driven by the cost of hedging the underlying exposure. Since the swap has to have a zero market value on the trade date the only remaining unknown factor is the fixed price. With a little bit of rearrangement of equations (2.5) and (2.6) it is possible to solve for a fixed rate (FXD) that achieves this objective. The single fixed price that will apply to the swap is calculated as USD 51.44 expressed to two decimal places. To illustrate this concept, the following table shows the value of the crude oil swap as of the trade date. The fixed cash flows are calculated as: Number of barrels x fixed price The example in Table 2.4 was calculated using Excel and so the fixed price on a per barrel basis is expressed to six decimal places: USD 50.624843. The first fixed cash flow in column 2 is calculated as: 10,000 barrels × USD 50.624843 = USD 506,248.43

TABLE 2.4 The valuation of a commodity swap under LIBOR (‘single curve’) discounting. Months 1 2 3 4 5 6

Fixed cash flows

PV of fixed cash flows

Floating cash flows

PV of floating cash flows

506,248.43 506,248.43 506,248.43 506,248.43 506,248.43 506,248.43 PV TOTALS

505,812.87 505,704.10 505,595.37 505,486.69 505,378.06 505,269.47 3,033,246.57

−500,000 −502,500 −505,000 −507,500 −510,000 −512,500

−499,569.81 −501,959.70 −504,348.55 −506,736.38 −509,123.18 −511,508.95 −3,033,246.57

NET PRESENT VALUE

0

37

Derivative Valuation

The present value of the fixed cash flows (column 3) is calculated as: Fixed cash flow x discount factor The first cash flow is calculated as: USD 506,248.43 × 0.999140 = USD 505,812.87 The floating cash flows in column 4 are calculated as: Number of barrels x futures price The first floating cash flow is: 10,000 × USD 50.00 = −USD 500,000 The PV of the floating cash flows (column 5) is calculated as: Floating cash flow x discount factor The first calculation is: USD 50,000 × 0.999140 = −USD 499,569.81 Over time the market factors used to establish the initial value of the swap will evolve. As a result, it is perhaps inevitable that the swap will have value for one of the market participants at the expense of the other. To establish how this value evolves, it is possible to use the principles just outlined to determine the value of the swap. To illustrate this concept, suppose that crude oil prices rise instantaneously by USD 1.00 across all the applicable maturities (all other things being equal). This will increase the magnitude of the floating cash flows to be paid resulting in a new net present value of −USD 59,916.17. The swap also has exposure to the passage of time. Assuming all else being equal then after one month the swap will only have five pairs of cash flows remaining. The PV of the fixed receipts will be USD 2,527,433.69 while the PV of the floating payments will be USD 2,533,675.75 resulting in a net present value of −USD 6,243 to the bank. The structure also has an exposure to the change in interest rates but in this relatively short-dated example the impact is negligible. 2.5.1.2

Overnight index swap discounting

Derivative credit risk exists for contracts that are ‘in the money’ (i.e. profitable). Given that derivatives are bilateral contracts, the credit risk could switch between the contracting entities depending on how the profitability of the contract evolves. Counterparty default does not necessarily lead to a loss. It would only do so if the contract were valuable to the non-defaulting entity. To mitigate the counterparty credit risk associated with a derivative transaction it is common for the contracting parties to agree to exchange collateral. Collateral agreements (e.g. the ISDA credit support annex) typically stipulate that interest will be paid on monies held as collateral. The most common interest rate that is used in this respect is

38

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

one that references an overnight rate. For USD contracts this could be the Fed Funds rate while for EUR contracts it would be the European Overnight Index Average (EONIA). Since these interest rates are very short term, the market perceives them to have a very low degree of credit risk. This has led to the use of overnight index swap (OIS) rates rather than LIBOR for valuation purposes. An OIS swap is an exchange of fixed cash flows for a series of floating cash flows where the latter reference an agreed overnight index. Since an OIS rate is perceived to have a lower credit risk, they should trade below the equivalent LIBOR. To give a sense of why an OIS would work consider a situation where a market participant has a crude oil swap with a residual maturity of one year and a notional of 10,000 barrels. For ease of illustration we will assume that the fixed price was originally set at USD 50.00/bbl. and that the floating cash flows are paid monthly referencing a futures contract. In this example the fixed price is received annually so there is only one of these cash flows remaining. The trader decides to offset this position with a swap that has the same characteristics but is traded at prevailing rates. If the fixed price is now USD 45.00/bbl., then the trader has been able to lock in a profit of USD 5.00/bbl., or a total of USD 50,000. The floating cash flows will cancel out and the profit is the difference between the two fixed prices. If 12-month LIBOR rates are, say, 5% then the mark to market of this transaction is USD 47,619 (USD 50,000/1.05). To protect the value of this position the trader takes collateral on the original ‘receive fixed’ position equal to this amount and agrees to pay the 12-month OIS rate. If this rate is, say, 4% over the course of the year, then the collateral will grow to reach USD 49,523 (USD 47,619 x 1.04). At the maturity of the transaction the trader expects to receive USD 50,000 on a net basis but taking collateral discounted at LIBOR but accruing at an OIS rate will not generate sufficient proceeds if the counterparty were to fail. The correct amount of collateral that the trade should demand is USD 48,077 (USD 50,000/1.04); paying the OIS rate on this amount of collateral will generate USD 50,000 at maturity. This suggests that the correct rate at which cash flows at which a collateralised deal should be discounted is the OIS rate. Referring to the discounting example in Table 2.5 the discount factors are now calculated using OIS rates rather than LIBOR. The applicable formula to calculate the discount factor is the same as LIBOR except that an OIS rate is used.

TABLE 2.5 Overnight Index Swap rates and their associated discount factors. Months

OIS rate

Discount factor

1 2 3 4 5 6

0.50% 0.75% 1.00% 1.25% 1.50% 1.75%

0.999570 0.999355 0.999140 0.998925 0.998710 0.998495

39

Derivative Valuation

The cash flows on the swap on the trade date appear in Table 2.6. TABLE 2.6 The valuation of a commodity swap under LIBOR (‘single curve’) discounting. Months 1 2 3 4 5 6

Fixed cash flows

PV of fixed cash flows

Floating cash flows

PV of floating cash flows

506,248.43 506,248.43 506,248.43 506,248.43 506,248.43 506,248.43 PV TOTALS

506,030.56 505,921.69 505,812.87 505,704.10 505,595.37 505,486.69 3,034,551.28

−500,000 −502,500 −505,000 −507,500 −510,000 −512,500

−499,784.81 −502,175.68 −504,565.51 −506,954.32 −509,342.10 −511,728.85 −3,034,551.28

NET PRESENT VALUE

0

Source: Author’s calculations

Note that on the trade date the net present value of the swap is still zero and that the fair price of the swap is USD 50.62, although the present value of the individual cash flows is different. This will manifest it most clearly when futures prices change. If futures prices were to increase by USD 1.00/bbl. across the entire curve, then under LIBOR discounting the swap will lose USD 59,916.17. Based on the same scenario, the OIS discounting would show a loss of USD 59,941.94. Although it may seem a relatively small amount, over a large portfolio of swaps that perhaps have larger notional amounts and longer maturities, this impact could be pronounced.

2.6

PRINCIPLES OF OPTION VALUATION

Probably one of the most documented areas of finance is that of option pricing. Since the aim of this chapter is to give readers a basic understanding of where the value of a derivative instrument comes from, the analysis will avoid excessive discussions on the mathematics of options and concentrate on the intuition. Those interested in understanding the mathematics are recommended to refer to a variety of texts such as Galitz (2013), Tompkins (1994) and Natenberg (2014). A more recent and commodity specific text has been written by Geman (2005)

2.6.1

Black Scholes and Merton

An option’s premium is primarily a function of: ▪ The expected payout at maturity ▪ The probability of the payout being made Although at an intuitive level these concepts are easy to understand the mathematics behind the principles is often complex and off-putting to many readers. To determine the premium on an option, a variety of inputs are required as well as is an appropriate model. Under a Black Scholes and Merton (BSM) framework, those inputs will include ▪ The spot price, ▪ The strike price,

40

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

▪ Time to maturity, ▪ The cost of carrying the underlying asset as a hedge (i.e. any income earned through holding the underlying asset less any expense incurred), ▪ The implied volatility of the underlying asset. The following input values will be used for the subsequent examples. Underlying commodity

Gold

Spot Strike Time to maturity Six-month LIBOR Six-month lease rate Six-month forward price Implied volatility

USD 1,400 USD 1,400 Six months 3% 0.10% USD 1,420.44 15%

We will assume that the option is European in style and given the input values noted above, a Black Scholes Merton model returns a premium of USD 69.38 per troy ounce (option premiums are quoted in the same format as the underlying asset). Note that at first glance this option appears to have been struck at-the-money, as the spot price and the strike are the same. However, since this option is European the model will value the option relative to an equivalent underlying price. Since the option cannot be exercised for six months, the equivalent underlying is not the spot price but the six-month forward. So, the option is in-the-money; the call buyer has the right to buy at USD 1,400 when the underlying market is USD 1,420.44. An option premium can be decomposed into two elements: time value and intrinsic value. The intrinsic value can be thought of as the amount of profit the buyer would make if they were to exercise the option straightaway. However, the term is defined in such a way that it does not consider the initial premium paid. The intrinsic value for a call option can be expressed in the following manner. Intrinsic value of a call = MAX (0, Underlying price − strike) For put options it is expressed as Intrinsic value of a put = MAX (0, Strike − Underlying price) In both expressions the underlying price is the forward price for European style options and spot for American style. In the original definition of intrinsic value prior to maturity for a European option, the difference between the underlying forward price and the strike would need to be present valued since exercise of the European style option could only take place at expiry and the premium is quoted as a present value. However, when analysing options intuitively, traders would probably disregard this aspect.

Derivative Valuation

41

Time value is the extra amount that the seller charges the buyer to cover them for the probability of future exercise – a sort of uncertainty charge. Time value is not paid or received at expiry of the option as for buyers it will fall to zero over the option’s life. When an option is exercised the holder will only receive the intrinsic value. Time value is only paid or received upon the sale or purchase of an option prior to maturity. This explains why early exercise of an option is rarely optimal. If a purchased option is no longer required it would usually be more efficient to neutralise the exposure by selling an opposite position in the market. In this way they would receive both intrinsic and time value. If the option were exercised, they would simply receive the intrinsic value. An understanding of the two option premium components is vital to understand the logic of interbank transactions. Intrinsic value is principally driven by movements in the underlying price, while time value is primarily a function of time to expiry and implied volatility.5 This means that when trading options the three main factors that need to be considered are: ▪ Movements in the underlying price. ▪ The passage of time. ▪ Movements in implied volatility.

2.6.2

The Black model

One of the ways to approach the valuation of commodity options that reference an underlying future is to use the Black model (1976) for options on futures. This model is used extensively in the interest rate options market for valuing caps, floors, and swaptions. In a Black Scholes Merton model an analyst would typically input the spot price of the asset into the model, which combined with the ‘carry’ parameters (e.g. interest rates and any income the underlying asset would generate) would determine the implied forward price. Based on the implied forward, the model would then calculate the option’s fair value. One of the main attractions of the Black model is its simplicity as the spot and net carry parameters are replaced with the observed forward or futures price. This would mean that the parameters required to price an option on a crude oil future would be: ▪ ▪ ▪ ▪

Price of the future. Strike. Option’s time to maturity. The implied volatility of the future’s price.

2.6.3

Bachelier model

One of the features of the Black Scholes Merton (BSM) and Black models is they assume that the underlying prices are lognormally distributed. From a price perspective, this means the models do not allow for the possibility that prices could turn negative.

5

See Tompkins (1994).

42

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

For conventional financial assets such as shares, bonds, and foreign exchange this is a reasonable assumption; when a company goes bust, their shares will stop trading rather than turn negative. As ever, commodities are different. Negative prices have been experienced in power and gas (see chapters 7 and 8) and calendar spread trades can flip between positive and negative values. The issue of negative prices and index values came more to the fore in 2020 as a result of activity in the shipping market (e.g. Baltic Capesize Index) and in April 2020 for the first time, crude oil (see see chapter 6). This brought into question the use of models such as Black 1976 for valuing and risk managing options on futures. An alternative to this model is the Bachelier model, which dates from around 1900. Some of the key characteristics of the Bachelier model are: ▪ It assumes that the underlying price follows a normal rather than lognormal distribution and so allows for the possibility of negative prices. ▪ Volatility is expressed as a monetary value rather than as a proportional percentage value. For example, assume an asset is trading at a price of USD 10.00 with an implied volatility of 10% per day. This would suggest that the asset is expected to trade with an approximate range of prices between USD 9.00–11.00. If the price drops to USD 5.00, but the implied volatility remains the same, then the approximate range of prices would be +/− 50 cents. Using the same set of prices, a Bachelier model would express volatility as a dollar value, say, USD 1.00. So, at USD 10.00 the range of prices would be similar. But if prices fell to USD 5.00 then under a Bachelier framework, the range of prices remains at +/− USD 1.00. At very low prices (e.g. USD 1.00), but with volatility expressed as a dollar value (e.g. USD 20.00), it means that the model implies a range of values from −USD 19.00 to +USD 21.00. ▪ Since the model allows for negative prices, OTM puts will be valued relatively higher using a Bachelier model rather than a BSM framework. Since the premium reflects the expected payout the Bachelier model reflects, this pushes the price relatively higher than the BSM framework. For example, using a simple Bachelier model a three-month put option with a zero strike, an underlying price of zero, and a dollar volatility of USD 40.00 returns a premium of USD 7.98. A Black 1976 model returns a premium value of USD 0.00. ▪ A BSM framework will value OTM calls relatively higher than Bachelier mainly due to the differences in shape between a lognormal and normal distribution. ▪ The option’s delta will not be the same as under a BSM framework and so the risk management of the option position will be different. The ATM put option valued in the last point had a delta of exactly 0.5, which is less likely than under a BSM framework. ▪ Risk (2020a) also argues that Bachelier tends to price shorter-dated options more effectively than longer-dated options as they can capture a sudden downward move in price. ▪ Risk (2020a) also points to the volatility skew associated with options valued under a Bachelier framework arguing that the flatter the skew the better the model is at capturing the behaviour of the market.

43

Derivative Valuation

2.6.4

Put-call parity: the theory

Although pricing models provide one linkage between the underlying price, the forward rate and the option premium, the concept of put-call parity is an alternative representation. Tompkins (1994) provides a detailed analysis of the concept. Put-call parity is a concept that attempts to link options with their underlying assets such that arbitrage opportunities could be identified. The conditions of put-call parity will hold if the strike, maturity, and amount are the same. Although put-call parity varies according to the underlying asset, in its simplest form it can be represented by the following expression: C−P=F−E Where C = Price of a call option P = Price of a put option F = Forward price of the underlying asset E = Strike rate for the option Strictly speaking the right hand side of the expression would need to be present valued as the strike and the forward price relate to a future time period, whereas the call and put premiums are expressed in present value terms. Although put-call parity was designed to identify price discrepancies between markets, it is possible to adapt the formula so it can be used from a strategy perspective. In this case the expression can be written as: C−P=F Where F is redefined as a position in the underlying, in this case a forward position. Each of the symbols in the expression can be annotated with either a ‘+’ or a ‘−’ to indicate either a buying or selling position, respectively. So: +C − P = +F That is, buying a call and selling a put is equivalent to a long position in the underlying. Although this may seem a very dry concept, the relationship is frequently used in financial engineering to create innovative structures.

2.6.5

Put-call parity: the application

One way in which put-call parity could be applied is in the construction of hedges. Let us take an example of a client looking to buy a commodity forward (e.g. an automotive hedger). If the hedger was looking to buy the commodity at a strike rate equal to the current forward rate, then the price of a call and a put will be the same. Not unreasonably, he may wish to achieve a strike rate E that is less than the current forward rate F, which

44

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

would suggest that for the relationship to hold the price of the call will increase relative to the put. The challenge therefore becomes to obtain a more favourable hedging rate by cheapening the value of the call option. This can be achieved using three possible strategies: ▪ Buy a call on a notional amount of N and sell a put with a notional amount of 2N (sometimes referred to as a ratio forward). ▪ Buy a reverse knock out call option with the barrier set at a level that is unlikely to trade. ▪ Buy a short-dated call option and finance this by selling a longer-dated put option at the same strike.

2.7

MEASURES OF OPTION RISK MANAGEMENT

An option’s ‘Greeks’ are measures of market risk that have been developed over time to help market participants manage the risk associated with the instruments. Each of the option model inputs has a related Greek whose value can be calculated numerically (see Tompkins, 1994 or Haug, 2007) or derived by perturbing the appropriate option model. Most of the Greeks look at how a change in the relevant market input effects the value of the option premium, that is, they are first order effects; measures such as gamma are second order in nature.

2.7.1

Delta

The delta of an option looks at how a change in the underlying price will affect the option’s premium. In one sense, delta can be thought of as the trader’s directional exposure. There are a variety of different definitions of delta: ▪ ▪ ▪ ▪

The rate of change of the premium with respect to the underlying. The slope of the price line. The probability of exercise. The hedge ratio.

The most traditional way of defining delta is the rate of change of the premium with respect to the underlying. Using this method, with a known delta value, the analyst can see how a small change in the underlying price will cause the premium to change. In formula terms it is expressed as: Delta =

Δ Premium Δ Underlying price

So, if an option has a delta value of 0.575, we can say that the premium should change by 57.5% of the change in the underlying. Using the gold option analysed in Section 2.6.1, if the underlying price rises by USD 0.50 from USD 1,400 to USD 1,400.50, the premium should rise by USD 0.2875 cents from USD 69.38 to USD 69.6675. Using

45

Derivative Valuation

TABLE 2.7 Premium against underlying price for a call option. Associated delta values shown in column 3. Underlying price (USD) 1,325 1,350 1,375 1,400 1,425 1,450 1,475 1,500 1,525

Premium (USD)

Delta value

33.89 44.00 55.84 69.38 84.56 101.29 119.43 138.83 159.33

0.37 0.44 0.51 0.58 0.64 0.70 0.75 0.80 0.84

an option spreadsheet, the premium moves to USD 69.6638. One of the reasons why the prediction is not accurate is that delta only applies to small changes in the underlying price. Delta will be either positive or negative depending on whether the option has been bought or sold or is a call or a put. For a purchased call or sold put the associated delta value will be positive. This is because in both instances the value of the option will rise if the underlying price increases – a positive relationship. For a purchased put and a sold call the delta value for these options will be negative. This is because a rise in the underlying price will cause the options to fall in value – a negative relationship. Both statements can be verified by looking at the payoff diagrams shown in Figure 1.2. The second way of illustrating the concept of delta is to see how the value of the premium changes as the underlying spot price changes (all other things being equal). Table 2.7 shows the premium and delta values for a range of underlying prices for our example call option. The resultant graph (Figure 2.3) from plotting the values in the first two columns is shown below. 180 160 140 120 100 80 60 40 20 0 1,325

1,350

1,375

1,400

1,425

1,450

1,475

FIGURE 2.3 Premium (Y axis; USD/oz.) against price (prior to maturity).

1,500

1,525

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

The second definition of delta is the slope of the price line prior to maturity (e.g. premium against price as per Figure 2.3). Delta is the slope of a tangent drawn at any point on the curve. This also suggests that delta should only be used to measure small changes in the underlying price. As the premium-price relationship is convex in nature using delta to determine the impact of significant price movements would give an incorrect estimate. Although not strictly true, delta is often interpreted as the probability of exercise. The application of the term in this definition is not uniformly accepted but it certainly provides a useful rule of thumb. Delta can be measured in a variety of ways: ▪ As a number whose value will range from zero to one ▪ As a percentage ▪ As a delta equivalent figure The most common way of expressing delta is a value ranging between zero and one, with a positive or negative sign associated. Out-of-the-money options will have a delta that ends towards zero while in-the-money option deltas tend towards one. It would be incorrect to say that all at-the-money options have a delta of 0.50 but the value will certainly be close. A plot of the delta values shown in Table 2.7 against the spot price of gold is shown in Figure 2.4. An alternative method is to express it as a percentage number, which was also illustrated earlier. The third way is to express it as a delta equivalent value. This technique compares the market risk position of the option with that of an equivalent underlying asset. So if we were to buy a call option on a notional amount of 50,000 ounces with a delta value of 0.58, the option has the same degree of market risk (for small changes in the underlying asset) as 29,000 ounces (50,000 × 0.58) The concept of delta can be extended to option positions. If we were to add another bought call option to the above position with a notional of 60,000 ounces and a delta of 0.40, this individual position would have a delta equivalent value of 24,000. On a 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

1,325

1,350

1,375

1,400

1,425

FIGURE 2.4 Delta (Y axis) versus spot price of gold.

1,450

1,475

1,500

1,525

47

Derivative Valuation

net basis the entire option position has a delta equivalent exposure of 53,000 ounces (24,000 + 29,000). The option trader’s position would have the same exposure to small movements in the underlying price as long physical holding of 53,000 ounces. If the option trader chooses to neutralise this exposure, he could take an offsetting position in other options or the underlying instrument. He may wish to do this if he is seeking to benefit from a change in another market factor such as implied volatility. In the previous example the trader is delta positive so his option position will rise in value if the underlying market price rises and vice versa. To neutralise the exposure he could therefore sell 53,000 ounces of gold in the underlying market or trade options in different combinations to achieve a net delta exposure with which he is comfortable. If the net delta position is reduced to zero, this is described as delta neutrality. This technique is referred to as delta hedging and demonstrates the use of delta as hedge ratio. If the delta neutralising trades are executed in the underlying market the trader is faced with making a choice between trading in either the spot or forward market. If the option position is European, then the forward market should be chosen. This is because the European option can only be exercised upon maturity and so the appropriate equivalent market is the forward market. However, some traders may choose to hedge in the spot market, and then hedge the resultant interest rate risk (recall that interest rates are one of the factors that determine the difference between the spot and forward price). We have seen that delta changes as a function of the underlying price, but will also evolve over time. For example, as the option approaches maturity the price line shown in Figure 2.3 above will become more linear in nature and at maturity will resemble the ‘hockey stick’ shape that was illustrated in Figure 1.2. As a result, all other things being equal, the delta of the option will tend towards zero or one. This evolution of delta with respect to time is referred to as ‘delta bleed’ and represents another risk to a trader. This is illustrated in Figure 2.5.

1 0.9

Delta tends to one

0.8 0.7 0.6 0.5 0.4 Delta tends to zero

0.3 0.2 0.1 0

1,325

1,350

1,375

1,400

FIGURE 2.5 ‘Delta bleed’ of a call option.

1,425

1,450

1,475

1,500

1,525

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

2.7.2

Gamma

Gamma is defined as the rate of change of delta with respect to the price and is therefore a second order function. Δ Delta Gamma = Δ Premium However, this definition is not helpful in trying to understand the practical aspects of gamma. Over the course of his career the author has collected a few alternative definitions: ▪ ▪ ▪ ▪

The speed with which a delta hedged position becomes unhedged. The exposure to actual volatility in the market. The rate of change of a trader’s profit or loss. The exposure to significant changes in the underlying price.

Gamma is positive for option buyers (irrespective of whether the option is a call or a put) and negative for sellers. Using the gold call option analysed in section 2.6.1, for an underlying price of USD 1,400, the option pricing model returned a value for delta of 0.58 and 0.0026 for gamma. If we take an exposure of 50,000 ounces the delta exposure is equivalent to owning 29,000 ounces of the underlying of the asset. We will assume the trader hedges this exposure by selling an equivalent amount in the underlying market. However, although the position is initially delta neutral, a movement in the underlying will lead to a change in delta and the position will no longer be 100% hedged. The gamma measure can be used to predict the magnitude of any move in delta for a small move in the underlying price. So in this instance we can say that for a small increase in the underlying market price, the delta will move to 0.5826 (e.g. 0.58 + 0.0026) and for a small move down it would move to 0.5774 (e.g. 0.58 − 0.0026).

2.7.3

Theta

Theta reflects the impact of the passage of time on the value of the option and is defined as: Δ Premium Theta = Δ Time Theta is positive for sellers and negative for buyers. This reflects the fact that for buyers, options will experience time decay. In other words, the buyer will pay a premium and will acquire a contract that has time value and possibly intrinsic value. However, over time, the time value element will fall to zero. Using the original call option example, where the spot and strike are USD 1,400 and holding all the other parameters constant, the effect of the passage of time on the option is reflected in Table 2.8. Table 2.8 shows that for the buyer of an option its value will decrease as time passes and that the rate of decay will accelerate as the option approaches maturity. The opposite will hold true for sellers of options. Theta can be thought of as the slope of the price line with respect to the passage of time (column 2 in Table 2.8). Theta will be small initially and will increase with the passage of time (column 3 of Table 2.8). Note that in Table 2.8 the change in the value of the option with respect to time is measured in units of 0.1 of

49

Derivative Valuation

TABLE 2.8 The effect of the passage of time on the value of an option. Time to expiry (years)

Premium (USD per troy ounce)

Change in premium

103.94 97.65 91.10 84.26 77.05 69.38 61.10 51.98 41.53 28.53 8.58

− 6.29 6.55 6.84 7.21 7.67 8.28 9.13 10.45 13.00 19.95

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.01

a year (about 37 days). It is more common to express theta in terms of the impact of a single day.

2.7.4

Vega

Vega is defined as the change in the option premium for a 1% change in an options implied volatility. It is expressed as: Vega =

Δ Premium Δ Implied volatility

Although most people are happy with the concept of volatility in general terms, some magnitude of change in market prices with no direction suggested, the notion of implied volatility sometimes remains difficult to grasp. Consider first the related concept of historical volatility, which as the term suggests, measures the magnitude of movement of the underlying asset over a historical period, measured in per cent per annum. The statisticians would describe this as a standard deviation. However, as is often cited in financial markets ‘that past performance is not a guide to future performance’, and there is a need for a more forward-looking measure of volatility. One of the most popular ways of trying to explain the concept is to describe as the volatility implied in an observed option price. The rationale for this is that if one looks at all the option pricing model inputs the only real unknown is the implied volatility. Terms such as the spot rate or strike are either easily observable or negotiated as part of the option contract. Since it is the only unknown factor, the traditional definition suggested taking an observed option premium, inserting the value into the option pricing model, ‘running the model in reverse’ and backing out the volatility implied by this price. However, this argument traditionally ceases at this point and does not address the obvious circular argument; where did the market maker quoting the observed option price obtain his volatility input? It also gives no real feel for what the measure is trying to achieve. Tompkins (1994, p. 139) describes it as ‘the risk perceived by the market

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

today for the period up until the expiration of a particular option series’. However, since no one can foretell the future with complete certainty, implied volatility is nothing more than a best guess as to the future expected volatility of the underlying asset. As an anecdote, the author recalls teaching a class attended by an experienced option trader who described the interbank options as the ‘market for guesses’. In the interbank market option prices are quoted in terms of a bid-offer implied volatility number. Since implied volatility is the only truly unknown variable this is the factor that it traded on an interbank basis. Trading strategies that aim to exploit movements in implied volatility are covered in chapter 3. The main confusion regarding implied volatility often surrounds the relationship with movements in the underlying asset price. The delta value of an option is sensitive to the magnitude of the implied volatility input and as the size of the volatility number increases the delta on the option will tend towards 0.50. This is because the range of expected values that the underlying is expected to take at maturity is wider and so intuitively, the ‘odds’ of the option being exercised tend towards 50/50. However, it does not follow that as the underlying price starts to move that implied volatility must also move as well. In an option model implied volatility and the spot price are two independent variables and as such, a movement in one factor can be independent of the other. Although it may be reasonable to assert that current observed movements in the spot price may alter a trader’s expectations on the distribution of spot values at maturity, the point is that there is no inbuilt dependency. There is no ‘ruling’ that says if spot were to change by X% that implied volatility must change by Y%. The confusion over the relationship between spot and volatility is like that seen between vega and gamma. Gamma was earlier introduced as a trader’s exposure to actual volatility. If we saw a large value for gamma then the difference between two delta values will be substantial for a given change in the underlying market. If the difference between two delta values is significant this means that the movement of the spot prices was quite large, hence one could reasonably describe such a market as being currently volatile. Table 2.9 shows the effect of implied volatility on the premium for three variants of the call option introduced in Section 2.6.1. ▪ An out-of-the-money option with a strike rate of USD 1,450. ▪ An at-the-money forward option with the strike rate is equal to the forward rate of USD 1,420. ▪ An in-the-money option with a strike rate of USD 1,400. As before all the other pricing parameters are held constant. From Table 2.9 we can draw several conclusions: ▪ The relationship between an ATM option premium and implied volatility is proportional. Doubling the implied volatility will double the premium. ▪ If the option has no implied volatility an OTM and ATM option will have no premium, although the ITM option will have its intrinsic value. This also suggests that volatility is arguably the defining factor that distinguishes an option from its underlying asset.

51

Derivative Valuation

TABLE 2.9 The impact of implied volatility on a variety of options with different degrees of ‘moneyness’. Implied Volatility 0% 5% 10% 15% 20% 25% 30%

OTM option premium

Change in OTM premium

ATM option premium

Change in ATM premium

ITM option premium

Change in ITM premium

0.00 8.67 27.00 46.36 65.99 85.70 105.43

8.67 18.33 19.36 19.63 19.71 19.73

0.00 19.73 39.46 59.18 78.88 98.55 118.20

19.73 19.73 19.72 19.70 19.67 19.65

20.00 31.29 50.07 69.38 88.80 108.25 127.69

11.29 18.78 19.31 19.42 19.45 19.44

▪ The relationship between an OTM option premium and the implied volatility is also non-linear. Notice how a doubling of the implied volatility at low levels causes the premium to rise by a much greater magnitude. Option buyers are said to be long vega (i.e. they will benefit if implied volatility rises), while sellers are short vega (i.e. they will suffer if implied volatility rises, but will benefit if it falls). The logic behind this lies in the pricing formula for options. Recall that the premium of an option is composed of the intrinsic and time value. The intrinsic value of the option is driven by the difference between the price of the underlying and the strike price. The main drivers of the time value are time and implied volatility. The buyer of an option acquires both elements and all other things being equal, an increase in implied volatility will increase the value of the option; a positive relationship.

2.7.5

Non-constant volatility

One of the assumptions of option valuation theory is the notion of constant volatility. This means that irrespective of the strike or tenor of the option the volatility input should be of the same value. For example: ▪ A one-month option should be valued using the same volatility as, say, a 12-month option. ▪ An OTM option will be valued using the same volatility as an ATM option. Empirically, these conditions are not observed in practice. The two main exceptions relate to the existence of skews and term structures. 2.7.5.1

The volatility skew

A volatility skew describes how different volatilities are used to value options of a given maturity but with different strikes. A representative volatility skew for options on WTI is shown in Figure 2.6.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS 38

Implied volatility (%)

36 34 32 30 28 26 24 22 P 25 UT D P 30 UT D P 35 UT D P 40 UT D PU T 45 D PU T AT 45 M D C AL 40 L D C A 35 LL D C 30 ALL D C AL 25 L D C 20 ALL D C 15 AL L D C A LL 10 D C AL L

PU T

20 D

15 D

10 D

PU T

20

Relative strike

FIGURE 2.6 Volatilities with respect to strike price for 3-month options on WTI crude oil. Source: Author, CME group

The ATM volatility is about 29% while low strike options (e.g. OTM puts with low delta values, e.g. 10D put) are higher, and high strike options (e.g. OTM calls with low delta values, e.g. 10D calls) are lower. This would be a case of the market being ‘skewed to the downside’. One way of interpreting the shape of this curve is by the simple interaction of demand and supply. Recall the main inputs for an option valuation model include the underlying price, strike, time to maturity, and implied volatility. All these components apart from implied volatility are either known with reasonable certainty or agreed with the counterparty. As a result, traders will express views on the component that is relatively uncertain – the implied volatility (IV). Suppose that the market expects oil prices to fall; traders could profit from this view by buying OTM put options. The option is traded with a low strike and so its premium will be relatively low. However, if there is an increase in demand its value expressed in volatility terms will increase given the higher demand. Since this option will incur a premium it may well be that the trader will finance this purchase by selling options in areas where he does not expect the underlying to trade; in this case OTM calls with relatively higher strikes. To illustrate the concept, consider the following market values. ▪ Three-month futures price = USD 55.73. ▪ ATM option valued with an IV of 29%. Premium =USD 3.1913. ▪ 10D call, strike rate of USD 66.59, valued with an IV of 26.47%. Premium = USD 0.3307. ▪ 10D put, strike rate of USD 45.06, valued with an IV of 35.80%. Premium = USD 0.5117. For a given maturity the ATM option costs more in premium terms than either of the two OTM options. This skew relationship is not static and will evolve over time. It will also vary between different commodity classes.

53

Derivative Valuation

Implied volatility (%)

19 18 17 16 15 14

P 25 UT D P 30 UT D P 35 UT D P 40 UT D PU T 45 D PU T AT 45 M D C AL 40 L D C 35 ALL D C 30 ALL D C AL 25 L D C A 20 LL D C 15 AL L D C A LL 10 D C AL L

PU T

20 D

10 D

15 D

PU T

13

Relative strike

FIGURE 2.7 Volatilities with respect to strike price for 3-month options on gold. Source: Author, CME group

20 D

15 D

10 D

P 25 UT D P 30 UT D P 35 UT D P 40 UT D P 45 UT D PU T AT 45 M D C AL 40 L D C 35 AL L D C A 30 LL D C 25 ALL D C 20 ALL D C 15 AL L D C A 10 LL D C AL L

48 47 46 45 44 43 42 41 40 39 38 37

PU T PU T

Implied volatility (%)

Figure 2.7 illustrates a typical skew shape for gold. Many practitioners argue that gold trades more like a financial asset and often incorporate gold desks within their foreign exchange trading activities. Here the relationship is more symmetrical and resembles a smile. One explanation of this shape is that since it is traded as a quasi-currency, the market is split between a crash of the USD and a crash of gold (currency code XAU). During the financial crisis of 2008, the implied volatilities for high strike call options soared as gold moved towards USD 2,000/oz. Figure 2.8 illustrates the relationship for US natural gas. In this case there is a tendency for the market to be ‘skewed to the upside’ (i.e. OTM calls tend to trade with relatively higher IVs than OTM puts). This may indicate that the market expects the price of natural gas to rise over the coming months. A similar

Relative strike

FIGURE 2.8 Volatilities with respect to strike price for three-month options on US natural gas. Source: Author, CME group

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS 30.00%

Implied volatility

25.00% 20.00% 15.00% 10.00% 5.00%

% 70 % 75 % 80 % 85 % 90 % 95 % 10 0% 10 5 11 % 0 11 % 5 12 % 0% 12 5 13 % 0 13 % 5% 14 0 14 % 5 15 % 0% 15 5 16 % 0 17 % 0 18 % 0% 19 0 20 % 0 22 % 5 25 % 0% 30 0 35 % 0%

%

65

%

60

55

50

%

0.00%

Relative strike

FIGURE 2.9 Volatilities with respect to strike price for 3-month options on copper. Source: Author, LME

pattern is also observed for options on electricity. Note while gold resembled a smile, this relationship is not quite symmetrical and is sometimes referred to as a ‘smirk’. Figure 2.9 illustrates the relationship for options on base metals such as copper. Traditionally, skews in this market have been less pronounced than in other commodity markets. 2.7.5.2

Volatility term structure

Recall that within the BSM option valuation framework, volatility was assumed to be a constant. In Section 2.7.5.1 it was shown that empirically volatility varied with respect to option strikes. It can also be seen that volatility varies with respect to time to maturity. In most financial markets the so-called term structure of volatility is upward sloping (see for example Schofield, 2017). This suggests that longer-dated options will be valued using higher volatilities. One reasonable way of interpreting this shape is to suggest that uncertainty over the ‘at maturity’ outcomes of the underlying asset rise with respect to time to maturity. However, in many commodity markets volatility displays an inverse term structure, i.e. volatility decreases with respect to maturity. Consider the following option on a fictitious asset (Table 2.10). The underlying asset price is 100 and in all instances the option is struck ATM. Two points arise from this analysis: ▪ For a given maturity there is a positive relationship between an option premium and the level of implied volatility. ▪ In all three conditions, longer-dated options will have a higher value than shorter-dated options.

55

Derivative Valuation

TABLE 2.10 Option premiums in various term structure conditions. Constant volatility

Positive term structure

Negative term structure

Maturity and vol Premium Maturity and vol Premium Maturity and vol Premium 1m / 15% 3m / 15% 6m / 15% 12m / 15%

1.73 2.98 4.21 5.92

1m / 15% 3m / 16% 6m / 17% 12m / 18%

1.73 3.18 4.77 7.10

1m / 15% 3m / 14% 6m / 13% 12m / 12%

1.73 2.79 3.93 5.53

Source: Author’s calculations

8M 9M 10 M 11 M 12 M 13 M 14 M 15 M 16 M 17 M 18 M 19 M 20 M 21 M 22 M 23 M 24 M

5M 6M 7M

4M

2M 3M

30.00 29.00 28.00 27.00 26.00 25.00 24.00 23.00 22.00 21.00 20.00

1M

Implied volatility (%)

The following figures illustrate the relationship for different commodities: Recall the forward curves for crude oil in Figure 2.2. That figure illustrated that the short end of the forward curve tends to be the most volatile. Logically this would also impact the volatility term structure of options (figure 2.10) and since it is inverted it suggests a wider dispersion of ‘at maturity’ values for shorter-dated options than longer-dated options. Since it is plausible to suggest that commodity prices mean revert then at a simple level, there is less expected variability for longer-dated options. This is also shown in the forward curve diagram where there is an element of ‘convergence’ for longer-dated prices. A similar argument could be used to explain the shape of the volatility term structure for natural gas (Figure 2.11). Again, gold is something of an exception. If one were to accept that it is traded more like a financial asset, then the upward sloping volatility term structure is not unexpected (Figure 2.12). The figure for copper indicates that like their observed skew profiles, term structures are not as well defined (Figure 2.13).

Option maturity

FIGURE 2.10 Term structure for crude oil. Source: Author, CME group

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS 50.00

Implied volatility (%)

45.00 40.00 35.00 30.00 25.00

8M 9M 10 M 11 M 12 M 13 M 14 M 15 M 16 M 17 M 18 M 19 M 20 M 21 M 22 M 23 M 24 M

6M 7M

5M

4M

2M 3M

1M

20.00

Option maturity

9M 10 M 11 M 12 M 13 M 14 M 15 M 16 M 17 M 18 M 19 M 20 M 21 M 22 M 23 M 24 M

8M

6M 7M

5M

4M

2M 3M

18.00 17.50 17.00 16.50 16.00 15.50 15.00 14.50 14.00 13.50 13.00

1M

Implied volatility (%)

FIGURE 2.11 Term structure for natural gas. Source: Author, CME group

Option maturity

FIGURE 2.12 Term structure for gold. Source: Author, CME group 21.00%

20.50%

20.00%

19.50%

19.00% 1m

3m

6m

FIGURE 2.13 Term structure for copper. Source: Author, CME group

1y

2y

3y

5y

10y

Derivative Valuation

57

What is the relevance of smiles and skews? First and foremost, options on commodities should always be valued considering the degree of skew or the term structure of volatility. But there are more subtle applications. In Chapter 14 a variety of commodity-structured products will be considered. Typically, these will incorporate some form of long-dated option. If the option references an asset with a downward sloping term structures, it will make these structures relatively more attractive for the investor.

CHAPTER

3

Risk Management Principles

3.1

DEFINING RISK

The use of the phrase ‘risk management’ needs to be clarified. For our purposes, risk within a financial context can be broken down into five major subcategories: ▪ Market risk – the risk that something that is owned or owed will change in value as market prices change. ▪ Credit risk – the risk that monies owed will never be repaid. ▪ Business risk – the risk that an entity engages in a business, which they do not fully understand. ▪ Operational risk – the risk that an entity loses money because of an operational control weakness. ▪ Legal and documentary risk – the risk that a contract is deemed to be null and void (e.g. ultra vires), or that a loss is incurred because of a contractual commitment. Although most institutions would be concerned about market and credit risk, in reality most catastrophic losses have probably been caused by a lack of understanding of the business in which the entity has been involved (business risk) or very poor internal controls (operational risk). In some ways there is an irony in that the risks that are most commonly at the root of most institutions’ losses cannot be easily hedged. For example, poor internal control issues are usually a result of cultural issues and a lack of discipline. For market risks a host of products exist that allow an institution to protect themselves against an adverse move in prices. Next time there is an announcement of losses incurred by an institution that are initially blamed on price movements, consider how it was that the perpetrator was allowed to engage in their activities for so long without any independent control highlighting the problem.

3.1.1

Subcategories of risk

Market risk Within each of the individual risk headings it is possible to break down the risk into a series of subheadings. For example, within market risk one could consider:

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Risk Management Principles

59

▪ Interest rate risk – the risk that entity loses money from an adverse movement in interest rates. For example, a company may borrow money on a variable rate basis and then be faced with higher costs if interest rates subsequently rise. Equally this exposure also applies to interest earned on cash surpluses, which is often ignored. ▪ Inflation risk – although not always obvious, this may be an exposure for a corporate whose revenues or expenses are linked to inflation. A corporate may be faced with a hidden inflation cost if they were to offer a pension scheme to their employees which is linked to a change in inflation ▪ Foreign exchange rate risk – typically foreign exchange rate risk arises from two sources. Transactional FX risk arises because of a company’s day-to-day business. For example, a US importer of goods and services from abroad will have a foreign currency payable. Translational FX risk arises from expressing a foreign currency asset or liability in the company’s domestic accounting currency. With respect to commodities, since they are mostly traded and quoted in US dollars, foreign producers or consumers will also be exposed to FX risk. ▪ Equity risk – this can arise in several different forms from a corporate perspective. Again, one source of equity risk could be hidden in a company’s defined benefit pension scheme. Proposed share buybacks and employee share option schemes may require the company to buy equity at an unfavourable price. Investments in other publicly quoted companies gives rise to a form of equity investment risk ▪ Liquidity risk – liquidity risk can be thought of as the potential inability of a company to meet its short-term cash requirements. This may arise from the inability to borrow money from its bankers, or the inability to be able to liquidate assets to cover any shortfall. ▪ Commodity risk – simply, this is the exposure that a company will face because of a change in commodity prices. This may be either explicit or as a side product of a company’s business. For example, a gold producer will be exposed to a fall in the price of the commodity, which is a direct function of his production. A haulage company’s exposure to diesel prices is arguably a secondary exposure to their main line of business. A company that is fully integrated along a particular supply chain will arguably face offsetting price risks. Credit risk The other main risk from the ‘big five’ noted previously that can be hedged is credit risk; although the use of credit derivatives is outside the scope of this book. To illustrate the principles let us consider the issues faced by a consumer of base metals within the automotive sector. It would be possible for them to enter direct physical hedging contracts with the producers of the metal, but this is not without difficulty. There would be three main risks that the producers would face. Firstly, there is the issue of product specification. Hedging directly with say a mine is not necessarily a good idea, as they will not be producing the metal in its primary form. It is more likely to be in an intermediate form that needs further work to make it usable by the consumer. Although a physical hedge may be possible with a smelting company, there is still no guarantee that they will be able to produce the metal in the exact specification required. The second issue relates to the counterparty credit risk. If either the mine or

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the smelter suffers any operational problems, they may not be able to meet their future physical obligations. Finally, there is the issue of price expectations. Consumers of the metal will be looking to hedge at times when the commodity price is at the bottom of the price cycle, while producers will be looking to hedge towards the peak of prices. One of ways that the metal consumers have sought to get around this is through fixed price component supply. However, this raises the issue of credit risk once again. If the metal consumer enters into an agreement with a component manufacturer, the latter will have to decide whether to hedge them to avoid a price mismatch. If the component suppliers choose to hedge directly and are of a poor credit standing, the terms of their hedge may not be favourable and this may result in poor terms being passed on to the automotive producer. Alternatively, if the component supplier chooses not to hedge their raw material costs, they will be impacted if the price of the underlying metal subsequently rises. Legal risk A force majeure provision in a contract means that a party may be relieved from performing some or all their obligations. It is also referred to as an ‘Act of God’ clause. Typically, they will apply when a specified event occurs (usually taken to be events that are beyond the control of the affected party), which prevent them from performing under the terms of the contract. During the COVID-19 pandemic of 2020 instances of this were seen in the commodities market. For example, both Chinese copper and LNG buyers faced a drop in demand due to reduced economic activity. However, the Financial Times (2020B) points out ‘LNG sellers complain that China’s use of force majeure is at least partly motivated by importers’ desire to buy at cheaper spot prices instead of cargoes imported under long-term contracts.’

3.2

COMMODITY MARKET PARTICIPANTS – THE TIME DIMENSION

When analysing commodities, it is useful to try and develop an understanding of the likely activity of market participants with respect to time. This is done by analysing the forward curve, which indicates the clearing price where demand equals supply for different delivery points in time. In each of the subsequent chapters the price drivers for each specific commodity are considered, but here we will try and provide a generalised approach to the issue of participant’s activity.

3.2.1

Short-dated maturities

Typical participants and their related activities in these markets are: ▪ Companies (e.g. banks and commodity trading companies) managing short-term trading risk. ▪ Investors tracking commodity indices. ▪ Hedge funds and commodity trading advisors using futures to express short-term views on the market.

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Medium-dated maturities

These maturities are dominated by the strategic risk management activities of producers and consumers. Examples of this include oil refinery margin hedging and consumer hedging such as airlines looking to hedge their jet fuel exposures.

3.2.3

Longer-dated exposures

These maturities will see producers who are selling their production forward, perhaps as part of the terms of a loan facility where the lending institution is seeking to minimise the volatility of the borrower’s cash flow. If the curve is steeply backwardated consumers may be tempted to take the opportunity to buy forward at what could be an attractive level. The other main participants in these maturities are investors buying OTC structured notes issued by investment banks. As a generalisation these notes may be constructed as a zero-coupon bond plus a call option.

3.3

HEDGING CORPORATE RISK EXPOSURES

When deciding whether to hedge, a corporate is faced with several possible strategies. These will be considered from the perspective of an automotive metal consumer to give the examples a context. Do not hedge – Here the decision not to hedge may be driven by the fact that the metal may only make up a small proportion of the finished product and so price fluctuations will only have a limited impact on margins. It may also be that the producer can pass on any increase in the price of the underlying metal to the consumers without impacting their own margins. If the underlying price were to fall, the producer can of course cut the final price, but the price reduction may be as large as the underlying price falls. Hedge to guarantee future unit costs – In this instance the manufacturer tries to lock in much of the future cost of a production run by hedging a significant proportion of the commodity price exposures. This allows the price of the final product to be fixed and ensures that there is an adequate margin. It also benefits the end customer, as they are immune to excessive price volatility. Timing mismatch between raw material cost and final product income – This situation arises if the manufacturing process is relatively long, and the price of the final product is linked in part to a commodity price. Having paid for the raw material, the manufacturer will be exposed to a fall in the price of the commodity prior to its sale. If the company were able to receive the raw material on a constant basis and match this with sales of their final production, the timing mismatch may not be a significant issue. However, in reality companies may receive irregular shipments of the raw material and may also choose to carry large levels of stocks. Thus, the timing mismatch issue becomes more acute.

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Active hedging based on directional views of the market – Many nonfinancial companies are uneasy about developing views on potential commodity price movements. The result would be that the hedges would only be implemented based on planned production levels. However, a number of firms have been willing to take advantage of favourable market conditions to implement hedges in anticipation of future needs as the companies realise that they will always have a certain need for a particular commodity. The other difficult decision is determining the size of the hedge. Hedges may be put in place of a forecasted purchase of the raw material. If the actual raw materials are not purchased, then the manufacturer may be faced with a hedge for which there is no underlying exposure. For this reason, several companies choose to hedge a proportion of their exposure. Many of the hedges put in place by companies are financially settled. This allows the hedger to source the metal from a particular supplier who can provide a specific grade or shape.

3.4

A FRAMEWORK FOR ANALYSING CORPORATE RISK

Very often risk management solutions to a potential market risk are considered at a micro level, without considering the big picture implications for the corporate. This approach ignores the fact that a corporate will be ultimately focused on some high-performance metric such as the share price, profit, or cash flow. As a result, it would be more appropriate to consider a two-stage approach to the issue – strategic and tactical. The following framework considers risk management, which develop ideas presented by Banks and Dunn (2003).

3.4.1

Strategic considerations

At the strategic level, a risk management strategy should consider the following issues so that the hedging solution can be placed within a particular context: ▪ What are the company’s strategic corporate goals? ▪ What issues are important to the internal and external stakeholders? ▪ What is the universe of financial risks to which the company is exposed? Which of the financial risks can be hedged? ▪ What is the appropriate strategic performance metric against which the success of the hedging programme is assessed? (e.g. share price, cash flow) ▪ What is the company’s existing risk management strategy? ▪ What is known about the competitors’ activities?

3.4.2

Tactical considerations

Only after the strategic issues have been addressed should the tactical side of hedging be considered. Some of the key issues to be addressed include:

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▪ What is the nature of the specific exposures to which the company is faced? – How certain are the exposures? – When should the hedge start? Now? In the future? What percentage of the underlying exposure should be covered? (i.e. how much risk are they willing to take?) – Is there a specific target rate or price that the customer is trying to achieve (e.g. some form of budget rate) ▪ What is the company’s current view on the market? This could be with respect to: – Direction of the market – Timing – Magnitude ▪ What hedging instruments is the company allowed to use? ▪ Is the company willing to pay a premium fee for protection? Corporate hedgers may be reluctant to express a view on the future movement of the market, sometimes claiming that they are not qualified to express a view on the market. However, it would be fair to say that any view expressed by an investment is just that – an opinion rather than a guarantee. A more efficient hedge could be constructed by a bank if the customer were able to express a view on these elements as option based strategies are normally three dimensional – they extract value from directional movements in the underlying price, the time to maturity, as well as implied volatility (i.e. the magnitude of expected price movements). Reasonably many hedgers may be concerned about the potential outcome of the hedging strategy. This can be addressed through scenario analysis. By constructing a few simple ‘what if’ scenarios the potential outcome of the hedged position could be shown. Indeed, the use of scenarios should ideally feed back into the strategic questions that are addressed at the start of the process. We argued that all hedging strategies should be placed within a larger context, as most firms hedge to solve a particular problem, such as a share price decline or an adverse movement in cash flow. The scenario analysis should feed back into how the hedged position will influence this key metric. Readers interested in this approach are referred to Charles Smithson (1998) for an example.

3.5

HEDGING CUSTOMER EXPOSURES

The trading function of a commodity market participant (be it a bank or a trading house) will be responsible for making decisions on how to manage the bank’s market and credit risk. These risks arise either from client business or from transactions designed to profit from a trader’s view as how market prices are expected to evolve. The way in which these risks are managed will have an influence on market activity and consequently the market price. The essence of derivative solutions is that they offer to market participants (corporates, institutional investors, and other financial institutions), the ability to transform some form of market or credit risk. As a result, the institution offering a particular solution will be taking on some form of risk and will therefore look to offset this in the market participant. This will also apply to both asset and liability structures.

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It would also be reasonable to suggest that in addition to managing exposures generated by client business, some traders will have discretion to execute trades that take advantage of an anticipated movement in market rates. Looking at all of these perspectives, a trader’s ‘book’ would therefore comprise a portfolio of different exposures that they will manage on an ongoing basis. Throughout the book we will analyse how commodity exposures are created and hedged using the suite of derivative products: ▪ Futures and forwards ▪ Swaps ▪ Options (vanilla and exotic)

3.5.1

Forward risk management

If a client were to enter an exchange traded futures contract, this does not result in any credit risk for the bank, as the client’s counterparty is the exchange’s clearing house. Any change in the value of the future is managed by the clearing house, through the collection of collateral (margin calls) from the customer. If a client executes a forward deal, the bank is now acting as a principal to the trade and as such this generates both credit and market risk. Given the way in which a forward price is calculated (i.e. spot price plus net carry) the bank has an exposure to a movement in all of these components. By taking an equal and offsetting position the bank can manage these risks. This concept is illustrated in the chapter on gold, where the pricing and risk of a forward deal is considered in detail.

3.5.2

Swap risk management

Hedging of swap risks can be more complex but it is possible to make some general observations. Again, the simplest hedge for the bank is an equal and opposite transaction with another market participant. However, if even the particular swap market is exceptionally liquid, this may be difficult to achieve. As a result, many banks will select instruments that are a close proxy for the exposure and run an element of market risk, usually within defined parameters. This type of market risk is referred to as basis risk and describes a situation where the value of the exposure does not change by the same amount as the hedging instrument. For example, in certain types of energy swap, based on one or more of the refined products (e.g. jet fuel), the traders may convert the exposure to a crude oil equivalent and manage the risk using exchange traded futures.

3.5.3

Option risk management

When a bank executes an option transaction it is faced with several different market risks. The market risks they look to manage relate to changes in: ▪ The underlying price. ▪ The strike price. ▪ Time to maturity.

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▪ The cost of carrying an underlying hedge. ▪ The implied volatility of the underlying asset. Each one of the listed market risks has an associated ‘Greek’ measure that is used by the banks to measure and manage a particular exposure. These Greeks and how they are used to manage market risk were analysed in Chapter 2.

3.5.4

Correlation risk management

One additional market risk worthy of mention is that of correlation risk. Correlation measures the tendency of variables to move in the same direction. Within the context of this book the focus will be on price correlation, although it is acknowledged that alternative correlation measures exist elsewhere within finance (e.g. default correlation within the credit world). Correlation risk may arise in several ways: ▪ From options that require it as a pricing input (e.g. spread and basket options). ▪ The price relationships that commodities have with each other (e.g. platinum and palladium). ▪ In the price relationships commodities have with financial assets such as bonds or equities. Similar to volatility, correlation could be estimated from historical data or be implied from current market prices. However, correlation measures tend to be unstable in volatile markets.

3.5.5

Case study: Managing market and credit – the collapse of Japan Airlines

One example of credit risk within the context of commodities was the collapse of Japan Airlines in 2010 with debts of YEN 2,322 billion. At the time this was Japan’s fourth largest corporate failure with the government pledging YEN 900 billion to keep the airline operational. The airline had hedged at least 78% of its fuel consumption but it is likely that some of this was done in 2008 and 2009 when energy prices were trading at all-time highs. The outstanding fuel hedges were estimated at USD 440 million, which was probably made up of forwards, futures, and swaps. To illustrate the nature of the counterparty risk, consider the following simplified example. In Figure 3.1 the airline establishes a commercial contract with a jet fuel supplier for delivery of the required volume of the contract. They agree between themselves that the contract price will reference some agreed index. To hedge this risk the airline enters a swap contract where they will receive the same index price for jet fuel that they are paying on the underlying contract. In exchange, they will pay to the bank a fixed price. The net result is that the airline is immunised against movements in the market price of jet fuel, but on a net basis will pay a fixed price for their fuel. The swap has market risk in that they will lose money if the price of jet fuel were to rise. As a result, they hedge

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Airline

Market Price of Jet Fuel

Physical Jet Fuel

Jet Fuel Supplier

Market Price of Jet Fuel

Long crude oil futures

Seller

FIGURE 3.1 Jet fuel swap. themselves with a long futures position in crude oil. This is not without risk as they are assuming that the price of crude oil will move in the same direction as jet fuel. Airline hedging strategies are considered in more detail in Chapter six. From the bank’s perspective credit risk only exists where the airline defaults and the derivative is in-the-money (ITM). Suppose that the fixed price on the swap had been set at USD 800.00 per metric tonne. If the market price of jet fuel were to fall, then at a very simple level, the swap would have value to the bank as they are paying out less than they are receiving. If the airline were to default, then market practice is for the derivative to be valued with any positive ‘mark to market’ (i.e. market value) being settled between the two entities. If the swap were ITM from the bank’s perspective, then they would become an unsecured creditor and would have a claim on the airline. If the swap were OTM for the bank they would be required to settle their debts with the airline’s bankruptcy practitioner. In the case where the swap is OTM for the bank, they do not have any credit risk. Credit risk only exists when an entity is owed money; money owed to the airline is a debt that must be paid. Readers interested in a more detailed explanation of derivative credit risk are referred to Gregory (2020). Since the associated swap cash flows will no longer take place, the bank is now left with an underlying hedge position. To unwind this hedge the bank will be required to sell futures back into the market, which in the case of Japan Airlines caused the market to fall in the short term.

3.6

TRADING RISK MANAGEMENT

What is trading? Although there is no single universal definition of the term, it can be characterised as the buying and selling of a commodity with profit as the main motivation. Rather than having to buy and sell the commodity or a derivative because of some underlying operational need or the desire to offset some economic exposure, trading is decidedly ‘view driven’.

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There are a whole series of strategies that fall within this category and as such the following highlights a few key themes. Throughout the text other examples will be illustrated within a particular context.

3.6.1

Spot trading strategies

A trader may decide to take an outright view on the movement of an asset. An outright deal is a single buy or sell strategy rather than some combination of deals. For example, say a trader is looking at an investment period of six months, but is not sure whether he should buy or sell. The decision is not as simple as suggesting that if he expects the price to rise then he should buy and vice versa. The decision is a function of the investment horizon and how the trader thinks that spot prices will evolve relative to initial forward price. Let us assume that gold is trading in the spot market at USD 1,425.40 per troy ounce while the six-month forward is priced at USD 1,449.10 (these are the same values as those presented in chapter two). The forward price is not a predictor of the future spot prices but should be used as a breakeven value against which all investment decisions should be judged. This is because a spot purchase which is held for a given period, will have a value equal to the forward price. This gives the trader one of three possibilities: ▪ If the trader believed that the actual spot price in six months’ time was going to be greater than the current forward price, then they should buy the gold, borrow money to finance its purchase, and lend out the gold to earn the lease rate. If their view materialises, they will be able to sell the gold at the end of the period at a price that will be greater than the cost of carrying the metal for the period. ▪ If the trader believed that the actual spot price in six months was going to be less than the current forward rate, then a selling position would be appropriate. They should sell the gold and place the proceeds on deposit to earn interest for six months. To ensure that the short position is covered, the bank would borrow the gold and pay a leasing fee. At the end of the six-month period, the gold is repurchased at the prevailing spot price and delivered to the lender of the metal. The net result is that the cash flows received exceed the cash flows paid. ▪ If the trader believed that the actual spot price in six months was going to be equal to the current forward rate, then they would be indifferent between buying and selling the gold. Note that in the second scenario it would be possible for the trader to believe that the price of gold was going to rise, albeit to a level less than the current forward rate, and this would still indicate a selling strategy. The key therefore is not whether the spot price will rise or fall but where it will be in relation to the forward rate.

3.6.2

Forward trading strategies

One obvious motivation for executing a forward trade is the fact that the trader does not have to take physical delivery of the underlying asset. In this sense it may be viewed as a more cash efficient manner of expressing a view on the market. Similar to the

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spot market, forward starting deals could be used to express a view on a directional movement in the underlying price. However, it may be more common to use forward transactions to exploit relative price movements. These would be executed as a pair of trades and may include: ▪ Taking a view that contracts trading with two different maturities may be mispriced relative to each other. Here the trader buys the contract considered to be underpriced and sells the contract that is overpriced. This strategy is based on how the shape of the forward curve is likely to move. In essence, curves could move in one of two ways. Firstly, the slope between any two maturities may increase or decrease. So, if a trader expected the slope of the forward curve to steepen the classic trade would be to sell the short-dated future and buy a longer-dated future. Secondly, the curvature of the forward curve could change. If the trader expected the curve to become more concave, then they would sell a short- and long-dated future and buy a medium-dated future. ▪ Taking a view that a historic relationship between two related prices may change. For example, a trader may identify a seasonal relationship between prices for delivery in winter and spring they believe will change. This is explored in greater detail in the Amaranth Advisors case study, which appears later in this chapter. ▪ A trader may initiate a transaction that exploits a differential between two different yet related commodities. For example, popular spread trades in the commodity markets include: – Crack spreads (e.g. gasoline or heating oil vs. crude oil). – Spark spreads (e.g. natural gas vs. power). – Base metal spreads (e.g. copper vs. aluminium). – Precious metal spreads (e.g. gold vs. silver or platinum vs. palladium).

3.6.3

Single period physically settled ‘swaps’

These are constructed as a simultaneous combination of a spot and a forward transaction. It is a temporary exchange of an asset for cash, which can be used for either: ▪ Borrowing money at an attractive rate. ▪ Obtaining temporary supplies of a commodity. A fully worked example of this type of structure is documented in the chapter on gold.

3.6.4

Single or multi-period financially settled swaps

A financial swap is either a single or multi-period exchange of cash flows that does not involve the physical movement of the commodity. A single-period swap will be economically equivalent to a cash-settled forward. From a trading perspective swaps could be used in a similar manner to forwards.

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3.6.5

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Option based trades – trading volatility

Recall from Chapter 2 that options are priced using several variables. The variables are agreed with the counterparty (e.g. maturity, strike) while other variables are easily discernible from market sources (e.g. the underlying price and interest rates). However, there is one variable – implied volatility – that although may be discernible from market sources is the source of a number of trading opportunities. Implied volatility is a measure of how volatile the market expects the asset to be until the option’s expiration. Since it attempts to quantify something in the future, it is nothing more than an educated guess – a perception of how risky the asset is expected to be. Market price screens do exist for implied volatilities, but these simply represent a consensus or equilibrium. However, it needs to be grounded in reality and so should bear some resemblance to how volatile the asset has been over a particular period (e.g. historical volatility). Expressed as an option ‘Greek’ implied volatility is referred to as ‘vega’. Accordingly, traders talk about buying and selling (implied) volatility as if it were a commodity. Recall from the pricing chapter 2 that an option buyer benefits from a rise in implied volatility, while sellers benefit from a fall. In some respects trading volatility is simple; if an option is bought, a premium is paid and a subsequent rise in implied volatility allows the buyer to take a reversing position in the market (‘sell the option back to the market’) to receive a higher premium. However, this strategy is not without risk as the option position leaves a trader with a number of other market risks (e.g. changes in the spot price, passage of time) that need to be managed. The following example illustrates how volatility could be traded and the associated risks. Trading of volatility is achieved by trading buying or selling options to achieve a particular vega exposure, while neutralising the position’s exposure to movements in the underlying price. The typical strategies for achieving this are: Selling volatility (trader believes that implied volatility will fall) i. Sell an at-the-money (ATM) call, sell an ATM put, same strike, same maturity (known as a short straddle) ii. Sell a call option and delta hedge iii. Sell a put option and delta hedge Buying volatility (trader believes that implied volatility will rise) i. Buy an ATM call, buy an ATM put, same strike, same maturity (known as a long straddle) ii. Buy a call option and delta hedge iii. Buy a put option and delta hedge Initially it can be confusing to grasp how volatility could be traded using the single option strategy, but this is usually because the option’s exposure is viewed along a single dimension. It would be more accurate to say that when executing option transactions, a trader must think in two or three dimensions, namely volatility (actual and implied) and direction. The sale of either a call or a put will result in a negative vega exposure while the delta exposure is negative for the sold call and positive for the sold put. This directional exposure is neutralised by buying the underlying (for the call) and selling the underlying (for the put) a technique referred to as delta hedging.

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Let us assume a bank has sold a three-month out-of-the-money (OTM) call option on gold on a notional amount of 10,000 troy ounces with a strike rate of USD 1,450, while spot is USD 1,425.40. With implied volatility at 15% the premium will be USD 31.66 per troy ounce. To hedge the delta exposure the trader decides to use the spot market, which is currently trading at a price of USD 1,425.40 per troy ounce. The delta of this OTM option is −0.4223, which means that if the price of the underlying were to change by a small amount, the premium on the option would change by 42.23% of the amount. Since a rise in the underlying price would cause the option to lose money, the trader decides to hedge this exposure by buying the underlying in the proportion dictated by the delta value. Since the option was written on a notional of 10,000 troy ounces the trader must buy 42.23% of this amount, namely 4,223 troy ounces. Therefore, if there is a small increase in the price of gold, the losses on the option should approximately be offset by the profits on the delta hedge. All other things being equal – mainly that the underlying price does not change – holding this position to expiry will yield a profit to the trader. The passage of time will reap a profit to the trader through the accretion of the option’s value by the theta effect. If this assumption is relaxed the main risk to the trader is to large changes in the underlying price. At first glance this may seem counterintuitive as the delta hedge was designed to ensure that the trader’s directional exposure was neutralised. However, although delta neutralises the trader against small changes in the underlying price, he is still exposed to large changes in the underlying price. Let us say that shortly after executing the trade, the price of gold rises by USD 5.00 per troy ounce to reach a level of USD 1,430.40. The option position is now valued at USD 33.82 per troy ounce, a loss to the trader of USD 2.16 per troy ounce or USD 21,600 on the option position. However, the trader will gain USD 5.00 per troy ounce on the underlying hedge. Since the delta hedge was for 4,223 troy ounces, the profit would be USD 21,115, which is insufficient to cover the loss on the option position, resulting in an overall mark-to-market loss of USD 485.00. At this point the trader is faced with a difficult decision. If the price of the underlying continues to rise, the losses on the option, which move in a non-linear fashion, will increase faster than the profits on the future, which change in a linear manner. As a result, he decides to rehedge himself at the new higher level where the delta on the option is now –44%. This means to be delta neutral he needs to buy a total of 4,400 troy ounces of gold. Since he already owns 4,223 troy ounces, he only needs to buy the difference (177 troy ounces), albeit at a new higher price of USD 1,430.40 per troy ounce. After rehedging the trader then sees that the market retraces falling back to its opening price of USD 1,425.40. On a mark-to-market (MTM) basis, the option position gains in value by USD 2.16 or USD 21,600 for the position. However, the physical hedge position in gold now loses USD 5.00 per troy ounce to give a hedge loss of USD 22,000 (4,400 ounces x USD 5.00). His net loss from this price fall is therefore USD 400.00. His total losses as a result of both price movements are therefore USD 885.00 (USD 485.00 + USD 400.00). If there were no further price movements during the trading day, the trader will have: ▪ Broken even on the option position (note the analysis is done on an intraday basis so theta is not an issue),

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▪ Broken even on the initial hedge position (4,223 troy ounces bought at USD 1,425.40), ▪ Lost money because of the rebalancing of the portfolio (an extra 177 troy ounces bought at USD 1,430.40 and revalued at the close of business at USD 1,425.40 to give a total loss of USD 885.00). What would have happened if the price had first fallen and then subsequently risen? If the price of the underlying had fallen the delta on the option would also have fallen, indicating to the trader that they were overhedged. He would then have to sell part of the hedge at a lower price. However, if the price were subsequently to rise then the hedge would have to be repurchased at a higher price. The result is therefore the same, when rebalancing the trader will be buying the hedge at a higher price and selling it at a lower price. This is the primary risk of selling options on a delta-hedged basis into a volatile market. The rate at which the option changes in value is different to that of the hedge. If the price of the underlying were to become more volatile the delta of the option would change, indicating to the option trader that the delta hedge needs to be adjusted. The magnitude of the change in delta as a result of a move in the underlying price will dictate the size of the rebalancing. With a short option position in a volatile market this will result in a mark to market loss. The rate of change of delta with respect to the underlying price is called gamma. Gamma is always expressed in relation to a range of price movements. So, in the above example the gamma for a USD 5.00 movement in the price of gold is 1.77% (44%–42.23%). Intuitively, gamma can be thought of as: ▪ The trader’s exposure to significant changes in the underlying (since delta only covers him for small changes). ▪ A trader’s exposure to movements in actual as opposed to implied volatility. Additionally, some traders think of gamma as the speed with which their profit and loss changes with respect to a change in the underlying price. The larger the gamma, the greater the difference between two delta values for a given change in the underlying price and the larger the required adjustment to the delta hedge. Hence an option with a large gamma value will generate large changes to the trader’s profit or loss. If the trader had bought options and delta-hedged under the conditions noted above, then he would have enjoyed a profit. However, there is a cost to this, as the options will decay in value over time. Therefore, option traders sometimes describe theta as “gamma rent”; it is the ‘price’ one must pay when buying volatility or the ‘reward’ one receives from selling volatility. An option trader who buys volatility is hoping that: ▪ Implied volatility will increase, leading to an increase in the value of their option position. ▪ The market will experience more (actual) volatility. ▪ Some combination of the two. If they decide to take a view on the actual volatility of the market, they hope to make more in delta hedging profits than they lose in time decay.

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An option trader who sells volatility is hoping that: ▪ Implied volatility will decrease, leading to a decrease in the value of their option position. ▪ The market will experience less (actual) volatility. ▪ Some combination of the two. If they decide to take a view on the actual volatility of the market, they hope to make more from time decay than they lose in delta hedging activities. The preceding example was based on intraday movements in order to illustrate that the source of profit or loss was from the rebalancing of the hedge position. However, the initial theta of the option was USD 0.2266 and so as a result of the passage of time, the trader will make USD 2,266, which is greater than the delta hedging loss. As the underlying price evolves traders may adjust their implied volatility quotations accordingly. One simple process to do this is as follows. By convention implied volatility numbers tend to be quoted as percentage per annum. It is possible to convert this to a daily value by dividing by the square root of the number of business days in the year (e.g. 250). An annual volatility of 15% is therefore equivalent to a daily figure of 0.95%. The trader would expect the underlying price to trade approximately within plus or minus of this range. Using our previous opening futures price of USD 1,425.40 this would imply a range of values from USD 1,411.86 to USD 1,438.94.

3.6.6

Case study: Amaranth Advisors and the US natural gas market

‘We thought about pulling the trigger and taking the loss . . . we had many discussions about it. We figured we could get out for maybe a billion dollars. But we decided to ride it out and see if the market would come around’. —Amaranth trader (United States Senate, 2007) Shortly before its collapse in the fourth quarter of 2006, Amaranth Advisors LLC managed a hedge fund valued at about USD 9.2 billion. The fund lost about USD 6 billion over a two- to three-week period because of losses on its US natural gas futures trades. US natural gas prices tend to display an element of cyclicality. That is, the price of natural gas for winter delivery is greater than for summer delivery so as a result, the forward curve for natural gas is humped in nature (see Figure 3.2). In the gas market so-called ‘spread trades’ are a common transaction. A spread trade involves taking a long position in a future of one maturity, and a short position in another maturity. A company that distributes natural gas to an end consumer may buy natural gas for summer delivery and simultaneously sell the gas for winter delivery. If the cost of storing the gas for this period is less than the spread between the two prices, then this activity will be profitable for the company. Of course, for every buyer there must be a seller who will be willing to take the opposite side of the trade, i.e. sell the gas for summer delivery and buy for winter delivery. A participant’s motive to do this trade could be driven by the view that winter prices are expected to be relatively higher than summer prices. Note that the spread between the prices is important rather than the absolute level of prices.

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Peaks are winter months

Troughs are summer months Contract maturity

FIGURE 3.2 Hypothetical forward curve for US natural gas. Source: Author Amaranth’s fundamental view was that winter natural gas prices would be much higher than summer natural gas prices. They believed this would be a result of increasing domestic demand for natural gas, expected supply shortages, delivery bottlenecks, and weather-related disruptions. Although the fund had a number of different positions, it expressed this view through two major trading strategies during 2006: ▪ Selling November 2006 futures and buying January 2007 futures. ▪ Buying March 2007 futures and selling April 2007 futures. Each spread trade is traded as a single transaction with a single price. The second trade has been termed the ‘widow maker’ as this particular price spread is very volatile. This is because March is the last month of the winter heating period when gas supplies are low and gas is being withdrawn from storage, while April is the first summer month when gas storage facilities start to be refilled. Amaranth’s view was that March prices would rise relative to April, i.e. that the spread between the two prices would increase. In late August 2006, market prices started to move against Amaranth. Before then the spread had been trading between USD 1.50 and USD 2.50. In the physical natural gas markets, there had been little hurricane activity to disrupt production and the amount of natural gas in storage was very high. Thus, the prices for the two key spread trades started to fall, i.e. the price of natural gas for winter delivery fell relative to that for summer delivery. By mid-September, the spread had fallen to USD 0.50 per MMBtu. Considering all their positions, Amaranth held as many as 100,000 natural gas futures representing one trillion cubic feet of natural gas. This was equivalent to about 5% of natural gas used in the US in a year. At times Amaranth also controlled up to 40% of all open positions on the futures exchange NYMEX for the winter month expiries of October 2006–March 2007.

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Given the size of their positions they were required to post increasing amounts of margin to the exchange. These margins eventually reached USD 3 billion. By mid-September, the fund was forced to sell its positions to its prime broker and another hedge fund, and liquidated the fund’s remaining holdings.

3.6.7

Case study: Metallgesellschaft

Metallgesellschaft AG, or MG, is a traditional German metal company, who in the early 1990s evolved into a provider of energy risk management services. They had several subsidiaries within its energy group, with MG Refining and Marketing Inc. (MGRM) in charge of refining and marketing petroleum products in the US In December 1993, it was revealed that MGRM had incurred losses of approximately USD 1.5 billion. The basic problem lay in a mismatch between the maturities of its commitments to deliver oil and oil products (heating oil and gasoline) and the derivatives used to hedge those commitments. The US arm of the group had undergone a rapid expansion of its business, through various acquisitions and had developed an ambitious marketing plan, which resulted in sales of approximately 300,000 barrels per day. In an attempt to win business MG negotiated contracts as long as five to ten years with individual service stations around the US, typically at fixed prices. Estimates suggested that they had built up long-term commitments to deliver up to 160 million barrels over a five-year period. This strategy left the group with a large exposure. Since they had contracted to sell oil and oil products in the future at a pre-agreed fixed price, unless hedged the company would have to buy oil to meet these commitments at the then prevailing market price. If the oil price were to move up it would result in large losses. MG chose to hedge this risk by buying exchange traded three-month futures contracts. This strategy was adopted because liquidity is greatest in the shorter-dated maturities even though it introduced a maturity mismatch. By buying futures MG believed it had implemented a good offsetting hedge position in relation to its fixed price client contracts. If oil prices were to increase the client contract would be unprofitable, but the futures hedge would show a profit (and vice versa). In order to maintain the hedge over the term of the client contracts, MG was obliged to roll over the futures exposure at each contract expiry. Initially the prevailing market conditions were such that futures prices tended to increase as they approached maturity, i.e. the market was in backwardation. This meant that MG was able to make profits by selling the expiring futures and buying new lower priced futures to replace them. The position could be reopened by purchasing contracts for the next delivery period at a cheaper cost of C, again in the expectation that price would rise. The traders at NYMEX were aware that MG would have to execute a substantial number of rollovers each month and started to use this information to increase the price of the futures contracts they traded with the company. Additionally, in November 1993 OPEC decided not to cut output, which caused prices to fall sharply with the price of benchmark crude falling to below USD 14.50 a barrel from a high of USD 22.00 mid-year. As a result, the forward curve fell and moved into contango. MG’s trading strategy was impacted in two ways. A fall in the price of crude oil resulted in extra margin calls of USD 200 million on MG’s long futures position. This

Risk Management Principles

75

was a daily drain on their cash flow that was not matched by income from the underlying client contracts. In addition the firm was now incurring a cost to roll the futures position due to the upward sloping nature of the forward curve; they were now being forced to close out their futures positions at a lower price than their initial purchase. At one stage MG was estimated to be losing about USD 30 million every time it rolled over the futures contracts.

CHAPTER

4

Gold

4.1

THE MARKET FOR GOLD ‘Boys, by God, I believe I’ve found a gold mine.’ —James Marshall

Along California’s Highway 49, tucked away in a beautiful valley in the Sierra Nevada foothills is the tiny town of Coloma. Running through the centre of the village is a fork of the American River where on 24 January 1848; James Marshall found some gold flakes in the streambed, sparking one of history’s largest human migrations. What are precious metals? Arguably the most recognizable precious metals are gold and silver. Another important segment market comprises of the Platinum Group Metals (PGMs). Of the PGMs there are two actively traded metals, platinum and palladium, although the category includes other non-traded metals such as: ▪ ▪ ▪ ▪

Rhodium Ruthenium Iridium Osmium

4.1.1

Physical Supply Chain

Gold is extracted from open pits or underground mines by blasting or digging. The economics of mining are such that deep level mines extract gold at purities of less than 10 grammes of gold per tonne of dirt (or ore), while for open pit operations the figure can be below one gramme per tonne. However, at this stage in its production it will contain several impurities and will not be in any usable form. It is first milled to release the metal before being refined and partly purified on site to produce doré gold bars. These bars will then be sent to refining operations dedicated to produce metal in a form that can be used by a variety of industries. The resulting output from the refiners may be in the form of bullion bars or ‘blank’ jewellery. Fabricators will then take the refined product to make jewellery or will build it into other products such as electronics, which benefit from gold’s physical properties, such as resistance to corrosion, thermal and electrical conductivity.

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4.1.2

Intermediaries

Outside of the physical supply chain sits two important entities: intermediaries (such as investment banks and trading houses) and central banks. Traditionally central bankers have been thought of as buyers of gold for reserve asset purposes. However, increasing pressures on central banks to make more effective use of their reserves resulted in them being net sellers for prolonged periods. These periods usually coincided with times when the gold price was relatively low. Intermediaries such as investment banks or trading houses will offer a variety of services that include: ▪ Helping mining companies (producers) manage their exposure to a change in market prices. ▪ Lending metal to refiners or fabricators to finance ‘in process’ inventories. ▪ Borrowing gold from central banks. ▪ Helping central banks manage their gold holdings. ▪ Acting as an intermediary between the main players in the production lifecycle. ▪ Trading with other financial institutions (e.g. hedge funds). From this brief description of the various entities within the supply chain it is possible to envisage a simple supply and demand model. Without considering the relative size of each component, the fundamental supply of gold comes from three main sources: ▪ New mine production, ▪ Existing central bank holdings, ▪ Recycling of scrap metal (the ‘urban mine’). The fundamental demand for the metal is driven primarily by: ▪ Jewellery. ▪ Physical investment (e.g. coins and bars). ▪ Industrial requirements.

Mining

Scrap

Jewellery

Flow Supply

Flow Demand

Central Banks

Physical Investment

FIGURE 4.1 Overview of gold market.

Industrial

78 4.1.3

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

The London Gold Market

Although gold is traded in a variety of different locations, London is the largest over the counter (OTC) bullion market in the world. Gold futures can be traded on various global exchanges such as the CME Group and the London Metal Exchange. The pre-eminence of London as the centre of OTC gold trading has led to the development of certain market conventions that are now accepted globally. There are three key professional trade bodies: ▪ London Bullion Markets Association (LBMA) – the LBMA acts as a standard-setting body for the global wholesale market for precious metals. The association’s membership encompasses all participants along the physical supply chain. ▪ London Platinum and Palladium Market (LPPM) – perform a similar role to the LBMA but for the PGM market. ▪ London Precious Metals Clearing Limited (LPMCL) – clearing relates to all the necessary operational activities that take place after trade execution but before settlement. Settlement is the final process that sees the final exchange of cash for the underlying asset. According to the LBMA’s website (www.lbma.org.uk),‘The clearing system is operated by the London Precious Metal Clearing (LPMCL) which is owned and managed by the five banks: HSBC, ICBC Standard Bank, JP Morgan, Scotiabank and UBS. They utilise the unallocated gold and silver, in accounts they maintain between each other, not only for settlement of mutual trades but also for trades on behalf of their third-party counterparties worldwide for whom they provide clearing facilities.’ In terms of market size, statistics produced by the London Bullion Market Association (LBMA) for August 2020 show a daily turnover of about USD 70 billion. To place this into some context the daily turnover of the foreign exchange market is USD 6.5 trillion1 . Since metals may be of different purities an element of standardisation is still important even in OTC markets. Counterparties trading on a ‘loco London’ basis (literally location London) will have an assurance that the metal traded will meet the criteria necessary for ‘London Good Delivery’. This ensures that the different bars are fungible within the market and will be delivered to a London based vault nominated by the seller. The technical name for the shape of these bars is a trapezoid prism. London Good Delivery means that a bar must conform to the following standards: Weight ▪ Minimum gold content: 350 fine ounces (approximately 10.9 kilograms). ▪ Maximum gold content: 430 fine ounces (approximately 13.4 kilograms). ▪ The gross weight of a bar should be expressed in ounces troy, in multiples of 0.025, rounded down to the nearest 0.025 of an ounce troy.

1

FX data sourced from BIS.org. Turnover figure is for 2019.

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Gold

Fineness ▪ The minimum acceptable fineness is 995 parts per thousand fine gold. Marks ▪ Serial number. ▪ Assay stamp of acceptable refiner. ▪ Year of manufacture (expressed in four digits). ▪ Marks should be stamped on the larger of the two main surfaces of the bar. As an extension of these market standards there is also a ‘loco London’ price. Settlement for the gold will take place two good London business days after trade date. A deal transacted on Wednesday, 15 January 2020 will settle on Friday, 17 January 2020. Loco London is the default basis for settlement for gold in the same way that New York is for the purchase or sale of US dollars. If an entity wishes to settle a transaction at another location or for a different level of purity, an adjustment to this benchmark price is normally made. Reference is often made to the purity of gold, which can be expressed in different ways. When using carats, the purity of gold is measured on a scale of 1 to 24. For example, gold described as being 18 carats is equal to 18/24th of 1000 parts, i.e. 750 fineness. However, the wholesale financial markets very rarely refer to carats. London Good Delivery Bars are a minimum 995/1000 fineness (or ‘two nines five’ in the market parlance). London Good Delivery Bars represent bars that have a gold content of between 350 and 430 fine ounces although most bars are generally close to 400 ounces (12.5 kg/27 pounds). Delivery will usually take place at the vault of a clearing member of the LPMCL either on an allocated or unallocated basis. Holding gold on an unallocated basis means the metal is held in a vault in common with other holdings and the customer has a general entitlement. Holding gold on an unallocated basis incurs only minimal storage costs but reduces the holder to being an unsecured creditor. That is, the owner has a claim on the bank where the gold is held but does not have title to specific bars. If gold is held on an allocated basis the metal is physically segregated from other customer holdings with detailed records being kept. Segregating the holding in an allocated account increases the degree of security as the holder is now secured, but will incur substantially higher charges. Traditionally, most of the market trading was done on an unallocated basis. The custodian banks would hold this gold on their balance sheets, but a change in regulations meant that this approach required them to set aside capital to support the business. Since bank capital will incur a cost, institutions offering this service have tried to move their client’s gold holding to an allocated basis, which would take them off the balance sheet (Financial Times, 2014a).

4.1.4

The LBMA gold price

Around the time of the original gold fixing in 1919, the Bank of England’s governor envisaged ‘an open market for gold in which not only every seller would know that he would receive the highest price the world could pay but also every buyer would know

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that he would get his gold as cheaply as the world could supply it’ (Financial Times, 2014b). Like all traded assets, price is determined by the interaction of demand and supply. However, as is common with many markets, it is convenient to quote a benchmark figure to facilitate the settlement of a variety of transactions. There are several reasons why the market needs a benchmark: ▪ Certain institutions such as central banks may have a legal requirement to trade with complete transparency and so may decide to execute a transaction at the day’s auction price. ▪ Industrial contracts may reference the benchmark to avoid conflicts of interest that may arise from an arbitrary choice of settlement price. ▪ Derivative contracts such as options can use the benchmark to avoid disputes over whether an option will be exercised or not. Since 1919 the value of gold has been ‘fixed’ twice daily apart from a 15-year period between 1939 and 1954. However, the use of the word ‘fixing’ has fallen into disrepute following several scandals relating to other benchmarks such as LIBOR. As part of a move to reform market practices, between 2014 and 2015 the old-style fixings for gold, silver, and the PGMs were transferred to independent third party administrators.2 It is now more common to refer to an auction process for gold that generates a snapshot benchmark value termed the ‘LBMA gold price’ at two predetermined times during the day (10:30 a.m. and 3:00 p.m.). There are two main categories of participant in the precious metals auction. A direct participant will manage their orders in the auction via the administrator’s electronic platform. Their trades at the end of the auction are settled with other direct participants or can be centrally cleared via the Intercontinental Exchange (ICE). An indirect participant is a client of a direct participant who will settle any transactions with their direct participant. At the time of writing there are currently 12 direct participants. The auction works in the following manner. The benchmark administrators will first propose a price to the participants. Based on this suggested price the participants have 30 seconds to submit their buying and selling volumes, which are fully executable if the auction is ‘in balance’. At the end of the 30 seconds the administrator’s system will calculate the difference between the buying and the selling volumes to see if there is a significant imbalance. If the imbalance is greater than 10,000 ounces, then the price is adjusted based on the direction of the imbalance and then the process is repeated. If the imbalance is less than 10,000 ounces, then all the volumes will trade at that price. Once the volume has been traded at this final auction price, it is then declared to be the USD benchmark price. The administrators will then convert the benchmark price into a variety of other currencies. Consider the following hypothetical auction example (Table 4.1). Suppose the initial suggested price in round 1 drew more buying volume (bids) than selling volume with the difference being 50,356 ounces. Since this was outside

2

At the time of writing the LBMA gold price is managed by ICE benchmark administration.

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Gold

TABLE 4.1 Hypothetical example of gold auction. Round

Price

Bid volume

Ask volume

1 2 3 4 5

1329.15 1329.55 1330.15 1329.90 1329.75

80,579 80,579 80,579 80,579 80,579

30,223 35,223 114,223 94,223 85,223

the 10,000-ounce imbalance threshold, then the price was increased for the second round. Although the second round attracted more sellers, the imbalance persisted and so the price increased for a third time. However, the increase in price for the third round attracted substantially more sellers than buyers and so the imbalance flipped. The price was then reduced for the fourth and fifth round when the price finally set at USD 1,329.75 and a demand/supply difference of 4,644 ounces. In addition to the spot market, two other key parts of the gold market are outright forwards and swaps. Until 2015 the LBMA operated a fixing to set what was referred to as ‘GOFO’ (gold forward offered rate). However, this fixing has now been discontinued although the concept may still be used in wholesale transactions. However, instead of quoting the forward price in outright USD terms the market makers quote the GOFO rate as the difference between the spot and forward USD prices expressed as a percent per annum. These transactions will be considered later.

4.2

GOLD PRICE DRIVERS ‘Gold gets dug out of the ground in Africa or some place. Then we melt it down, dig another hole, bury it again and pay people to stand around guarding it. Anyone watching from Mars would be scratching their head’. —Warren Buffet ‘There is one unique feature of gold that is possessed by no other investment and which ensures it is an investment of choice for many: its place in the human psyche. It has been a global monetary unit for more than 2,500 years while also having significance in language, tradition and religion’. —Jonathan Spall (Financial Times 2010c) ‘[The gold price represents] the longest lasting bubble in human history . . . [I would not invest my wealth] into something without intrinsic value, something whose positive value is based on nothing more than a set of selfconfirming beliefs’. —Willem Buiter (Economist, 2010)

It is generally accepted that there is no direct link between the price of gold and the balance of supply and demand for the physical commodity. This is because gold is

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almost indestructible and there is a large inventory of the metal held above ground. This means that a sudden increase in demand could easily be met out of existing supplies. For example, a net increase in physical supply over demand could still be associated with an increase in price. If there was, say, an increase in speculative investment demand as well a weakening in the dollar, the metal would become relatively cheaper for non-USD investors. ‘It is hard to put an objective valuation on gold, as demand for it is essentially irrational – its value is in the eye of the beholder’. —John Authers

4.2.1

The price of gold

Like most metals gold is denominated in US dollars (USD) and in volume terms it is traded in troy ounces. A troy ounce is slightly less than a conventional avoirdupois ounce. The maximum nominal (i.e. non-inflation adjusted) price of gold occurred on 5 August 2020 when it reached a level of USD 2,048.15.

4.2.2

Supply of gold

Production of gold over the past 6,000 years has totaled around 187,0003 tonnes of which approximately 80% is still in existence with the remaining balance probably lost at sea. However, most of the gold has been produced in relatively recent times with 90% of all gold having been mined since the Californian gold rush of the mid-nineteenth century. After central bank attempts to control the market value of the metal proved to be futile, true liberalisation of the gold price really started to be seen in the 1960s and 1970s. This prompted a massive boom in production of the metal and is evidenced by the fact that 60% of all gold has been mined since the 1950s. At this time, the metal was trading at about USD 35.00 per troy ounce and by 2020 had reached its all-time peak of USD 2,048.15. In the late 1990s as the price of the metal fell back many producers reduced the amount of expenditure on exploration and so production in subsequent years was relatively flat. It is also noticeable that the production of gold has experienced a certain geographical drift away from the mature markets of South Africa and North America to new areas of production such as Asia, Latin America, and Russia. It is also worth noting that reserves of the metal are becoming more difficult and expensive to extract. For example, in South Africa, the producers are already operating at depths of 4 kilometres. South Africa has traditionally been thought of as the largest producer of the metal. However, over the last 20 years they have seen production fall in both absolute and percentage terms. In the early 1970s the country was producing about 1,000 tonnes per annum, which accounted for about 70% of all world production. By 2019 their output had fallen to 118 tonnes, which represented about 3% of total mine supply. The largest 3

Source: World Gold Council (www.gold.org)

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Gold

supplier of gold is now China who produced about 383 tonnes of metal in 20194 (about 11% of total world production). Figure 4.2 shows the distribution of global production. How much gold is left? In the first edition of this text, a figure produced by the World Gold Council (whose membership includes gold mining companies) estimated that in 2002, there were 1,227 million ounces or just over 38,000 tonnes of the metal remaining in the ground. This represented about 15 years of production. A figure produced in 2020 by the US Geological Society (USGS) suggested that the figure was currently 53,000 tonnes, which is about 14 years of current production. This would suggest that there is still a relative abundance of gold, albeit at significant depths beneath the earth’s surface. Figure 4.3 shows the way in which supply has evolved over the period from 1980 to 2016. The key features are: ▪ Overall production from mines has continued to rise and is still the major source of new supply. ▪ After many years, official sales by central banks are no longer a key component of the available supply; this sector of the market has become a source of demand. ▪ As the price of the metal has risen there has been more incentive to recycle gold and hence the relative importance of scrap has increased. There are, however, regional South Africa 118 China 383.2

Ghana 142

Peru 143

Canada 182.9 Russia 329.5

USA 200.2 Australia 325.1

FIGURE 4.2 Production of gold by geographic location (tonnes). Source: World Gold Council 4

Source: World Gold Council (www.gold.org)

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

differences. For example, in Asia it is quite common to trade in old or unfashionable pieces for new items unlike the West, where bid-offer spreads for this activity are not as attractive. ▪ Producer hedging activities were a source of supply until 1999. Thereafter this sector underwent a period of dehedging apart from the period 2014 to 2016. It is not automatically obvious why the act of selling their production forward by mining companies contributes to an increase in supply5 . On the other side of the transaction there will be an intermediary such as a trading house or investment bank, who are long gold for forward delivery. If this exposure is unhedged, they will lose money if prices were to fall. To hedge this exposure, this intermediary will borrow gold in the leasing market and sell for spot value. When the forward matures the producer delivers the gold at a fixed price to the intermediary who uses this metal to repay their borrowing. It is this borrowing by the intermediary that introduces more gold onto the spot market therefore increasing its supply. This could of course work in the opposite direction. As the price of gold started to rise in the late 1990s and early twenty-first century, mining companies that had fixed the price of the metal for forward delivery at relatively low prices came under pressure from shareholders to unwind these transactions. As the positions were bought back, the opposite effect occurred; the intermediaries bought the metal for spot value and then lent the gold. The combination of this spot purchase and subsequent leasing activity resulted not only in an increase in demand but also led to an 6,000 Producer hedging

5,000

4,000 Recycled 3,000

Official sales

2,000 Mine production 1,000

0

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

Mine Production

Official Sales

Recycled

FIGURE 4.3 Components of gold supply 1980 – 2019 (tonnes). Source: World Gold Council 5

A detailed example is given in section 4.4.1.1.

Producer hedging

85

Gold

increase in the price of the metal creating something of a virtuous circle for producers. Another consequence was that it pushed lease rates to all time historic lows.

4.2.3

The Demand for gold

‘Gold is a need of the people. It is not a luxury item; it is an essential’. —Mumbai Gold Merchant (Financial Times, 2016) The factors that influence the demand for gold include: ▪ ▪ ▪ ▪ ▪

Investor activity Industrial uses Official central bank purchases Jewellery Producer hedging activities

Since 1980, the use of gold for investment purposes has been very volatile. However, post the financial crisis, which coincided with a sharp increase in the gold price, investor interest in gold increased substantially. One of the major sources of investment demand has been from exchange traded products (ETPs), which will be considered in Chapter 14. The largest component of demand is traditionally jewellery, but it is very sensitive to increases in the price of gold. One of the points shown on Figure 4.4 is the changing role of central banks in the demand and supply equation. Like most financial institutions central banks will have 6,000

5,000 Producer dehedging Investment

4,000

3,000

Fabrication

Official purchases

2,000 Jewellery 1,000

0 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

Jewellery

Official Purchases

Other Fabrication

FIGURE 4.4 Components of gold demand 1980–2019. Source: World Gold Council

Investment

Producer Dehedging

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a portfolio of assets, which have traditionally included gold. The argument for holding gold is that it is not affected by the economic policies of any one country; holding the asset acts not only as a valuable diversifier but also gives an element of economic security. It has also been an effective hedge against inflation and currency weakness. However, some governments have questioned their need to hold gold since it does not intrinsically earn any income. Although there is an active market for leasing gold, the returns from this may be below alternative investments. As of October 2020, the Federal Reserve in the USA still has the largest holding of reserves at some 8,134 tonnes, with Germany holding the second largest amount (3,362 tonnes) (see Figure 4.5). The United Kingdom has been one country that has been seeking to manage its gold reserves more actively and now only ranks 18th overall with a holding of about 310 tonnes6 . One of the main features of central bank holdings over recent times has been the increase in holdings by emerging market participants. For example, China has increased its holdings from 600 tonnes in early 2009 to 1,948 tonnes by mid-2020. During the 1980s governments purchased a net amount of over 600 tonnes, but in the following two decades they disposed of about 4,400 tonnes on a net basis figure (4.6). Following the sharp rise in gold prices in the mid ‘noughties’ the trend changed, and they became net purchasers of gold. Figure 4.6 shows the reported central bank activity over the period from 1980 to 2019 showing the annual purchase and sales, and the cumulative activity. With the central banks holding a significant proportion of metal above ground their selling activity in the 1980s and 1990s pushed the price of gold down towards USD 250 per ounce. As a result, pressure from producers led to the first central banks gold France 2,436

Italy 2,452

USA 8,134

IMF 2,814

Germany 3,362

FIGURE 4.5 Central banks gold holdings (tonnes; figures as of October 2020). Source: World Gold Council 6

A detailed example is given in section 4.4.1.1.

87

Gold 1,000

800

0

600

-1,000

400

-2,000

200

-3,000

0

-4,000

-200

-5,000

-400

-6,000

-600 -800

-7,000 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

Official sector sales (RHS)

Cumulative activity (LHS)

FIGURE 4.6 Central banks sales / purchases 1980–2019. Source: World Gold Council agreement (‘The Washington Agreement’) in 1999. The original agreement existed for five years and was signed by 15 central banks. The agreement was designed to avoid excessive fluctuations in the price of gold and has been extended three further times. The latest agreement was signed in 2014 by the European Central Bank and 20 other central banks and will last until 2019. The main features of the agreement are: ▪ Gold will still be used as part of the signatories’ monetary reserves. ▪ The signatories will continue to coordinate their gold transactions to avoid market disruptions. ▪ The signatories to the agreement currently do not have any plans to sell significant amounts of gold. The annual limit for sales has been set at 400 tonnes for the third and fourth agreement. Jewellery demand has risen over the period illustrated in Figure 4.4 but peak demand was reached in 1997 (3,350 tonnes). The current figure (end of year 2019) is 2,137 tonnes, which accounts for about 44% of all demand. The general increase in demand until the late 1990s was largely attributable to the long-term decline in the gold price from a peak value in 1980. However, from then on, the demand for jewellery has declined as the price of gold has risen from relatively low values. As the price of gold increased there was a move away from jewellery to gold for investment purposes. In 1980, gold experienced a significant nominal peak largely because of the Russian invasion of Afghanistan. At this time investment demand accounted for over 360 tonnes,

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

which was about 70% of total demand. During the 1980s it averaged 30% but during the 1990s it only accounted for only about 8% of the total. By 2001, the figure had fallen to 6%, but with the rise in the price of gold during the next decade it increased to reach a peak of 1,763 tonnes by 2011 (39% of demand). Part of the reason for the increase in investment demand has been the introduction of exchange traded products (ETPs). These are securities that track the price of gold and can be traded on a stock exchange.7

4.2.4

Gold price relationships

Since gold can be used to produce tangible goods, the price of gold will be affected by fundamental demand and supply dynamics but because it also traded as a currency then to an extent it will also be influenced by macroeconomic and financial drivers. ‘Gold does not protect against inflation or deflation per se but it is likely to do well in either scenario as it is a hedge against financial dislocation and uncertainty’. —Jonathan Spall (Financial Times 2010c)

Inflation One of the classic theories is that gold is a good hedge for inflation. Before considering the validity of this statement it is necessary to digress to consider a few aspects of the traded inflation market. One of the most popular relationships used in the inflation markets is the Fisher equation. In a simplified shorthand form it states: Nominal yields = Real yield + expected inflation + risk premium To explain each of these factors consider the following simple example. Suppose an investor has USD 100.00 to invest for a 12-month period. Her bank offers her a deposit rate of 3%; this is the nominal yield. According to the Fisher equation, this nominal yield can be decomposed into three individual components. The first is expected inflation which if one assumes to be, say, 2% p.a. then what costs USD 100.00 today will cost USD 102.00 in 12 months’ time. The second component is the risk premium, which is an additional return that an investor demands for unexpected inflation; for ease of illustration this will be assumed to be zero. In practice the inflation market tends to combine inflation expectations with the risk premium referring to the measure as ‘breakeven inflation’8 . The final component is the real yield, which based on the previous figures returns a residual value of 1%. But defining the real yield as a residual element does not convey any meaningful sense to this element of the equation. A real yield signals how much today’s savings are worth in terms of

7

See Chapter 14. In reality nominal yields rates are impacted by several factors so it is more accurate to describe the difference between nominal and real yields as the breakeven spread.

8

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additional future consumption. So, a basket of goods and services costing USD 100.00 at the start of the period would cost USD 102.00 one year later. By forgoing immediate consumption and saving USD 100.00 means the investor ends up with a cash flow of USD 103.00 at the end of the period and so can afford approximately 1%9 more goods and services. One aspect of recent times is the existence of negative real yields. Using the same example, suppose that nominal rates are 1%, inflation expectations are 3%, and the risk premium remains at 0%. This suggests that real rates are −2%. The investor saves USD 100.00 for 12 months and receives a cash flow of USD 101.00. However, the basket of goods and services now costs USD 103.00. This means the investor is now worse off by saving. Logically, they should have spent the money at the start of the period; saving for the proverbial ‘rainy day’ is not a wise move in this case! Returning to gold’s relationship with inflation, the question that needs to be asked is what type of inflation; historic or expected? Presumably when investors buy gold as an inflationary hedge, most hold some expectation of how inflation will evolve. Therefore, comparing the evolution of gold prices with historic inflation values may not be valid. In Figure 4.8 the price of gold is plotted against inflation breakevens10 (i.e. expected inflation). The chart breaks down the relationship between the two variables on a year-by-year basis. The relationship is not clear-cut. Arguably at low levels of expected inflation there is no positive relationship between the two variables (2014–2017). Only in 2013 is the relationship relatively pronounced and casual empiricism suggests that in 2011 there appears to be no correlation. 2000.000 1900.000 1800.000 1700.000 1600.000 1500.000 1400.000 1300.000 1200.000 1100.000 1000.000 1.500

1.700

1.900

2.100 2017

2.300 2016

2015

2.500 2014

2.700 2013

2.900 2012

3.100

3.300

3.500

2011

FIGURE 4.7 Gold price plotted against inflation breakevens. Source: Data sourced from Barclays Bank

9

Strictly speaking it is 0.98% (USD 103.00 / 102.00 −1 × 100). The breakeven rate used is the five-year zero coupon inflation swap rate, five years forward. This measure is used by central banks such as the Federal Reserve to monitor how inflation expectations are evolving. 10

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2,000 1,900 1,800 1,700 1,600 1,500 1,400 1,300 1,200 1,100 1,000 -2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

FIGURE 4.8 Gold price plotted against real interest rates. Source: Barclays Bank Figure 4.8 shows a more interesting relationship and that is a scatter graph of gold against real interest rates.11 Here there is much clearer relationship; as real rates fall, the price of gold will tend to rise. A possible explanation is that since gold does not pay dividends or coupons (although it is possible to lend gold and earn a relatively low nominal lease rate) a rise in real rates would encourage investors to switch out of gold into higher real yield earning assets. US Dollar Another popular relationship is the price of gold against the US dollar. Indeed, many participants treat the USDXAU (US dollar vs. Gold) relationship as a currency pair as they would say USDJPY. Gold’s role as a currency relates back to earlier days when coins were made from gold and then attempts by governments to link monetary policy to the metal. In addition, there is the observed investor behaviour that in times of economic turmoil investors fear that other debts may not be repaid and so will seek out ‘safe havens’ such as gold to offset other potential losses. The turnover in gold is quite difficult to compare to currency markets. It is a much smaller market than foreign exchange and a former colleague of the author once described gold as being like CAD or CHF in terms of volumes traded. Modeling the gold price An interesting approach to modeling the gold price was published by Barclays (2013). They argue: ‘compared with other metals gold is a particularly complex commodity to model. Not only is it affected by demand and supply dynamics, but it also plays the role of a currency and, as a result, is influenced by several macroeconomic and financial drivers. Furthermore, gold is sentiment driven, making it 11

The measure of real rates is five-year real rate swap rates.

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important to assess investor confidence. Large above ground inventories (given that all the gold that has ever been mined still exists in some form) weaken the link between gold prices and the supply and demand balance. In the short run, gold moves away from the market balance equilibrium, mainly because of its currency role. This is inevitably linked to economic indicators, the state of financial markets, market confidence and political tensions’. Their model included the following factors as explanatory variables for the spot price of gold: Highly significant explanatory variables ▪ Price momentum (positive relationship). ▪ US dollar index (negative relationship). ▪ Physically backed gold exchange traded products (ETP) holdings (positive relationship). ▪ Euro Stoxx 50 index (negative relationship). ▪ MSCI emerging market index (positive relationship). Significant explanatory variables ▪ US 10-year breakevens (positive relationship). ▪ University of Michigan Consumer sentiment index (negative relationship). ▪ US 10-year real yields (negative relationship). ▪ US presidential approval ratings (negative relationship). ▪ An in-house measure of industrial production from 30 countries (positive relationship).

4.3

THE GOLD LEASING AND DEPOSIT MARKET

One of the factors that distinguish the gold market from that of, say, base metals, is the large amount of metal that already exists above ground. This excess of metal has led to the development of an active leasing market12 . In a leasing transaction, the lender will temporarily transfer title of the gold to another entity for an agreed period in return for earning interest either in gold or in cash. From the lender’s point of view this could be a useful way of earning income on an asset that otherwise has no intrinsic return. However, it should always be borne in mind that an opportunity cost exists as gold interest rates are generally lower than unsecured interbank rates. The holder of gold can always sell the metal and invest the proceeds in a simple USD deposit. And with pressure coming to bear on central banks to make gold ‘earn its keep’, many entities have been tempted to go down this path, particularly in a low lease rate environment. Although the main purpose of the leasing market is to borrow and lend metal, care must be taken when using these terms within other metals markets. For example,

12

Some market participants may use the term ‘deposit’ in relation to this market.

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within the base metals market, ‘a borrow’ is a simultaneous purchase and sale for different value dates. This type of transaction will be analysed in greater detail in the base metals chapter. Therefore, the terms ‘leasing’ and ‘deposits’ should be used with respect to the gold market to avoid confusion. To understand the subtleties of the leasing market, it is instructive to take a sidestep and consider how gold forward prices are formed.

4.3.1

Forward price formation

To illustrate the principles of forward price formation, take the example of a gold producer who wishes to achieve a degree of price certainty over future production13 . The producer approaches a bank asking for a price for delivery of gold in, say, six months. There is an old derivatives adage that states that the price of any product will be driven by the cost of hedging the bank’s own exposure – ‘if you can hedge it, you can price it!’. If the bank does not hedge itself then in six months’ time it will take delivery of gold at the pre-agreed price and will then be holding an asset whose current market value could be lower (or higher) than the price paid to the producer. To avoid the risk that the price of gold will fall, the bank executes a series of transactions on the trade date that will mitigate this risk. Since the bank is agreeing to receive a fixed amount of gold in the future, it sells the same amount in the spot market. However, the bank has sold a quantity of metal now that it will not take delivery of until a future period; six months in this case. To fulfill the spot commitment, it leases the gold until the maturity of the contract with the producer. Having sold the gold spot and borrowed to cover the sale, the bank is now left holding dollars. Since the bank would be looking to manage its cash balances efficiently, these dollars would now be invested until the producer delivers the gold in six months’ time. As a result, it is possible at the inception of the trade to identify all the associated hedging cash flows, allowing the bank to quote a price that will ensure no loss at the point of delivery. The maturing principal plus interest on the USD cash deposit is used to pay the producer on the maturity of the contract. The gold received from the producer is used to repay the gold leased from the central bank. The maximum amount the bank will pay the producer cannot exceed the proceeds received from the initial spot sale of the metal plus the interest received from the dollar deposit less the fee to the lender of gold. A numerical example may help illustrate the point. We will assume that the producer asks for a six-month (182 days) forward price. For simplicity we will base the calculations on a single ounce and use a spot price of USD 1,300. The trader sells the metal for spot value at USD 1,300 and to complete the delivery, he borrows from the local central bank for six months at a lease rate of 0.25% per annum. The dollars received from the spot sale are put on deposit for six months at LIBOR to earn the prevailing rate of 2% per annum. Performing a quick calculation the trader works out that the borrowing

13 It may well be that the hedging of future revenues may also be associated with some form of bank financing. That is, the bank will only lend money to a producer if it takes steps to ensure the stability of future income to service the debt.

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fee equates to USD 1.64 (spot price x lease rate x 182/360) and that he will earn USD 13.14 from the deposit (spot sale proceeds x LIBOR x 182/360). The maximum amount the bank can afford to pay the producer is USD 1,311.50. This is calculated as spot sale proceeds plus interest on the LIBOR deposit minus the leasing cost. The forward price is simply the spot price plus the cost of carrying an underlying hedge. It is important to note that the shorter the time to maturity the smaller the differential will be between the spot and forward price since the hedge is carried for a shorter period. Indeed, if every day we were to recalculate the forward price applicable for a single fixed date in the future, the differential would reduce (all other things being equal). By the spot value date the two prices will have converged, although, in reality this convergence would not happen in a linear fashion as it is dependent on how the other components of the forward price move (e.g. LIBOR and the lease rate). Note that in this example, the forward price is greater than the spot price. This does not means that the bank thinks that the gold price will increase over time or that it is the market’s best guess of future spot prices. The forward price is a mathematical construct that reflects the income and expense from hedging the underlying exposure. In the interbank market the convention for quoting forward prices is similar to that seen in the FX markets – i.e. interbank participants do not quote the forward price (e.g. USD 1,311.50), but quote the difference between spot and forward prices as a percentage per annum. For this example, the quote would be: = (Forward price∕spot price) − 1 × 360∕182 = (1, 311.50∕1, 300) − 1 × 360∕182 = 1.7498% This differential has a special name in the gold market and is variously called the GOFO rate/swap rate/contango bid. GOFO is a shortened version of Gold Forward Offered Rate. By way of example the following hypothetical quotes shown in Table 4.2 are based on a mid-market spot rate of USD 1,331. TABLE 4.2 Forward gold prices. Maturity

Swap bid

Swap offer

Outright bid

Outright offer

1 week 2 weeks 1 month 2 month 3 month 6 month 9 month 12 month 24 months

1.6000 1.6250 1.6600 1.7300 1.7900 1.8700 1.9700 2.0700 2.2350

1.8000 1.7750 1.7600 1.8300 1.8900 1.9700 2.0700 2.1700 2.3850

1331.06 1331.49 1332.55 1.334.42 1336.67 1343.23 1350.53 1358.58 1390.96

1331.30 1331.75 1332.85 1334.82 1337.19 1344.08 1351.72 1360.11 1395.19

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Note that term structure of outright prices rises with respect to maturity. This is a reflection that, in all cases, LIBOR exceeded lease rates and so the swap rate (‘GOFO’) is positive. It is rare for swap rates to be negative; this would only happen if lease rates were greater than LIBOR.

4.3.2

Deriving implied lease rates

When deriving the forward price for gold it was assumed that spot, LIBOR, and the lease rate were all observable. However, data on actual leased transactions is not routinely reported and so the lease rate can be inferred from observable values. Since: Forward price = spot price + LIBOR − Lease rate

(4.1)

Forward price − spot price = LIBOR − Lease rate

(4.2)

Rearranging:

Since the difference between spot and forward prices is the swap rate, then equation (4.2) can be rewritten as: Swap rate = LIBOR − lease rate

(4.3)

Swap rate − LIBOR = lease rate

(4.4)

So,

If the six-month gold swap rate were 2% p.a. and six-month LIBOR was 1.5% p.a., it would imply a lease rate of 0.50% p.a.

4.3.3

Who lends and borrows gold?

On the supply side of the lease market the main players include central banks and institutional investors, both of whom are looking to enhance the return on their physical holdings. On the demand side a variety of factors could impact the level of lease rates. They include: ▪ The level of money market interest rates (e.g. LIBOR, although this relationship has experienced times of dislocation). ▪ Producer hedging programmes. ▪ Demand from jewellery manufacturers. ▪ Demand from speculative short selling. Firstly, there is the absolute level of interest rates. It would seem reasonable to assume that a fall in interest rates will cause lease rates to fall. Secondly, one of the key reasons why gold is borrowed is to facilitate producer hedging programmes. As producers reduce the hedging of their mined product, the lease rates begin to fall. This was covered in the section that analysed demand and supply price drivers. The lease

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market displays a term structure with different rates being charged depending on the maturity of the transaction. As a rule of thumb, producer hedging activity tends to drive the longer end of the curve towards the 12-month maturity and beyond, while central bank lending activity tends to be focused on shorter maturities. A change in the level of activity of either of these entities can cause the shape of the curve to change. However, there are exceptions to this generalised explanation of how the curve moves. For example, certain producer hedging products (e.g. a floating rate forward) derive their value from shorter-term rates and therefore drive that part of the curve. Another factor influencing the level of lease rates is the utilisation of the market by refiners or fabricators. Take a jewellery fabricator; in normal circumstances one would expect them to have to buy the gold and then transform it into jewellery. However, they may have to pay for the raw materials before selling the gold. This may involve having to borrow US dollars and will leave them open to an element of price risk (i.e. the difference between what they pay for the raw material and what they eventually raise from the final sale). An alternative strategy is for the fabricator to borrow gold from a bank and use that to produce the final product. When the product is sold, they can then use the proceeds of the sale to buy the physical gold from the spot market and repay the gold loan. In this way the price risk is eliminated and the cost of leasing the gold is lower than the US dollar LIBOR rate they will have paid to finance a purchase of metal from a producer. If a speculator believed that the price of gold was going to fall then he could sell the metal for spot delivery, borrow it on the leasing market to fulfill the sale, and wait for the price of gold to fall before buying it back from the market, hopefully at a lower price. The purchase is used to repay the loan of the metal. The profit to the short seller would be the difference between their buy and sell price less the lease rate paid. However, in a rising price scenario this strategy may be less popular, so no demand for borrowing gold is created, putting further downward pressure on lease rates. It is also possible for the lease payments to be made in gold, so called ‘gold in gold’ contracts. The interest rates for these transactions differ slightly from those charged for cash transactions. Assume we have a one-year lease rate (zero coupon, actual/360 day basis) of 0.75%, a gold swap rate of 3.75% (defined here as the annual percentage difference between the spot and the forward rate), and a spot gold price of USD 1,300. Let us assume that a financial institution lends out 100,000 ounces for this one-year period (365 days). This would give the following payment in ounces (rounded): 100,000 × 0.75% × 365∕360 = 760 oz. The monetary equivalent for forward value in one year’s time can be determined by applying today’s one-year forward price to the number of ounces settled. The one-year forward price is calculated as: Spot price × [1 + (swap rate × days in period∕360)] USD 1,300 × [1 + (0.0375 × 365∕360)] = USD 1,349.43 Which, when applied to the settlement amount in ounces, gives a forward value of USD 1,025,566.80 (760 ounces x USD 1,349.43).

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If the same transaction were done for payment in cash, the amount to be repaid at the contract’s maturity would be based on the current spot price: 100,000 × USD 1,300 × 0.75% × 365∕360 = USD 988,541.67 To make both transactions equal in monetary terms one year forward, this would mean that the lease rate for ‘gold in gold’ transactions would have to be 0.722527%. This is calculated as: [(USD 988, 541.67∕USD 1, 349.43) × (360∕365)]∕100,000

4.4 4.4.1

HEDGING Forwards

Arguably, one of the main risk management issues for producers is the amount of revenue generated from either current or future production. From a logistical perspective the producer needs to match the timing of hedging transactions with planned future mining activity. The interested reader is referred to the research document written by Jessica Cross (2001) for an outline of producer motivations and hedging philosophies. Producers have typically favoured hedging products that are easy to understand, represent ‘good value’, can be processed using their existing computer systems, and can attract favourable accounting treatment. It comes as no surprise to find that simple ‘vanilla’ forward and option products are often the most preferred structures. It is worth noting at this point that forwards could come in different variations. It is also possible to consider two other possibilities: 1. The exchange of a pre-agreed amount of cash for a pre-agreed amount of gold at a pre-agreed date where delivery will require the actual physical movement of the metal. For example, a producer sells forward new mine production in exchange for a fixed USD amount. 2. The exchange of a pre-agreed amount of cash for a pre-agreed amount of gold at a pre-agreed date, where delivery is done by ‘book entry’. For example, two banks trade unallocated gold and so the metal stays in a vault but the client’s respective holdings are updated accordingly. Investment banks have developed a wide range of variations based on the humble forward. A comprehensive analysis of the relative merits of each product is provided in the publication ‘Gold Derivatives: the market view’ (Cross, 2001). The following is a short description of some of the main products. With all these deal types the structuring bank simply alters the constituents of the forward price (LIBOR, lease rate, maturity), which allows the producer more flexibility to express views on the direction of certain market parameters.

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Spot deferred – in this transaction the two parties agree the spot price at the outset. However, there is no fixed maturity, and the deal can be terminated with the appropriate amount of notice. The final forward price is based on the daily movement of the LIBOR and lease rates. This is in effect a rolling contract where gold is initially sold for spot value (trade date plus two business days). The following day, the position is rolled forward by buying back and then reselling for spot value. This effectively pushes the settlement date one day further forward. As part of the transaction the dollar proceeds earned from the sale are invested on an overnight basis while lease costs are incurred to cover the short sale. The transaction settles daily with a debit/credit being made to the customer’s account based on the movement of LIBOR and the lease rates. This structure allows the producer to earn the short-term contango. Floating rate forwards – here the contract fixes the appropriate spot gold price and LIBOR components of the contango for the maturity of the contract. However, the final forward price is not calculated until maturity and is based on an average value of a short-term lease rate over the life of the deal (e.g. the three-month lease rate). The flat rate forward – in this contract the producer sells its production forward in stages over an agreed period. For example, the producer may agree to a contract with a 12-month final maturity with the gold being delivered every three months. Under normal forward pricing theory this would involve a different price for each settlement. However, as the product name suggests the contract is structured in such a way that each of the four deliveries takes place at a single forward price. The single price is based on the weighted average of the forward prices at each settlement date. The calculation is the sum of the forward rates at each of the delivery dates weighted by a discount factor of the same maturity, all divided by the sum of the discount factors. An example of a structured forward is: Convertible forward – this can be constructed by combining the purchase of a vanilla put option and the sale of a reverse knock in call option, both with the same strike. This transaction is structured to have zero cost by manipulating the barrier on the reverse knock in call. The strategy is based on the principle of put-call parity to create a synthetic forward. The mathematical form of put-call parity varies according to the type of underlying asset (see Tompkins, 1994), but can be expressed in a convenient way as: +C − P = +F That is, the purchase of a call (+C) and the sale of a put (−P) with the same strike, notional and maturity will be equivalent to having purchased the underlying asset (+F). For the convertible forward structure, the initial position is that the producer owns a given amount of the physical gold in addition to which they have bought protection against a price decline by buying a put (+P). In addition, the producer sells a reverse knock in call option (−C). This barrier option has a trigger point placed above the spot rate, which will activate the option if the price of gold rises. This makes the barrier an ‘up and in’ call option. If the trigger is hit activating the short call, combining this with a long put will give the producer a synthetic short forward position in gold (e.g. −C+P = −F), which when combined with their long physical holding in the metal will ensure them of a fixed delivery price.

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Unwinding forward sales

The value of any forward position will change as the underlying price drivers change. For example, a producer may be tempted to unwind a forward hedge if the spot price of gold has risen substantially, since it would now be better to sell the gold in the spot market. Indeed, several gold mine producers (e.g. Barrick in 2009) faced shareholder pressure to unwind long-dated forward hedges as the price of gold rose. Given that many banks will now require collateral to be deposited for profitable transactions a rise in the gold price will have required producers to deposit increasing amounts of cash which will have caused a strain on their cash flow. Say the producer enters a three year forward at a pre-agreed fixed price for the sale of gold at a price of USD 500.00/oz. Assume that two years later, the price of gold has risen substantially such that the prevailing one year forward price is USD 1,100. The existing hedge position is now unfavourable relative to the underlying market. The producer contacts an investment bank requesting a price to unwind the hedge. This ‘break cost’ will simply be the ‘mark to market’ (i.e. the current value) of the transaction. The producer has an agreement to deliver a fixed amount of gold for a fixed price on an agreed fixed date. To neutralise this exposure they could do a reversing deal, where for the same maturity date the producer could agree to buy the same amount of gold and pay a fixed sum of money. The break cost is simply the difference in value between the original deal and the reversing position, which is settled in cash. This break cost is sometimes referred to as an ‘exit price’14 . Using the figures quoted above, the producer would incur a gross termination cost of USD 600.00 (USD 500.00 − USD 1,100). Since this maturity is still one year away this would need to be present valued using an appropriate one-year zero coupon rate. If it is assumed that the appropriate rate is 3% and there is exactly one year to maturity, the settlement amount is: USD 600.00∕(1.03) = USD 582.52 This represents a mark-to-market loss from the producer’s perspective. If the producer were a non-USD entity this would then have to be translated back to their domestic currency, using the one-year forward currency rate. 4.4.1.2

Gold swaps to alter a delivery date

Suppose that a gold producer has a legacy outright forward sale in effect that requires them to deliver 50,000 ounces on an agreed fixed date at a price of USD 1,300/oz. The producer realises that due to operational issues they will be unable to deliver the gold on the required date and so contacts the contracting bank to defer the delivery date. This deferral can be achieved using a gold swap traded two days before the original forward 14 The exit price is usually defined as the price that would be received to sell an asset or paid to transfer a liability in an orderly transaction between market participants at the measurement date.

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deal becomes due. The following example is done from the client’s perspective and the cash flows are based on the values in Table 4.2. Original outright forward (due to settle in two days’ time)

Gold leg Sell 50,000 oz.

USD leg Receive USD 1,300/oz.

Gold swap

Spot Six month

Buy 50,000 oz. Sell 50,000 oz.

Pay USD 1,330/oz. Receive USD 1,343/oz.

The spot leg of the swap is designed to reverse the original outright forward transaction. On this date, the amount of gold to be dealt nets off and the customer will be required to pay USD 30.00/oz. to the bank to reflect the movement in the gold price. The forward leg of the swap reestablishes the economics of the original transaction in that the customer now has a commitment to deliver the gold in six months’ time at a fixed price of USD 1,343/oz.

4.4.2

Swaps

The use of word ‘swap’ without any qualification in the gold market should be treated with caution as it could have several meanings. Conventional commodity swaps are possible in the gold market and these comprise of cash-settled, Asian-style, fixed for floating structures. A structured swap would typically include some form of embedded optionality that results in a payoff that is initially more favourable than the vanilla equivalent. However, if the optionality is exercised then the participant is faced with a payout that is less favourable. 4.4.2.1

Locational and quality swaps

Two types of swaps that are perhaps unique to the gold market are quality and locational swaps. When reference is made to ‘the’ gold price then it can usually be taken to mean the ‘loco London’ price. Other loco prices are possible such as Zurich or areas with common transport and warehousing facilities (e.g. Tokyo, Shanghai) as well as where the refineries are based. For example, as I type this text, the price of gold loco London is USD 1,341, loco Zurich USD 1,342, and loco New York USD 1,340. Suppose that a US mining company wishes to swap 50,000 ounces of its physical American gold holdings for a similar position in London. It contacts its custodian bank

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and arranges a locational swap. Typically, these are booked as two separate transactions. From the client’s perspective they are executing the two following transactions: Sell 50,000 oz. gold at USD 1,340 loco New York Buy 50,000 oz. gold at USD 1,341 loco London The client must pay to the bank the difference in USD between the two loco prices, which in this case will be USD 50,000. On the sale leg, the mining company’s metal account in New York is debited with the offsetting credit to the New York gold account of the transacting bank. On the purchase leg, the transacting bank debits its London metal account for 50,000 oz. and credits the mining company’s London metal account for the same amount. In this way the mining company that now owns metal in London does not actually have to arrange for the metal to be shipped. A quality swap would work in a similar fashion. In the loco swap example, it was assumed that the qualities of the two metals were equal. A quality swap would be where one party owns gold of a given purity, but has a commitment to deliver gold of an alternative quality. Rather than have to pay for the metal to be refined into the necessary grade it may be possible to enter into a swap transaction where ownership of gold is transferred with a settlement in USD to reflect any price differential. 4.4.2.2

American barrier reset swap

A possible term sheet is presented below: Fixed price payer: Floating price payer: Fixed price: Floating price: Reset event:

Trigger level: Reset fixed price: Settlement frequency: Comparable vanilla swap level:

Client Bank USD 1,250, subject to a reset event Unweighted arithmetic mean based on the daily AM LBMA gold price over each month. If the LBMA gold price settles at or above the trigger level, the fixed price for the current month is set to the reset fixed price. USD 1,400 USD 1,400 Monthly USD 1,300

The structure is illustrated in Figure 4.9. The consumer buys physical gold monthly from their usual supplier and for ease of illustration assume the commercial contract also references the LBMA gold price. As is common with many commodities contracts, the agreed price will be based on the concept of ‘average of the month’ prices. This means that the consumer is protected

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Gold

Floating price Client

Bank Fixed price (subject to reset)

Floating price

Physical gold

FIGURE 4.9 Structure of American barrier reset.

from a sudden upward spike in prices. By the same token they cannot benefit from a sharp fall in prices. The main purpose of the swap is to transform the floating price exposure of the physical supply contract into a fixed price, but the advantage of this structure is that the fixed price is initially lower than the vanilla equivalent. If the price of gold increases beyond the trigger level of USD 1,400 then the fixed price payable by the client increases to this level, which is now higher than the vanilla equivalent. The reduction in the fixed price is achieved by the fact that the client has sold a strip of options. The premium receivable on this option is not paid in cash but is instead used to subsidise the lower fixed rate. The seller of an option is normally faced with open-ended losses but note that in this case that if the option is exercised then the client will end up paying a fixed amount of USD 100.00 more than the vanilla equivalent. This would suggest that the embedded strip of options is a series of digital call options. The ‘barrier’ is actually the strike and the option is American in style and so can be exercised at any time. In this structure the first of the embedded options is a spot starting one-month option with a strike of USD 1,400. The remaining options have the same characteristics (e.g. one-month maturity, pre-agreed strike of USD 1,400 and a fixed payout of USD 100.00), except they are all delayed start instruments. If the optionality is exercised in one month, the higher fixed rate will only apply for this single period. At the start of the next period, the client will pay the advantageous fixed rate unless the gold price has increased beyond the threshold. 4.4.2.3

American barrier knock out swap

This swap is also structured to offer an improved fixed price to the customer subject to a trigger event. We will assume the same context as the previous example. A term sheet may look as follows:

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Fixed price payer: Floating price payer: Fixed price: Floating price:

Client Bank USD 1,200, subject to a reset event Unweighted arithmetic mean based on the daily AM LBMA gold price over each month. Knock out event: If the LBMA gold price settles at or above the trigger level, the swap knocks out and payments cease. Trigger level: USD 1,400 Settlement frequency: Monthly Comparable vanilla swap level: USD 1,300 In this structure the client initially pays a fixed price of USD 1,200, which is below the vanilla equivalent. If the price of gold increases beyond the trigger price, then the remaining portion of the swap terminates, leaving the consumer unhedged in a higher price environment. Since the swap can be terminated at any time that the gold price hits the barrier then it is an American-style structure. Once again, the client is initially enjoying a subsidised fixed price, which suggests they are selling some form of optionality. Since the swap will terminate if the option is activated, this means the client has sold an option on a swap, i.e. a swaption. This option will require the client to enter a second swap with terms equal but opposite to those of the initial swap. Suppose that the gold price hits USD 1,400 at the end of the first month triggering the embedded option. The client will then be required to receive fixed/pay floating on an offsetting swap with 11 months remaining, but with the same terms as the initial swap. This means that both the fixed and floating cash flows will cancel out. However, rather than require the client to hold two positions that are perfectly offsetting, the bank will simply agree to terminate the structure leaving the client unhedged.

4.4.3

Options

In addition to using forward based strategies, gold producers can hedge their production using options. 4.4.3.1

Vanilla put options

The simplest structure for a producer is to buy a put option. This gives them the right but not the obligation to sell a pre-agreed amount of gold to the bank at some future date at a price agreed today. Let us assume that the producer decides to buy a six-month put at a strike price of USD 1,300 per ounce with the current forward market at USD 1,306. This option is out-of-the-money as the strike price is less favourable than the underlying forward market. Since the producer has bought a European-style option that can only be exercised upon maturity, the underlying is the forward rather than the spot market.

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The put option will give the producer protection if the market falls below this strike level, but will allow them to walk away from the contract if the price of gold rises. A common misconception concerning this strategy is that it would be appropriate if the producer expected the price of gold to fall. If the producer held this view, it would be cheaper for them to sell the gold forward particularly if the market were in contango. The purchase of a put would be appropriate if the producer felt the price of gold were to rise, but wanted insurance in case their view of the market was wrong. Although the purchase of a put option is a simple strategy, it is often unpopular due to the premium cost. With implied volatilities for gold often close to 20% (for short-term options) the premium on a substantial production target could be relatively high. For example, pricing a six-month option with a strike of USD 1,300, a forward price of USD 1,306, and an implied volatility of 20% would return a theoretical fair value of USD 70.00 per ounce. This represents about 5% of the current spot price, which on a position of, say, 50,000 ounces would represent a substantial upfront cash flow (USD 3.5 million). 4.4.3.2

Asian style put option

One of the popular approaches to the issue of hedging is to offer options with lower premiums. The first alternative would be to offer the producer an average rate option (sometimes referred to as ‘Asian’ options). These are options that settle against the average price of the asset during the option’s lifetime. These can provide an effective hedge for consumers or producers who buy or sell the physical metal on commercial contracts that reference some form of averaging process. A typical term sheet from a producer’s perspective may look as follows: Volume: Option type: Strike: Settlement: Maturity: Payoff: Averaging:

50,000 oz. Put option USD 1,300 (ATM spot) Cash-settled Six months At maturity, (i) if XAU average < Strike price client receives Strike – XAU average (ii) otherwise no payoff will take place. XAU average is the average of the daily AM LBMA gold price over the averaging period.

Asian-style options will always be less expensive than the non-averaging equivalent. The volatility input is still referencing the underlying. However in this instance, it is not the outright price but an average price over some pre-agreed period. As a result, the volatility of an average price series is lower than that of just the outright price. Using an implied volatility of, say, 15% rather than the 20% used in the previous

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example and an averaging period equal to the option’s maturity (i.e. six months) the premium returned is USD 28.59. It is tempting to claim that this is ‘cheaper’ than the non-averaging equivalent, but this may be misleading use of the terminology. ‘Cheapness’ is more commonly used to denote options that are undervalued relative to some notion of ‘fair value’. In cash flow terms it will cost less than a European-style option, but since its payout references the average of a time series, the payout will also be lower. As the averaging period falls, the value of the option will increase; taken to the extreme an averaging period of one day will make it indistinguishable from a European option and will therefore cost the same. 4.4.3.3

Barrier options

A barrier option is a structure where the payout depends on whether the underlying price crosses or reaches a defined barrier level. Knock-in options start their lives worthless and only become active in the event a predetermined knock in barrier price is breached. Knock-out options start their lives active and become null and void in the event a certain knock-out barrier price is breached. Volume: Option type: Strike: Settlement: Maturity: Knock out barrier: Payoff:

Premium:

50,000 oz. Knock out put option (‘up and out’) USD 1,300 (ATM spot) Cash-settled Six months USD 1,350 At maturity, (i) if spot gold has never traded above the knock-out barrier during the life of the contract, the client receives MAX (Strike – XAU final, 0) on the settlement date. (ii) Otherwise no payoff will take place. XAU final = the LBMA gold price on the expiration of the contract. USD 35.03

From the producer’s perspective they are most concerned about the possibility of falling prices. If prices were to rise through the barrier, they may feel comfortable with the termination of the option. It will leave them unhedged if the price of the underlying asset were then to fall. As was suggested in section 1.8.2 the main motivation for using barrier options is that the premium is less than the European equivalent. Compared to the vanilla put option, the premium has fallen by 50%. If the producer asked for the barrier to be moved closer to the current spot price (say USD 1,330) the premium on the option would fall as the option is more likely to be terminated. This reduces the probability that the option will be exercised and as such reduces the cost. If the barrier is moved further away from the spot price, the option will increase in value. There is less chance of the option being terminated and so the position more closely resembles that of a vanilla equivalent. Another alternative would be a ‘down and in’ put option.

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Volume: Option type: Strike: Settlement: Maturity: Knock in barrier: Payoff:

Premium:

50,000 oz. Knock-in put option (‘down and in’) USD 1,300 (ATM spot) Cash-settled Six months USD 1,250 At maturity, (i) if spot gold has traded below the knock-in barrier during the life of the contract, the client receives MAX (Strike – XAU final, 0) on the settlement date. (ii) Otherwise no payoff will take place. XAU final = the LBMA gold price on the expiration of the contract. USD 66.70

Here the producer has downside protection, but only once the option is activated upon spot trading through the USD 1,250 barrier. At that point, the producer has the right to sell at a price that is USD 50.00 higher. This means that the option is ‘born’ with USD 50.00 of intrinsic value. The premium is lower than the vanilla equivalent but is higher than the knock-out variant.

4.4.3.4

Two-asset barrier options

Consider a scenario where a gold producer also mines copper as a by-product. The producer may also seek to hedge this additional production and could feasibly use options in a similar manner to those outlined above. However, the cost of hedging this secondary production could be managed using a two-asset barrier option. This type of option links the payoff on the copper component to the price of gold. It may be reasonable to suggest that the producer would only need protection against adverse copper price movements when gold prices are low. A hypothetical term sheet for this type of option may look as follows:

Option type: Spot price of copper: Spot price of gold: Copper strike price: Gold knock in barrier: Settlement: Maturity: Payoff:

Premium:

Two asset knock-in put option (‘down and in’) USD 7,100 USD 1,300 USD 7,100 (ATM spot) USD 1,000 Cash-settled Six months At maturity, (i) if spot gold has traded below the knock-in barrier during the life of the contract, the client receives MAX (Copper strike price − Cu final, 0) on the settlement date. (ii) Otherwise no payoff will take place Cu final = the London Metal Exchange cash price for copper on the expiration of the contract. USD 52.83 (Vanilla six-month copper put option USD 562)

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TABLE 4.3 Relationship between option premium and correlation for a two-asset barrier option. Correlation input +1.0 0.0 −1.0

Option premium (USD) 93.35 52.83 0.01

If the prices of copper and gold are positively correlated then as the price of gold falls below the USD 1,000 barrier then the right for the producer to sell copper at the strike will be activated; the positive correlation in prices would make it likely that the put option would now be ITM. Compared to a vanilla copper put option this structure represents a major reduction of the premium. This is because the pricing of this type of option includes a component to reflect the correlation between the two underlying prices. All other things being equal, the relationship between the premium and the price correlation is positive (Table 4.3). If the two prices exhibit positive correlation, then a fall in gold prices is likely to be associated with a fall in copper prices. This increases the likelihood that the option will expire ITM. Negative correlation of prices returns a very low premium value. This relationship would suggest that high gold prices are associated with low copper prices. Therefore, the barrier is less likely to be activated as a result, but the activation barrier is less likely to be hit, so the option will expire OTM. Conversely, low gold prices would be associated with high copper prices and so although the option may activate the right to sell at price lower than the market would be of no value.

4.5 4.5.1

TRADING GOLD Gold swaps / FX swaps

Although there are several generic trading strategies a gold trader can execute (e.g. trading option volatility), this section focuses on those strategies that are perhaps somewhat specific to the gold market. Section 4.3.1. illustrated how a fair forward price could be derived using time value of money principles and introduced the concept of the gold swap rates. Within the context of forward markets, it is important to make a distinction between outrights and swaps. An outright forward is a single transaction where a given quantity of gold is to be delivered at a fixed date beyond spot value for a pre-agreed fixed price. A producer could use a single outright forward sale of gold as a way of achieving cash flow certainty. The rationale for a gold swap is much less intuitive although readers with a background in foreign exchange may be familiar with the instrument; indeed, some market participants do refer to them as ‘FX swaps’. A gold swap consists of a spot and forward transaction that are executed simultaneously. The following example shown in Table 4.4 illustrates the principles, based on a two-month transaction expressed from the perspective of a market maker.

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TABLE 4.4 Gold swaps.

Spot price Swap % Outright price Trader’s actions (market maker’s perspective) Interpretation

Bid

Offer

1,330.65 1.73% 1,334.42 Sell gold for spot value Buy gold for two-month forward value Trader lends gold, borrows USD

1,330.83 1.83% 1,334.82 Buy gold for spot value Sell gold for two-month forward value Trader borrows gold, lends USD

Suppose a market maker executes a trade at their bid price. Typically, these trades may base the spot value of the transaction on the mid-market spot price, but here the example will use the bid price. For ease of illustration the example is based on a single ounce.

Gold component Cash component

Spot date

Forward date

Bank delivers one oz. of gold Bank receives 1,330.65

Bank receives bank one oz. of gold Bank repays 1,334.42

When looked at vertically (i.e. thinking of the transaction as a combination of a spot and forward deal), the rationale for the swap is not obvious. Arguably the better way to view the transaction is to look at it horizontally. Looking at the cash component, the bank has taken in USD and then repaid it two months later; economically this is nothing more than a USD borrowing. Looking at the gold element of the transaction the trader has lent gold for the period. Combining the two suggests that the transaction could be viewed as nothing more than a USD borrowing collateralised with gold. However, it does beg the question as to why the trader did not simply borrow USD on an uncollateralised basis. Although borrowing on an unsecured basis in the money markets is possible, logic dictates that borrowing on a collateralised basis should be cheaper. Indeed, for some participants whose credit rating is considered questionable, this may be the only way in which they can borrow. Viewing the transaction as a collateralised loan allows us to reinterpret the swap rates. At the bid price the percentage difference between the incoming dollars and the amount repaid represents a borrowing cost of 1.73% p.a. At the bid price the trader is lending gold and borrowing USD at a net cost of 1.73% p.a. At the offer price the trader is borrowing gold and therefore lending dollars on which they would expect to earn 1.83% p.a. net. Although this analysis conveys one rationale for using gold swaps, it is possible for anomalies to arise. In the section on leasing it was highlighted that the swap points represented the percentage difference between spot and forward prices. The two factors

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that determined this differential were LIBOR rates and lease rates. It was also pointed out that the market often inferred the lease rates by subtracting the swap rate from the prevailing LIBOR rate (‘LIBOR minus GOFO’). Equation (4.3) showed that the swap rate is calculated as LIBOR minus the lease rate. So, if the lease rate is positive, the collateralised cost of borrowing (i.e. the swap rate) is less than the unsecured equivalent. Using the figures in the above table, suppose the appropriate value for two-month LIBOR was 1.63% implying a lease rate of −0.10%. This suggests that if you were to borrow some gold you would be paid to do so! However, one possible explanation for this can be seen in the FX market and is referred to as the FX basis. Suppose that if a bank were to borrow in the unsecured LIBOR market it would be required to pay a margin over the benchmark LIBOR rate because of credit concerns. The trader decides to use the gold market to raise collateralised funds knowing that her borrowing cost will be lower. If there were sufficient demand for this type of USD borrowing, then the amount of USD that counterparties will demand to be repaid in the forward leg will increase. If the observed LIBOR and the spot rate are assumed to be unchanged, the increase in the forward price will be associated with a lower implied lease rate. If the demand to borrow USD is sufficiently high, then eventually the implied lease rate will turn negative. A simple example will illustrate based on the following market conditions: ▪ ▪ ▪ ▪ ▪ ▪

Tenor: 12 months. Spot price: USD 1,300. 12-month LIBOR: 3%. 12-month lease rate: 0.10%. Day basis: Actual/Actual. Implied 12-month forward price: USD 1,337.70.

Based on the above figures the 12-month net borrowing cost is 2.90%, which will also be the swap rate. Suppose now that there is an instantaneous increase in demand to borrow USD using gold as collateral. Traders will react to this demand by increasing the cash amount that must be repaid at maturity. Assume that the swap rate is now quoted as 3.46% implying a forward price of USD 1,345. Assuming that the spot rate and 12-month LIBOR are unchanged then the implied lease rate is −0.46% (3%–3.46%). So according to this approach no one is being paid to borrow gold, but rather a borrower of USD is having to pay LIBOR + 0.46% (i.e. the swap rate of 3.46%) more than the unsecured rate to borrow on a collateralised basis. Why would they do this? It would suggest that they are unable to borrow at LIBOR and the rate of interest to borrow USD offered by the gold swap is their best option.

4.5.2

Non-deliverable gold swaps

Non-deliverable forwards (NDFs) are well established in the foreign exchange market and a similar product exists within the gold market. In an FX context, NDFs can be used either as hedging or trading tools for situations where a market participant may either be unwilling or unable to take delivery of a particular currency. As an example,

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in a USDKRW contract at settlement then logically there should be an exchange of US dollars against Korean Won. However, if this is done as a NDF then rather than there being an exchange of cash flows, there is a single cash flow settlement in USD. In the gold market these may also be referred to as ‘cash-settled swaps’ or ‘bullet swaps’. Suppose a hedge fund client who does not wish to take physical delivery of the metal agrees to a gold NDF for an amount of 10,000 ounces and is quoted a six-month forward rate of USD 1,343. The value of the contract is therefore USD 13,430,000 vs. 10,000 oz. of gold. The trader’s view is that the spot price of gold will not evolve as per the forward rate, and at maturity will be less than the contract value. Gold (XAU to use its currency code) is referred to as the reference currency, while the USD leg is the settlement currency. The contract will be settled in USD at its maturity in six months based on the spot value (‘settlement rate’) of gold at the time. The hedge fund trader is designated to be the reference currency buyer. The relevant settlement formula is: USD notional amount × (1 − Forward rate∕settlement rate) Suppose that in six months’ time the settlement rate is USD 1,320, then the settlement amount is: USD 13,430,000 × (1 − 1, 343∕1, 320) = −USD 234,007.58 If the settlement amount is a positive number the reference currency buyer will pay that amount in the settlement currency to the currency seller or if the settlement amount is a negative number the reference currency seller will pay the absolute value of that amount in the settlement currency to the reference currency buyer. In this case the hedge fund trader profits as the rate moved as expected.

4.5.3

Deferred margin accounts

Deferred margin accounts are a type of derivative transaction in which a client can express views on how the gold price is expected to evolve. The accounts work on a leveraged basis but do not confer any rights of ownership on the physical metal. Suppose a client wishes to take a bullish view on the evolution of the gold price and agrees to a contract size of 10,000 oz. with the offering bank. The current gold price is USD 1,300/oz. which implies an initial account balance of USD 13,000,000. However, the client only partly finances this exposure and agrees to lodge an initial deposit of 8% (USD 1,040,000) with the bank. The bank finances the balance of the required proceeds (USD 11,960,000). The client is then allowed to make purchases or sales of the metal if the following relationship is maintained: Market value of metal − initial account balance + initial margin > 8% ∗ MAX (market value of metal, initial account balance)

(4.5)

The initial values are: USD 13 m − USD 13 m + USD 1,040,000 = 8% ∗ MAX (USD 13 m, USD 13 m)

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i.e. the equation is in balance. These products are designed in such a way that the bank minimises its credit risk, as typically they do not have any recourse back to the client. To illustrate how this relationship works assume that shortly after the contract is executed the price of gold falls to USD 1,250. The left-hand side of equation 4.5 is therefore: USD 12,500,000 − USD 13,000,000 + USD 1,040,000 = USD 540,000 The right-hand side of the equation is: 8% ∗ MAX (USD 12, 500,000, USD 13,000,000) = USD 1,040,000 Since the price of gold has fallen then the client will have incurred a loss of USD 500,000 (10,000 oz. x USD 50.00), and so their initial margin will have fallen in value. The amount lent by the bank is still intact as the position could be unwound and the bank’s principal would be repaid in full. In this case, the bank would require the client to replenish the margin account such that the 8% threshold is maintained. Some banks may impose a second threshold (e.g. 5%) below which the transaction would be automatically unwound. This would protect the bank in the event of volatile price moves. If the price of gold were to rise to USD 1,350, then the relationship in equation (4.5) becomes: USD 13,500,000 − USD 13,000,000 + USD 1,040,000 = USD 1,540,000 Implying a profit of USD 500,000 However, the right-hand side of the equation is now 8% ∗ MAX (13,500,000, USD 13,000,000) = USD 1,080,000 Although the client would have to deposit some more margin, he would be allowed to withdraw the ‘intrinsic value’ of the position, which is USD 460,000 (USD 1,540,000 − USD 1,080,000). In this example the initial margin is retained in the account. He is not able to withdraw any of the bank’s initial funding of the position and has no rights over any physical gold. From the offering bank’s perspective, they are exposed to a fall in the price of gold. One of the ways in which they could hedge themselves is to sell gold futures. At the time of writing, the contract specification for the gold future on the CME exchange is for 100 troy ounces. The bank could therefore sell 100 futures as a possible hedge and use the client’s margin to finance the exchange’s initial margin. This is not a perfect hedge, though as the client’s margin account is referencing the spot price, the hedge will reference a futures price. This leaves the bank exposed to movements in the ‘carry’ component of the future (i.e. LIBOR and lease rates).

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4.6

YIELD ENHANCEMENT

Although central banks have had something of a love-hate relationship with gold, it is still a fact that they hold considerable amounts of the metal. Since the metal does not have any intrinsic source of income such as a dividend or a coupon, banks may seek to earn a return on them by either leasing a portion of them to the market or executing a variety of strategies to enhance the yield. Lease rates are generally very low and below interbank rates such as LIBOR. As such, in a rising interest rate environment, it is tempting to suggest that banks should simply sell off their holdings for cash and invest the proceeds! One popular yield enhanced strategy involves selling a call option on a proportion of the existing inventory of metal. This is commonly referred to as a ‘covered call strategy’. The sale of the call option will require the seller to deliver the underlying metal if exercised. If the call is not exercised the central bank will simply collect the premium and enjoy an enhanced return. A common misconception is that selling options while holding the underlying asset is risk free. A simple example will demonstrate that this is not the case. Assume that the central bank decides to sell a 12-month call option based on a portion of their physical holdings. We will assume that the current spot price is USD 1,300 per ounce; the three-month forward price is USD 1,303 and implied volatility at 20%. Using a simple option-pricing model the premium on an OTM European-style option with a strike at USD 1,400 is USD 18.35 per ounce. Figure 4.10 illustrates the concept with the analysis on a per ounce basis. The vertical axis is defined as the value of the overall position in USD, while the horizontal axis represents the current spot price of gold. The physical holding of gold is shown as a 45-degree line bisecting the horizontal axis at the current spot rate. This position suggests that as the spot price of gold rises so does the value of the underlying holding. The sale of the call option is shown with an ‘at expiry’ payoff and the net position of the two transactions is also highlighted. As the price of gold falls in the spot market, the value of the net position declines, but the loss is offset by the income received on the option. Although the premium provides a cushion for losses on the underlying holding, the overall position will show a loss. If the price of gold were to fall, the net position starts to lose money beyond a spot price of USD 1,281.65 (USD 1,300 − USD 18.35) so it is clearly not risk free. This is the point where the cushion of the USD 18.35 received as a premium is eroded. However, the central bank is still in a relatively better position than simply holding the metal. The maximum value of the position is realised at a spot price equal to or greater than the strike of the sold call option. Beyond this position the central bank loses on the call but profits from the increased value of the physical gold. The net effect is that the profits are maximised beyond this point. If the call is exercised against the central bank, they do not need to deliver the metal and can choose to settle their obligations in cash. Figure 4.10 shows that beyond USD 1,418.35 (USD 1,400 + USD 18.35), the returns from holding just the physical gold would exceed that of the combined strategy. This is a point where the call option breaks even and is equal to the strike plus the premium. When considering the appropriateness of the strategy, the central bank must believe that the price of gold will only rise by a relatively small amount.

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15,000,000 Long gold position 10,000,000

Profit / Loss

Net exposure Sale of OTM call

5,000,000

U/L Price 1,526.4000

1,507.5000

1,488.6000

1,469.7000

1,450.8000

1,431.9000

1,413.0000

1,394.1000

1,375.2000

1,356.3000

1,337.4000

1,318.5000

1,299.6000

1,280.7000

1,261.8000

1,242.9000

1,224.0000

1,205.1000

1,186.2000

-5,000,000

1,167.3000

0

-10,000,000

FIGURE 4.10 Covered call strategy.

From this analysis there are a few extra points of note: ▪ The bank could move the strike of the sold call option closer to the current underlying price. This would increase the premium of the option but also mean there is a greater risk that the option will be exercised. ▪ The option was valued at an implied volatility of 20% with no reference to the state of the skew. If the relationship between implied volatility and the strike resembled a smile (e.g. Figure 2.7), then the position would be revalued using a higher implied volatility, which would increase the premium. ▪ If the term structure of implied volatility for gold is upward sloping, then all other things being equal, the bank would earn a higher premium if they were to trade a longer-dated option.

4.7

SUMMARY ‘(one) feature that sets gold apart from other commodities and currencies is the role that sentiment plays. Clearly it is important in all markets – the ability of traders to ignore bad news and focus only on positive features that reinforce an already-held view. However, in gold, this is taken to new levels. Why should a piece of metal be a hedge against inflation? Why should it be seen as a store of value? Is it desirable because it represents no one else’s debt? But then again, the same is true for a lump of coal. The reason that gold has these attributes is that we believe that it does. It has been embedded in human psychology and reinforced over the millennia.’ —Spall (2010)

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The key points from this chapter are: ▪ Gold traded on wholesale markets will conform to a set of agreed standards with ‘London Good Delivery’ bars being one example. ▪ The gold price moves on a constant basis although a twice daily auction formerly referred to as the ‘fixing’ establishes a benchmark value to aid transaction settlement. ▪ There has been a shift in production away from the locations traditionally associated with gold (such as South Africa) to Asia (e.g. China). ▪ Central banks moved from being net sellers to net buyers as the price of gold increased. ▪ Although the price of gold has been characterised as having strong price relationships with the US dollar and inflation, arguably a more compelling relationship exists between the metal and real yields. ▪ The significant amount of metal held above ground, and the fact that most of the gold ever mined is still in existence, has given rise to a leasing market. ▪ Given gold’s history as part of the monetary system it shares many similarities with the currency markets. ▪ Some of the more unique swap products traded by the market include location and quality swaps. ▪ Options on gold range from the vanilla to the exotic.

CHAPTER

5

Base Metals

5.1

OVERVIEW OF BASE METAL PRODUCTION

Typically, the mining process will begin with a geological survey of an area including test drilling to determine the size of the deposit, its depth, and quality. From this a decision will be made as to whether or not the value of the deposit will be greater than the cost to develop and operate the mine. This decision will consider several factors, some of which may not be purely geological. These other considerations will include mining infrastructure issues such as where to put the buildings or roads and will likely include any related environmental issues. Lead times between the actual discovery and production can take many years and may often involve a substantial initial outlay. Many banks wishing to lend to mining operations may often link the debt repayments to the revenues generated and may involve some form of hedge to lock in future cash flows. About 80% of all elements found in the earth are metal. However, they rarely occur in a commonly recognisable form as they react to combine with other elements to create compounds. As a result, the production process will involve separating the metal from the individual components with which it has bonded. Different metals will react with other elements to varying extents. Silver and gold are very unreactive and do not readily combine with any other element, and so are found in their pure state. At the other extreme it is impossible to find francium in its pure form, as it will immediately react with oxygen or water when exposed to the atmosphere. Metals commonly occur in the form of compounds or ores where they are chemically bound to one or more elements. For example, the metal sodium is commonly found as sodium chloride; sodium has bonded to chlorine. To produce and transform the metals into a usable form the ore has to be separated from the host rock. The process to remove the host rock is similar regardless of the type of metal concerned; the rock and ore are ground down to a powder and are then separated mechanically. The next stage in the production process involves the separation of the metal from the compound. Breaking down the ore to form pure metal can be carried out by a number of different processes. The more reactive a metal is the harder it is to remove from its ore and the more expensive the process. Several metal ores are broken down using the addition of carbon and/or oxygen. Ores of very reactive metals have to be melted down (smelted) and the metal removed by electrolysis. Refining is the final stage of the production process where impurities are removed, and the metal is transformed into a state that would allow fabrication of an end product.

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5.2 5.2.1

115

THE COPPER LIFECYCLE1 Copper resources

Copper occurs naturally in the Earth’s crust in a variety of forms, and can be mined in different ways such as surface or underground operations. Mine production in 2016 was approximately 20 million tonnes, although overall production capacity was 10% higher. One question that is commonly asked about many scarce commodities is ‘how much is left?’ It is acknowledged that richer, low cost, long life ore bodies have already been developed and are deteriorating quickly. Typically, the future availability of minerals is based on the concept of reserves and resources. According to the International Copper Study Group (ICSG, 2017) ‘Reserves are deposits that have been discovered, evaluated and assessed to be economically profitable to mine. Resources are far bigger and include reserves, discovered deposits that are potentially profitable, and undiscovered deposits that are predicted based on preliminary geological surveys.’ The ICSG estimates that for 2016 ‘total copper resources’ amounted to 5,600 million tonnes. However, this is broken down into two main categories: undiscovered and identified resources. Undiscovered resources are classified as those who ‘the existence of which are only postulated’ and were estimated at 3,500 million tonnes. Identified resources are defined as ‘resources whose location, grade, quality and quantity are known or estimated from specific geological evidence. Identified resources include economic, marginally economic and sub-economic components’. For 2016 these were estimated at 2,100 million tonnes. Within the identified resources estimate sits copper ‘reserves’, which were estimated at about 720 million tonnes; reserves are: ‘That part of the reserve base which could be economically extracted or produced at the time of determination’. These reserves are determined so that they meet ‘specified minimum physical and chemical criteria related to current mining and production practices’. The question that follows is whether it is likely that the world will run out of copper. Although copper is a finite resource, the level of reserves at any time usually tends to be sufficient to meet about 40 years of demand. This can be explained by a number of factors: ▪ As demand increases the price of the metal will rise meaning it will be more economical to extract marginal sources. Essentially, more ‘resources’ will become classified as ‘reserves’. ▪ Mining technology improves and so the estimates of resources and reserves evolve over time. ▪ Copper is an example of a transformable rather than consumable metal and so can be recycled repeatedly without any loss of performance. ▪ Innovation will change the way in which the metal can be used perhaps resulting in economies. 1

Unless otherwise stated the data in this section was taken from The World Copper Factbook 2017 by the International Copper Study Group.

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5.2.2

Uses of copper

The main applications of copper include: ▪ Electrical – power cables, appliances. ▪ Electronics and communications – data transmission, computer chips. ▪ Construction – external and internal applications (e.g. plumbing and window frames). ▪ Transportation – motors, wiring, electric vehicles. ▪ Industrial machinery – gears, bearings, turbine blades. ▪ Other – coins, cookware, art.

5.2.3

The copper supply chain

A simplified overview of the supply chain for copper is presented in Figure 5.1. As with many commodity supply chains some companies may be fully integrated or may just offer a specific service. The starting point to produce ‘primary’ copper is the mining of ore. This is the solid material from which the metal can be extracted. The top five countries producing copper are in descending order are: ▪ ▪ ▪ ▪ ▪

Chile Peru China United States Australia

The next step is to crush and grind the ore in order to remove all of the unwanted rocky material. This is referred to as ‘concentrate’, which is comprised of several different elements typically 1/3 copper, 1/3 sulfur, and 1/3 iron silicate. It is possible for the copper content at this stage to range between about 20–40%. The concentrate is sent to a smelter, which transforms the material into ‘matte’ where the copper content will increase to 50–70%. The top five countries smelting copper are in descending order: Alloy Alloy metals ingots Concentrate Matte

Ore

Mine

Blister Anode

Wire Bars Wire Rods

Cathodes

Smelter

Refinery

Semi fabricator

Manufacturer

Scrap

Scrap

New scrap

New scrap

FIGURE 5.1 Copper supply chain.

End of life management

Old scrap

Base Metals

▪ ▪ ▪ ▪ ▪

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China Japan Chile Russian Federation India

The matte is then processed to produce ‘blister’ where the copper content is 98.5–99.5%. The blister is further refined and cast into anodes before the final refining stage, which produces copper cathodes. A cathode is a 5–80 kg copper square and is one of the main raw material inputs for ‘semi’ fabricators. Other refinery shapes may include wire bars, ingots, billet slabs, and ‘cake’. The top five countries producing refined copper are in descending order: ▪ ▪ ▪ ▪ ▪

China Chile Japan United States Russian Federation

Semi fabricators (‘semis’) convert the metal into several products and shapes such as wire rod, tubes, and strips that can be used in the end manufacture of a specific product. This part of the supply chain covers a wide variety of different entities such as wire rod plants and brass mills. Brass is a mix of metals, referred to as an alloy, which is comprised of copper and zinc. The top five countries producing refined copper are in descending order: ▪ ▪ ▪ ▪ ▪

China United States Germany Japan Korean Republic

5.2.4

The role of scrap copper

The copper market distinguishes between ‘new’ and ‘old’ scrap metal. New scrap copper is excess copper that is not incorporated into a final manufactured product. It is metal that has been discarded as part of the fabrication or manufacturing process. ‘Old scrap’ is metal that has been recovered from a manufactured product that has reached the end of its life. This metal can then be re-introduced back into the supply chain. Indeed, refined copper that has been made from scrap sources is termed ‘secondary copper production’.

5.2.5

Trading copper

In looking at the different elements of the supply chain, it becomes clear that where copper is mined, smelted, refined, and fabricated could take place in many different geographical locations and be performed by different market participants. The ICSG argues that the major product categories traded internationally include:

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Concentrates, Blister and anode, Cathode and ingots, Scrap, Semis.

Typically concentrates and refined copper are the most imported and exported elements. In terms of the major trade flows of ores and concentrates (basically from mining company to smelter) the major exporters are: ▪ Chile ▪ Peru ▪ Indonesia The major importers are: ▪ China ▪ Japan ▪ Spain In terms of blister and anodes (i.e. smelter to refiner) the major exporters are: ▪ Chile ▪ Bulgaria ▪ Namibia Whereas the main importers are: ▪ China ▪ Belgium ▪ India The main trade flows for refined copper (i.e. refinery to semis) include the following main exporters: ▪ Chile ▪ Japan ▪ Russian Federation While the main importers are: ▪ China ▪ Germany ▪ United States

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In terms of semi-fabricated copper products, the main exporters are: ▪ Germany ▪ Taiwan ▪ China While the main importers are: ▪ China ▪ United States ▪ Italy

5.3

ALUMINIUM

More aluminium is produced today than any other non-ferrous metal, with more than 60 million tonnes produced each year. The prospects for the metal are generally regarded as favourable as the demand for lighter, more durable, energy efficient, and recyclable goods increase. The starting point for the production of aluminium is bauxite. Once mined it is crushed and dissolved in caustic soda at high temperatures and pressures. The solution contains dissolved aluminium ore, which can be separated from any un-dissolved impurities, as they will have sunk to the bottom of the collection tank. Aluminium ore is chemically referred as aluminium oxide (Al2 O3 ), but is perhaps most commonly referred to as alumina2 and exists in the form of a white powder. The alumina is dissolved into a molten solution capable of conducting electricity. Two electrodes are then attached, one positive and one negative, and the aluminium is extracted by electrolysis. Electrolysis uses electricity to separate the metal from its ore. As the electricity passes through the molten solution, the aluminium is attracted to the negative electrode and can be siphoned off to yield very pure aluminium. This entire extraction process is energy intensive and as a result the cost of electricity will have a substantial impact on production costs. Four tonnes of bauxite yields about two tonnes of alumina, which yields one tonne of aluminium. Another important component of supply is the amount that is recycled. One of the big advantages of producing aluminium via recycling is that the process consumes considerably less electricity than primary production. The refining of aluminium is renowned for consuming considerable amounts of electricity, which can account for about 40% of production costs. It also explains why some smelters have chosen to locate themselves in areas of relatively cheap energy costs such as Iceland. Recycling aluminium requires about 5% of the energy needed to make it from alumina. 2

As a rule of thumb alumina has traditionally been sold on a long-term contract basis with the price being set at 12–14% of the price of aluminium.

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The largest producer (measured as smelting output) of aluminium is China followed by the Gulf region and then North America and Western Europe. The largest user of the metal is the transport sector, which accounts for about a third of demand. A significant proportion of this is in the automotive industry for such things as engine blocks and body panels. This would suggest that a downturn in demand in this sector would have a significant impact on the demand for the metal. Construction is the second largest user of the metal (25%) with packaging constituting a significant proportion (16%).

5.4

THE STEEL MARKET3

By way of contrast to the copper market, steel is not a commodity that exists naturally in the ground. Steel is an alloy of iron and carbon and contains small amounts of other elements such as manganese and silicon. Iron ore is first reduced to form molten iron, sometimes referred to as ‘pig’ iron. This molten iron is then transferred to a basic oxygen furnace (BOF; about 72% of all production) where it is combined with a proportion of scrap steel and once various impurities are removed, the resulting product is molten steel. Alternatively, it is also possible to produce steel in an electric arc furnace (EAF; about 28% of all production). Arguably, the key differences between the processes relates to the production inputs. The EAF process tends to use a greater proportion of steel scrap. Steel can be infinitely recycled without loss of quality. To produce 1,000 kg of crude steel using the BOF technique, the main required inputs are: ▪ ▪ ▪ ▪

1,370 kg of iron ore, 780 kg of coal, 270 kg of limestone, 125 kg of steel scrap. To produce 1,000 kg of crude steel the EAF process requires about:

▪ ▪ ▪ ▪

710 kg of steel scrap, 586 kg of iron ore, 88 kg of limestone, 2.3 GJ of electricity.

The main by-product of steel production at this point in the supply chain is ‘slag’ which has application in areas such as cement production. Steel is often thought of as a single commodity, but there are more than 3,500 different grades of steel, significant portions of which have been developed within the last 3

The facts in this section have been primarily sourced from the World Steel Association (https://www.worldsteel.org/steel-by-topic/statistics.html)

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20 years. ‘Unalloyed’ carbon steel (e.g. just iron and carbon) comprises the majority of steel production. The addition of other metals will improve the quality of the steel. For example, adding manganese will make it harder while nickel and molybdenum improves its resistance. Coating steel with zinc or nickel will help prevent rusting. The next stage of the process is to cast the molten steel into semi-finished products. These comprise of ‘long products’ (e.g. bloom and billet, mostly produced from a BOF) or ‘flat’ products (e.g. slabs, mostly produced from an EAF). These products can then be rolled into different shapes. Semi-finished long products are rolled into: ▪ ▪ ▪ ▪

Wire rod – used in construction transport and energy. Rebar – reinforcing steel bar used in construction. Sections – used in construction. Structural steel and rails – used in construction. The flat products are rolled into:

▪ Plate – used in construction, appliances, engineering, and energy. ▪ Hot/cold rolled coil – used in construction, transport, and appliances. The key applications of steel are: ▪ ▪ ▪ ▪ ▪ ▪ ▪

Buildings and infrastructure – 51% Mechanical equipment – 15% Automotive – 12% Metal products – 11% Other transport – 5% Domestic appliances – 3% Electrical equipment – 3%

5.4.1

Factors impacting the price of steel

Since the raw material inputs in the production process will often be traded markets, it is no surprise that they will have a significant impact on the price of steel. The key inputs are: ▪ ▪ ▪ ▪ ▪

Metallurgical coke (a refined carbon product made from coal). Iron ore, Scrap steel, Energy (e.g. coal and natural gas), Freight costs associated with movement of raw materials.

On the demand side, the main consumer of steel is China, followed by India and the Middle East. Notably, China is also the largest producer of steel.

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Steel risk management

Although the market for steel is sometimes considered to be the second largest after crude oil, futures contracts are a relatively recent addition to the suite of risk management products. At the time of writing, the London Metal Exchange (LME) offers two cash-settled steel futures; one references steel rebar and the other is scrap steel, the latter being the more liquid of the two contracts. The contract specification for the scrap steel contract is shown in Table 5.1. TABLE 5.1 Scrap steel futures contract. Contract type

Futures

Deliver type Lot size Contract period Price quotation Final settlement price

Cash-settled 10 tonnes Monthly out to 15 months US dollars per tonne Based on the monthly average price index price of the “Platts TSI HMS 1/2 *0: 20 CFR Turkey” assessment

Source: Based on LME, London Metal Exchange- Steel Scarp, 2020.

The contract reflects the fact that Turkey plays a central role in the market for steel scrap. One notable difference of this contract compared to the normal conventions applied to LME contracts is that it is cash, rather than physically settled, referencing a Platts index. Risk management products have also emerged for iron ore and coal, which will be considered in subsequent chapters.

5.5

THE LONDON METAL EXCHANGE

One common aspect of many commodity markets is the struggle to establish a single common and transparent pricing basis. For those participants involved in negotiating commercial contracts it may be difficult to determine if they are paying a “fair price”. In addition, the settlement of derivative transactions requires agreement on a single common price for the underlying asset. One of the main attractions of the London Metal Exchange (LME) is that their traded prices can provide the basis for a substantial proportion of such commercial transactions. The LME (2017) point out that the exchange is designed with physical market participants in mind (e.g. producers, processors, and consumers) who can avail themselves of the different risk management products that are available and can also use the exchange as a possible source of supply. However, this type of entity makes up about 1/3 of the total volume, with a variety of different financial market participants making up the balance. The LME offers futures and options that will allow participants in these markets to manage their price risk. Although the LME has many features in common with other

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financial exchanges (e.g. standardised contracts) the design of its forward price-based contracts often has more in common with over the counter (OTC) style instruments. It should be noted that a significant proportion of base metal transactions are executed on an over the counter basis. If a corporate customer wished to execute a transaction which is exactly tailored to their needs, the OTC market offers greater flexibility and a wider range of products. However, the LME offers an efficient mechanism where the risk taken in an OTC contract can be hedged using their suite of risk management products.

5.5.1

Exchange traded metal futures

Futures contracts represent the commitment to either buy or sell a particular metal at a pre-agreed price at a specified date in the future. LME transaction will require both parties to the trade to physically deliver the metal if the contract is held to maturity. Although it is possible to use the futures contract as a source of supply, it is more likely that the contract will be used as a financial hedge. Using the future in this fashion permits the user to separate the supply of the metal from the associated price risk. In reality, only a very small proportion of futures trades will go through to final settlement, typically about 1%4 . Physical settlement can be avoided by taking out an equal and opposite trade for the same delivery date (termed the ‘prompt’ date). The two transactions will offset each other, and the counterparty will cash settle the trade paying or receiving the difference between the two prices. The exchange currently offers futures contracts on four different categories of metals: Non-ferrous ▪ Copper ▪ Primary aluminium ▪ Aluminium alloy ▪ North American Special Aluminium Alloy (NASAAC) ▪ Lead ▪ Nickel ▪ Tin ▪ Zinc Ferrous ▪ Steel scrap ▪ Steel rebar Minor metals ▪ Cobalt ▪ Molybdenum

4

Source: LME (2017)

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Precious metals ▪ Gold ▪ Silver

5.5.2

Exchange traded metal options

The exchange offers options on the underlying futures contracts, so the buyer has the right but not the obligation to buy or sell an LME futures contract at a predetermined price at a pre-agreed time in the future. The exchange also offers Traded Average Price Options (or TAPOs). Average price options (sometimes referred to as ‘Asian style options’) are options where the settlement of the contract is not made against a single market price but against an average for a predetermined period. They are attractive from a buyer’s point of view as the premium cost is lower than an equivalent non-averaging option. TAPOs are settled against the LME Monthly Average Settlement Price (MASP), which is a figure published by the exchange that represents the average of all the daily settlement prices for a particular month.

5.5.3

LME prices and contract specification

In Section 5.2 it was argued that the supply chain for copper could be broken up into different components: ▪ ▪ ▪ ▪

Mining (ores and concentrates), Refining, Semi-fabrication, End product.

One of the issues central to the exchange traded metals markets is the exact form of the metal to be physically delivered at maturity. To ensure the contracts are standardised and are useful to market participants, the exchange sets specifications for form, quality, and shape, which are most widely accepted by the different market users. The LME contracts are usually for metals that can be easily transformed into an end product by a commercial user. As such the LME contract is designed to reflect the form and associated price of the metal at the refining stage of production. As a result, the LME price can be used as the basis for pricing a wide variety of commercial metal contracts where the actual metal content may vary. For commercial contracts based on metal in a state different to that specified in the LME contract, a mutually agreeable adjustment to the LME price could be applied. This may be a discount (e.g. ores and concentrates) or a premium (e.g. semi-fabrication or end product users). One example of how this is applied can be illustrated by considering an intermediate pricing system that is used between miners and smelters referred to as ‘TC/RCs’. TC stands for treatment charges (i.e. how much it costs to smelt the copper concentrate) while RC stands for refining costs. Theoretically it represents the cost of converting a tonne of concentrate into metal. They are charged by a smelter to a mine and as such represent revenue for a smelter and cost to a mine. Suppose a mine delivers concentrate to a smelter with 30% copper content. The price paid for the concentrate would reference the LME price but at a slight discount

125

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(e.g. 96.5% of the current market price). If the LME price is quoted as USD 7,000/tonne, the amount payable by the smelter would be USD 2,030 (30% x 96.65% x USD 7,000). However, this initial payable amount is reduced by the TC/RCs. The treatment charge can be quoted as a USD amount per ‘dry metric tonne’ (DMT) of concentrate. The refining charge is quoted differently as it is based on the quantity of copper within the concentrate; it may also by convention be quoted in US cents per pound. So if the copper content is 30% and the refining charge is, say, USD 0.045/pound of copper content, then the refining charge would be 30% x USD 0.045 x 22,046 = USD 22.8/DMT (there are 22,046 pounds to a metric tonne). The exchange also stipulates common standards for weights and strapping. Participants trade in lots rather than tonnes, with aluminium, copper, lead and zinc being sized at 25 tonnes. The NASAAC and aluminium alloy contract is for 20 tonnes, with nickel at six tonnes and tin at five tonnes. For example, the specification for the copper futures contracts is outlined in Table 5.2. The contract specification for copper options is outlined in Table 5.3. The expiry structure of LME contracts is relatively involved and merits a few comments. Metal can be traded for settlement on any business day three months into the future. For contracts expiring between three and six months, settlement is then weekly with Wednesday being the designated expiry date. Depending on the specific contract, settlement beyond six months will take place monthly out to a maximum of 123 months, each settling on the third Wednesday of the month. As a rule of thumb contracts for three-month delivery are the most liquid; this is based on the historic time it took to transport metal from its origin to London.

5.5.4

Trading

Trading at the LME is by a mix of open outcry and electronic transactions. The focus of open outcry trading is the ‘ring’ sessions. There is a morning and an afternoon session, which follow the same general structure. Each metal is traded twice in designated five-minute sessions and at the end of the second ring in the morning session, LME TABLE 5.2 Copper futures contract specification. Contract

Lot size Form Delivery (‘prompt’) dates

Quotation Settlement type Clearable currencies

Grade A copper conforming to the chemical composition stipulated by the exchange. All copper deliverable against an LME contract must be of an approved brand. 25 tonnes Cathodes Daily from cash to three months. Then weekly every Wednesday from three to six months. Then monthly every third Wednesday from seven months out to 123 months. US dollars per tonne Physical US dollar, Japanese yen, sterling, euro

* = Prompt date refers to the day that the physical metal is exchanged for cash. Source: Modified from LME, London Metal Exchange- Copper, Future Contract Specifiation, 2020.

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TABLE 5.3 Copper options contract specification. Underlying contract Lot size Price quotation Option style Delivery dates Settlement type Expiry date Premium quotation Strike price

LME copper futures – third Wednesday prompt of the contract month. 25 tonnes US dollars per tonne American Monthly from the first month out to 63 months Physical Any LME business day up to and including the first Wednesday of the expiring option month. US dollars per tonne USD 25 gradations for strikes from USD 25.00 to USD 9,975 USD 50.00 gradations for strikes from USD 10,000 to USD 19,950 USD 100.00 gradations for all strikes over USD 20,000

Source: Data from LME, Copper options contract specification, The London Metal Exchange. www.lme.com

staff monitoring activity within the ring will determine the ‘official’ closing prices for a variety of different maturities. Although it varies between metals, for copper the official prices quoted are for: ▪ Cash (i.e spot value) ▪ Three months ▪ Three forward December prompts This official fixing allows the market to establish a transparent benchmark against which trades can be settled. For example, for copper the ring trading times are: First session First ring Second ring (official) Kerb trading

12:00–12:05 12:30–12:35 13:25–13:35

Second session Third ring Fourth ring Kerb trading

15:10–15:15 15:50–15:55 16:20–17:00

Kerb sessions run after the main ring sessions and during this time, all the metals are traded with more than one trader per company allowed within the ring. In addition to the ring sessions it is possible to buy and sell metals around the clock on the exchange’s electronic trading application.

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5.5.5

127

Clearing and settlement

Settlement describes the point in time where an asset is exchanged for cash. Clearing relates to all those activities that happen after trade execution but before settlement. It is quite common for people to use the terms ‘clearing’ and ‘settlement’ interchangeably. One of the features common to all exchanges is the existence of a central clearing house and for the LME these functions are performed by its own entity LME Clear. Its primary role is to ensure that all purchases and sales executed on the exchange are settled in a timely manner. Once a trade is executed, both sides to the deal input the transactions to a common system and if the details agree, the trade is considered matched. As a result, the clearing house then becomes the legal counterparty to both sides of the transaction. That is, it becomes the seller to the buyer and the buyer to the seller. Neither of the original counterparties will have any further contractual commitments to each other, as the clearing house is now their counterparty. With the clearing house acting as the counterparty to both sides, the risk of the original counterparty defaulting is transferred to the clearing house. If one of the original contracting entities were to default, then the exchange would step in and guarantee the financial settlement with the non-defaulting entity. However, the probability of the clearing house defaulting is very slim as these entities are usually very well capitalised. It should be noted that this mitigation of credit risk only extends to those transactions executed directly on the exchange. A client who asks a broker to act on their behalf is still exposed to the full credit risk of their broker and vice versa. Even though the likelihood of the clearing house defaulting is slim, one of the techniques used to further mitigate the risk is the margining system. Margin is collateral that is collected at the start of the transaction (‘initial margin’) or as the value of the contract changes (‘variation margin’). Although cash is the most popular form of collateral, it may also be possible to deposit risk free securities (e.g. government bonds). In addition to the formal margining system covering transactions executed in the ring (or electronically), institutions trading on behalf of clients will also margin customers in order to mirror the payments they will make to the clearing house. The margining system on the LME works in a different manner than that seen on the various financial exchanges. On financial exchanges, variation margin is calculated based on the change from the previous day’s closing price. The margins are paid or received daily5 over the life of the deal, with the final settlement price – the exchange delivery settlement price (EDSP) – occurring on the last trading day. The impact of this margining system is to effectively make the future a series of daily contracts, which are instantaneously closed out and reopened at the closing daily futures price. The following examples will illustrate the concept. We will assume that a ring member has executed a trade where they buy one lot of aluminium at USD 1,900 per tonne for delivery in three months’ time. They will have to pay an initial margin, which is assumed to be USD 100.00. Suppose that one day later the price for delivery on the original prompt date is now USD 1,950. 5

Typically margins are calculated based on the closing price of the metal and are payable first thing the following day.

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In the first scenario we will assume that the member closes out the trade at this point. He has bought at USD 1,900 and sold one day later at USD 1,950. Assuming no further trades, the initial margin of USD 100.00 is returned as is the USD 50.00 profit which is their variation margin. In the second scenario we will again assume that the price has risen but that the trader decides to retain the position. Even though his position has increased in value, he receives no cash benefit. Unlike many financial exchanges the LME will only pay profitable variation margin when the position is terminated. However, if the price of the metal were to fall after one day to USD 1,850, the trader would be required to make immediate cash payment to the clearing house to support this loss. Losses will need to be made good immediately (like financial exchanges) whereas profits will not be paid until maturity (like an OTC contract). Since the financial crisis, the differences between OTC and exchange-based transactions have begun to blur and continue to evolve. Most financial markets are evolving towards three different structures: ▪ OTC traded, OTC cleared and settled, ▪ Exchange traded, exchange cleared and settled, ▪ OTC traded, exchange cleared and settled. For OTC transactions that do not involve the exchange, the credit risk between broker and client could be managed in a variety of ways. Some institutions may allow profits and losses on contracts to be handled as part of some agreed credit facility. Other institutions may operate a system where all losses and profits are remitted as and when they occur, or they may simply mirror the LME process. However, a very common method of managing the credit risk is through the taking of collateral. This is often governed by the terms of ISDA documentation (International Swaps and Derivatives Association). The part of the documentation that refers to collateral is referred to the Credit Support Annex (CSA). These cover: ▪ How often collateral can be taken. ▪ The point at which collateral will be taken (similar in some respects to an overdraft limit). ▪ The minimum amount that can be transferred between the two counterparties (for example £100,000). ▪ The type of acceptable collateral (e.g. cash and certain government securities).

5.5.6

Delivery

Settlement of futures contracts on the LME takes place in a unique fashion in comparison to a financial exchange. On financial exchanges, instruments can be bought and sold at any time although they will typically have fixed maturity dates set at three-month intervals. LME contracts can be traded for settlement on any chosen day (the ‘prompt date’) for up to three months from the trade date, then weekly for maturities between three and six months followed by monthly settlement and then monthly settlement out

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to 15, 27, 63, or 123 months forward. This makes the LME future more like a centrally cleared over-the-counter forward. Most LME contracts require physical settlement if they are held to maturity. As mentioned previously, the percentage of contracts going to final delivery is relatively small, but nonetheless the exchange can be used as the ‘market of last resort’ to procure supplies. To facilitate the potential delivery of the metal the LME has approved over 600 warehouses in 35 different countries typically sited in locations of net consumption rather than production. The exchange does not own or operate the warehouses and neither does it own the metal that is held therein. However, market analysts watch the volume of metal held within the warehouses as a gauge of currently available inventories. When an institution agrees to sell metal on the LME, it may choose the warehouse destination where delivery will take place. The contract specification outlines what can be delivered and the exchange has strict requirements on quality, shape, and weight. At the time of writing, the LME lists over 90 different brands of copper that can be delivered to satisfy a short position. If the seller delivers metal to the warehouse it will receive a warrant, which acts as evidence of ownership. The deposit of metal into the warehouse need not be in support of an LME contract and the issue of a LME warrant will only take place if the metal conforms to the contract standards outlined by the exchange. The terminology is that the metal is ‘put on warrant’. If the owner of the metal on warrant wishes to remove the metal, then the warrant will need to be canceled so it becomes ‘off warrant’. The right of a buyer to take delivery of the metal at the expiry of a futures contract is conferred by the transfer of a warrant from the seller. The issue of warrants is done by the warehouse in the location chosen by the seller for delivery, but the LME has overcome the administrative difficulties of managing a physical warrant system by introducing an electronic transfer system (LMEsword). This acts as a central depository for all LME warrants, which are issued in a standardised format and can now be transferred rapidly between buyer and seller. In certain financial futures markets (e.g. bond futures) the contract seller has a variety of embedded delivery options. In the metals market the seller can choose the location of delivery and the brand. If a seller is in possession of a number of warrants and is faced with having to deliver the metal, then logically they will choose the location that is most favourable to them (so probably less favourable to the buyer) and the brand that is least attractive. In financial futures markets this feature is referred to as ‘the cheapest to deliver’ option. This means that although there is a single ‘global’ futures price for all metal deliveries, the quoted price will reflect this optionality. As a result, there is a market to ‘swap’ warrants, which takes place off the exchange. So, if the terms of the warrant are not suitable for the buyer, they may seek to swap the warrant for a more favourable type. This has led to the development for premiums for warrants that confer delivery in a popular location or for a popular brand of metal. LMEsword allocates warrants randomly to those buyers with outstanding positions. This means that a buyer does not know which brand and into which location they will be delivered. On settlement date, the exchange will analyse the position of each individual entity netting off as many of their remaining purchases and sales, with any price differences settled in cash. The remaining net position will then go to settlement. Since the position on the exchange is always in balance (that is the total number of purchases or ‘longs’

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equals the total number of sales or ‘shorts’) at expiry, the exchange will take up the warrants from the market longs and will randomly assign them to the market shorts. The actual cash settlement amount may differ from the forward price agreed under the terms of the original deal because each contract allows the actual weight of the metal to differ by +/− 2% of the contract standard. As a result, the final price paid by the buyer will need to be adjusted to reflect the actual amount delivered.

5.6

BASE METAL PRICE DRIVERS

The main factors that drive the price of base metals markets include: Raw material availability – richer, low cost, long life ore sources have already been developed and are deteriorating quickly. Level of inventories – in the gold chapter it was highlighted that the bulk of all known gold was held above ground and as a result the forward curve was generally in contango. However, it is different for base metals where the balance of above and below ground supply is the opposite. For example, copper has traditionally suffered from relatively low above-ground inventories and as such its forward price curve can be prone to extended periods of backwardation. Government fiscal and monetary policy – at a simple level if the government were to implement an expansionary economic policy, this should stimulate economic activity and increase the demand for resources such as base metals. For example, in the copper market such factors as the level of car output, semiconductor demand, and new housing activity all influence the price of the metal. Exchange rates – base metals are traded in US dollars and so movements in the exchange rate will have an impact on the balance of demand and supply. If the dollar weakens relative to other currencies, the domestic currency cost of buying the metal will decrease, leading to an increase in demand and therefore an increase in the USD price. Chinese and Indian demand – the industrialisation of the Chinese economy and the rapid development of India has made the two countries substantial importers of many metals due to the lack of their own natural resources. This has contributed substantial upward pressure to the price of many commodities including base metals. For example, in 2016, copper production was estimated6 at 23,339 thousand tonnes, (abbreviated here to ‘kt.’) of which China was the largest single country producer at 8,436 kt. However, China consumed 11,446 kt. which represented about 50% of global demand. To put this into some context, European demand was 3,700 kt. while North America accounted for 2,336 kt. Availability of finance – after the financial crisis of 2007/2008 many banks were unwilling to extend credit and so as a result capital expenditure declined. In theory, this could eventually feed through to lower production and higher prices (all other things being equal). 6

Barclays Bank (2018) ‘Copper at the crossroads’.

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Capital spending and exploration – during periods of sustained low metals prices, mining companies are reluctant to invest in their own infrastructure or instigate new exploration projects. However, as the prices of metals rise, it will then prove difficult to bring new production on stream to benefit from rising prices. With many commodity markets there may be a substantial delay until new supplies of metal can be brought to market during which time the excess demand will cause the price of the metal to rise further. For example, it could take up to 10 years to produce metal from the point of its discovery. Over the years this production lag has increased due to factors such as increased construction costs due to rises in the price of metals (such as steel) greater labour and environmental regulations and a weaker US dollar. Although the argument has been made from a mining perspective, similar arguments could be made with respect to smelting and refining capacity. Environmental approvals – these can often be very lengthy processes and may encourage producers to focus on those jurisdictions where the standards are relatively loose. Substitution – as commodity prices rise the possibility of product substitution increases. With respect to base metals this may not be possible in the short term, but over the course of, say, two to three years this may well become feasible as manufacturers develop products with a smaller metal content. Production disruption – this usually manifests itself in two ways. The first would be the cessation of production due to labour disputes. Although rising prices may boost a producer’s profitability, it may lead to an increase in wage demands from the work force and possible industrial action. Barclays (2018) estimates that labour costs account for 26% of the cost of producing copper. The second reason relates to industrial accidents such as landslides, which may halt production for a period. Quality of infrastructure – although it may be tempting for producers to seek out relatively cheap sources of supply, one of the consequences may be that the state of local infrastructure may present challenges in terms of extraction and onward movement along the supply chain. If the extraction of the metal takes place in an emerging economy, there may also be issues surrounding the provision of a constant supply of energy. For example, in 2007, China agreed to build or refurbish Congolese infrastructure to a total of USD 12 billion in exchange for the right to mine copper of an equivalent value7 . Rising nationalism and protectionism of domestic resources – this relates to the fact that the extraction of the ore may be undertaken by a private foreign entity. A change in political climate may result in a demand to ‘take back’ the resources into local ownership. Production costs – one of the features of the general rise of commodity prices is the impact it then has on the costs of subsequent production. Operating costs could rise due to factors such as higher steel prices and energy costs. For example, the impact of higher energy prices is perhaps most apparent in the aluminium market where 50% of the production costs arise from these charges. 7

Economist (2008), ‘A ravenous dragon’.

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Investment demand – the equity bear markets of the late twentieth/early twentyfirst century led many institutional investors to seek out alternative asset classes to enhance their return. Evidence suggests that returns on commodities tend to be negatively correlated with those on financial assets, offering a powerful incentive for investors to diversify. Other investment motivations include the wish to find a hedge against inflation and the desire to benefit from the rise in prices in a bull market. One of the most common indicators of this activity is the ‘Commitments of Traders’ report produced by the Commodity Futures Trading Commission in the USA. This report shows the positions (in the US markets) for ‘commercial’ and ‘non-commercial’ users. Commercial users are defined as those entities that would use futures for hedging some form of underlying exposure. Investment demand would therefore be captured within the non-commercial users’ category. The impact of the business cycle – here the focus is essentially on the level of metal inventories. Figure 5.2 illustrates in a generalised fashion the impact of the business cycle on the base metals market. In this very simple model, the business cycle is represented as having four stages. Every economy will progress through each of these four stages in order but the length of each stage (how long it lasts) and the depth (how severe it will be) will be both different and unpredictable. In phase I (‘prosperity’) the economy is expanding and prices in general are rising. As economic activity increases there is an incentive to produce more and metal inventories tend to be relatively full. Available production capacity can catch up with the increase in demand. In phase II (‘transition’) asset prices overshoot their ‘fair value’ and demand starts to fall. As a result of the general decline in demand, inventories are wound down. This is because consumers are reluctant to buy new metal at high prices and so meet their requirements by running down existing inventories. There will also be an incentive to recycle the metal from scrap products as it increases in value. At this point, financial investors will start to withdraw their funds. Phase III (‘Recession’) represents a bear market, as demand is very low. Here there is very little incentive to produce the metals given the combination of lower prices and lower demand. In phase IV (‘Recovery’), growth accelerates as businesses restock metal inventories due to rising prices and demand. At this point inventories may tend to fall, and metal prices rise, as the increasing demand cannot easily be met out from available productive capacity.

Prosperity I

Transition II

Recession III

FIGURE 5.2 The impact of the business cycle on base metals.

Recovery IV

Base Metals

5.7

133

ELECTRIC VEHICLES

Broadly speaking there are three main types of electric vehicle (EV): A hybrid vehicle uses two systems to power the car. There is a traditional internal combustion engine that uses gasoline and an electric motor. The electric motor could be used to provide additional acceleration but can also be used to completely power the car at low speeds and short distances. The electric motor is charged by the internal combustion engine as well as the braking system. Plug-in hybrid electric vehicles will have some similarities to hybrid vehicles except that the battery capacity is greater allowing them to run on this source of energy for longer times and for greater distances. The battery is recharged from mains electricity. A full battery electric vehicle is only powered by an electric motor that derives its energy from batteries. These batteries can be charged by plugging the car into mains electricity. One of the key arguments made in favour of EVs is that they do not produce emissions, but this tends to ignore the fact that to generate electricity then either coal or natural gas will be burnt. This simply moves the emissions issue from the vehicle to another part of the supply chain. From a commodities perspective, electric vehicles will impact several aspects of this text for a variety of reasons: ▪ Will the advancement of battery technology see new traded markets develop? ▪ How will the metals currently used in car production evolve? For example, palladium and rhodium are not typically used in the EV production process. ▪ How will the move to electric motors impact the main energy markets of oil, refined products, natural gas, and electricity? ▪ How will the energy infrastructure develop to accommodate the increase in demand for electricity? As of the time of writing the LME currently offers EV risk management products in cobalt, nickel, copper, and aluminium. To meet the increasing demand for EVs then new products likely to be developed include lithium, nickel, sulfate, and manganese.

5.7.1

Lithium

Most electronic devices use lithium-ion batteries. Lithium has been described as the ‘new gasoline’ given its importance in EV batteries. Although the batteries may contain 40–80 kg of lithium, scientists are always looking at ways to reduce cost and boost power given that many consumers cite ‘range anxiety’ as one of the reasons they are reluctant to invest in an electric car. This could feasibly mean an increase in alternative cheaper materials as substitution takes place. The supply chain for lithium shares common characteristic with those of other metals: ▪ Mining ▪ Concentration/semi-processing

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Chemical refining Battery precursors Battery cathode materials Li-ion batteries

5.7.2

Cobalt

This metal is used as a compound with lithium in the cathode of lithium-ion batteries. It is produced mainly as a by-product of copper and one of the largest suppliers is the Democratic Republic of Congo, who sells a substantial proportion of the output to China for processing into battery materials. The metal has traditionally traded at a relatively high price and so there will be an incentive to find cheaper alternatives. In 2017, Volkswagen issued a tender to obtain a minimum of five years of cobalt supply at a fixed price. However, in anticipation of potential increasing demand and therefore rising prices, miners were reluctant to sign up.

5.8 5.8.1

STRUCTURE OF MARKET PRICES Long-term prices

‘Long-term prices’ is a commonly used phrase in commodities and is worthy of some analysis. In theory, a long-term price is one that ensures a balanced market and stable prices over the medium to long term. It is often one that is used for longer-term valuation and investment analysis. So, if a bank is considering lending to a producer to finance a new mine operation, they may insist that as part of the transaction, a proportion of the production should be sold on a forward basis. If the new mine was not going to see any production for five to six years, the analyst is faced with making predictions about the forward price at some future date rather than today’s forward price. The big question is – which price should be used? Arguably, there are perhaps five different approaches: 8 ▪ Mean reversion price – an average over an extended history of prices (and whether it is adjusted for the impact of inflation). ▪ Future average price – the average of annual forecasts over an extended future period. ▪ Equilibrium price – a qualitative assumption or derived from some perceived relationship between price and levels of inventories. ▪ Forward market long-term price – using the back end of the current forward curve. ▪ Incentive price – the price needed to encourage supply to meet future demand. The theory is based on the notion that producers will only invest if they believe that prices will be high enough to cover all their investment costs and provide an adequate return on capital over the life of the project.

8

Barclays (2004), ‘Copper market outlook – The twin peak’.

Base Metals

5.8.2

135

How do forward curves move?

When prices increase it is the shorter end of the forward curve that exhibits greater volatility. The shorter end of the forward curve will be more influenced by incidents in the physical market, whereas long-term prices are determined by mostly financial considerations (e.g. inflation and interest rates). An example of this was illustrated with respect to crude oil in Chapter 2 (Figure 2.2). This suggests that there are three main ways in which a forward curve can move: ▪ Directional changes – the curve moves up or down in a broadly parallel manner. ▪ Slope changes – the slope of a curve measures the difference between two prices at different maturities. So, between any two maturities it is possible for the curve to either steepen or flatten. ▪ Shape changes – this relates to the degree of curvature and is measured as the difference between any three points. Although there are several ways in which this could be calculated, it is usually measured as a central maturity minus a shorter-dated maturity minus a longer-dated maturity.

5.8.3

Are forward prices forecasts?

This was discussed at length in Chapter 2 and perhaps can be summarised by a simple statement: ‘it depends’. There is something of a market myth that forward prices are somehow the market’s ‘best guess’ as to future spot levels (i.e. today’s three-month forward price is a forecast of the spot price in three months) but this supposes that price formation is solely determined by expectations, which is a very severe constraint. The best way to think of a forward is to view it as a benchmark rate against which hedging decisions could be assessed. Suppose that the ‘cash’ (i.e. spot) price of copper is USD 6,700 and the three-month rate is USD 6,800. A market participant looking to sell the product in three months’ time could either lock into a price of USD 6,800 or do nothing and hope that over the period prices will rise above the initial forward rate. If the seller believed that the cash price was going to be higher than the initial forward, then the ‘do nothing’ scenario is the optimum solution. If they believed that cash was going to end up below the initial forward rate, then they should sell forward. If they felt that the cash price would evolve in line with the forward market and end up at USD 6,800 then they would be indifferent between the two choices9 . As the price of the metal rises there is a possibility that the market could move into backwardation. Indeed, as the price rises, the slope of the forward curve becomes more steeply backwardated. In these conditions (high prices and steep backwardation), producers will be less tempted to sell their production forward. Anecdotally, at very high price levels, producers are often less keen to lock into attractive prices. This is often a result of shareholder pressure that wants the company to benefit from rising prices. It may also be simple over-optimism. Somewhat paradoxically, anecdotal evidence suggests that producers tend to be more active hedgers in low price environments. In addition, consumers may decide to take some advantage of the cheaper forward purchase 9

This simple analysis ignores other hedging strategies such as options.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

price for the metal. Investors may wish to take advantage of the rising price environment and take exposure to the market using exchange traded futures, further adding to the longer-dated buying pressure. These actions will, to an extent, act as a brake to the degree of backwardation experienced by the market.

5.8.4

The role of marginal costs

The classic definition of marginal cost is the additional cost of producing one additional unit of a particular product. Within the base metals world discussions on how long-term prices are expected to evolve often centre around this measure and is usually shown diagrammatically. A hypothetical marginal cost curve is shown in Figure 5.3. The graph plots the production capacity and costs for an entire sector (e.g. copper or coal). The horizontal axis maps out the cumulative production of all the participants against their cost of production on the vertical axis. By overlaying the current price of the commodity onto the chart it can provide a quick indication of which producers are currently profitable. As a rule of thumb some analysts will focus on those producers sitting beyond the 90th percentile responsible for 10% of all production. These are treated as the marginal producers who in theory would withdraw supply from the market in the event of prices being persistently below their costs. In theory, marginal producer cash operating costs are a good guide to the floor for prices during periods of oversupply. When prices fall to or just below marginal production costs, a portion of output will incur losses leading to the removal of supply from the market. This cuts the available supply and prevents prices from falling further. However, marginal production costs are not a good guide to prices during periods of rapid demand growth when supply is struggling to keep up with demand. It is important to realise that these curves are not static: ‘Historically cost factors appear to have been highly dynamic, with the marginal cost of production (and consensus long-term forecasts) tending to move up with spot Cost of production

90th percentile

Production

FIGURE 5.3 Hypothetical marginal cost curve.

Base Metals

137

prices and then falling as the cycle turns down. Costs (like all market prices) are endogenous to the broader economic environment’ (Credit Suisse, 2013).

5.8.5

Premiums

Metal premiums are charged by a producer to a customer. They are designed to cover the cost of shipping metal to a customer and include elements such as transportation, warehousing, financing, alloying, and marketing. They are market driven and negotiated with the client as part of the terms of a commercial contract. They represent revenue for a refiner and a cost to a consumer. The easiest way to understand the role of the premiums is to realise that the LME price is, in effect, a ‘global price’ that does not always capture regional differences. Suppose that a US consumer of aluminium is negotiating a bilateral supply contract with a producer. When it comes to establishing the price to be paid, this could be made up of several components: ▪ The LME official price for a specific date or an average of LME prices over a specific period. ▪ A regional premium which is intended to reflect the availability of the metal in a particular geographic region and the costs associated with delivery. ▪ Premiums which may reflect the costs of producing a particular shape, quality, or alloy. ▪ Any foreign exchange rate considerations (e.g. a EUR-based consumer who is paying in USD). ▪ The part of the supply chain to which the contract relates (e.g. ores and concentrates may trade at a discount to the LME price, while a finished product with a higher specification than the LME might attract a premium). The sum of these different components would represent the ‘all in’ price paid for the metal. During the preparation of this manuscript (mid-2018), the USA announced plans for tariffs on steel and aluminium imports. One of the consequences was that since the US is a net importer of aluminium, the US Midwest Aluminium futures premium registered a significant increase in anticipation of higher costs either from increased demand for US-produced metal or imported metal subject to tariffs. Premiums for aluminium in the US market came under regulatory scrutiny in 2014 when the commodity-related activities of several market participants were reviewed10 . During the investigation it was argued that warehouse queues were artificially managed to increase the amount of time it took to remove metal from a particular location increasing the warehouse owners’ rental income. The report noted that the increase in the number of days taken to ‘load out’ the metal was associated with an increase in the regional premium. The implication being that this extra rental cost was one factor increasing the regional premium.

10

US Senate (2014)

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

One of the more recent innovations from the LME has been a contract that allows participants to hedge the size of the premium for aluminium. The contract specification for the US aluminium premium contract is shown in Table 5.4. TABLE 5.4 Aluminium premium futures contract. Feature

Description

Contract name Region Underlying metal

LME Aluminium US premium Midwest and South US regions High grade primary aluminium premium warrant in the designated region. 25 tonnes Third Wednesday of each maturity month Monthly out to 15 months US dollars per tonne Physical delivery Seller provides: LME aluminium premium warrant in the designated region. Buyer provides: Any LME warrant, plus the premium cash as agreed at the time of the contract formation, less the “Free on Truck” charge at the warehouse where the LME premium warrant is delivered.

Lot size Prompt dates Maturity months Price quotation Settlement type

Source: Modified from LME, London Metal Exchange- Aluminium, Future Contract Specifiation, 2020.

The aim of the contracts is to allow participants to hedge the ‘all in’ cost of buying physical aluminium in a non-queued LME ‘premium warehouse’. The nature of the transaction is considered in Figure 5.4. Figure 5.4 illustrates the use of the contract in conjunction with a standard LME contract. The standard contract is shown on the left-hand side of the diagram and illustrates the purchase of the metal where the buyer receives a standard LME warrant and Standard LME contract

LME premium contract

Buyer

Buyer

Standard metal warrant

Cash

Standard metal warrant + premium cash

Seller

FIGURE 5.4 Hedging a base metals transaction.

Premium warrant

Seller

139

Base Metals

delivers the contracted price. The diagram on the right-hand side illustrates the purchase of a premium contract. From the buyer’s perspective their net position is that they will pay the agreed cash amount plus a supplemental cash amount for the premium contract in exchange for receiving a premium warrant in the designated region. If a commercial contract does reference the LME price, then it is possible to hedge this component using the exchange’s risk management products. Although, the exchange offers a risk management contract to hedge the premium components, it will reflect general demand and supply dynamics and may not capture the various subtleties of an individual contract. As a result, there could be an element that is unhedgeable, which represents the position’s basis risk.

5.9

HEDGES FOR ALUMINIUM CONSUMERS IN THE AUTOMOTIVE SECTOR

The commodities primarily hedged by the automotive sector are: ▪ ▪ ▪ ▪ ▪ ▪ ▪

Aluminium (body panels, engine blocks). Copper (wiring). Zinc (stainless steel coating). Lead (batteries). Platinum and Palladium (catalytic converters). Plastics (cabin interiors). Steel (body panels).

Of these commodities, aluminium is the most significant in terms of volume because the physical characteristics of the metal are attractive. It offers a good strength to weight ratio and since this reduces the weight of the vehicle, there is an added environmental benefit in that the level of emissions are lower. One of the ways in which the aluminium content could be hedged is by using the NASAAC (North American Special Aluminium Alloy Contract) future on the LME. This futures contract was set up by the exchange to meet the specific hedge requirements of the US automotive sector. The contract specification is ‘engine block alloy’ and delivery locations are near the end users. It was introduced due to concerns that the price movements of the primary aluminium alloy contract was not sufficiently correlated with the actual metal used by the industry. However, to date, the contract has experienced mixed success mainly due to poor liquidity. Although the car producers would be natural buyers of the contract, there are limited natural sellers. The sellers tend to be scrap merchants who are of poor credit quality and are therefore constrained as to the tenor to which they can sell forward.

5.9.1

Forward purchase

For purposes of illustration we will assume the following prices for aluminium (USD per metric tonne). Cash: Three months:

USD 2,400 USD 2,500

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

The use of averaging to settle commodity market contracts is a common practice and has several benefits. Take for example a consumer of metal who decides to link the cost of buying the physical metal to some form of average. By using the average price, the cost of the metal will not be based on an extreme level, as a sharp upwards movement prior to the end of the period will be averaged out. However, by the same token they cannot take advantage of a sharp downward movement, which would reduce their cost. The simplest (and often the most popular) method of hedging a purchase is to buy the metal for forward delivery. In this example we will separate the delivery of the metal from the hedge. That is, the consumer will buy the required tonnage of the metal from their normal supplier and enter a cash-settled hedge transaction with a bank. Since the manufacturer will take delivery of the metal from his regular supplier in the future he is said to be ‘short the metal for forward delivery’. That is, a rise in the price of the metal will incur extra costs while a fall in the price will save money. For the purposes of this example, it is assumed that the commercial contract will be in the form of a ‘floating forward’. This means the consumer agrees to buy the metal for delivery at a fixed future date, but the settlement price will only be determined at the delivery date and will be based on some average price. There are many ways in which this could be structured; for example, a three-month forward deal with the settlement price based on the average of the LME cash price over the month prior to settlement. In addition to this physical contract the consumer agrees a cash-settled, three-month floating price forward with its bank at a price of USD 2,500/metric tonne. This contract will also settle against the average of the LME cash price over the month prior to settlement. The forward price hedge with the bank is cash settled, as it is not intended as a mechanism for obtaining physical supplies of the metal. In this case it is assumed that the cash settlement amount on the forward is simply the difference between the average LME cash price in the month prior to maturity and the forward price agreed at the outset of the hedging transaction. Somewhat confusingly, the market will refer to this type of deal as a ‘swap’ transaction as it is, in effect, a single period contract for difference. However, it should not be confused with a multi-period swap or a swap transaction where two entities execute a simultaneous purchase and sale for different maturities against cash. At the end of the three-month period we will assume that the appropriate monthly average LME cash settlement price is USD 2,400. Under the terms of the physical contract, the consumer takes delivery of the required amount of metal at this price from his supplier and settles the forward contract in cash with the bank. In this case the settlement price is below the forward and so the manufacturer must pay USD 100.00 (USD 2,400 – USD 2,500) per tonne to the bank. However, from the manufacturer’s perspective, their net expense is the cost of buying the underlying metal from their normal supplier (USD 2,400) plus the cash payment to settle the forward contract with the bank (USD 100) – a total cost of USD 2,500, which was equal to the fixed price agreed under the terms of the hedge with the bank. Had the settlement price been USD 2,600 then the manufacturer would pay this amount to procure their physical supply but would receive USD 100.00 from the bank in settlement of the hedge. Again, the net price achieved for the purchase of the metal would be USD 2,500.

Base Metals

5.9.2

141

Carry trades in the base metal market

One of the issues faced by end users of derivatives relates to the timing of the hedge. Let us assume that the aluminium supplier tells the manufacturer that there will be a delay in the shipment of the metal. This means that the hedging transaction also needs to be delayed avoiding a mismatch in timing. Closing out the original trade can restructure the hedge with an equal and opposite transaction and simultaneously execute a second transaction that re-establishes the original exposure, but at a different time in the future. Recall that the original hedge required the consumer to buy the metal for three-month forward delivery at USD 2,500. After one month the consumer decides that he wants the forward delivery date to be moved back by a month. The original three-month exposure now has a residual exposure of two months, and so the consumer sells an offsetting two-month forward and simultaneously buys the metal for three-month delivery. This simultaneous sale and purchase of futures for different maturities is referred to generically as a ‘carry’ trade. When the consumer sells the future for a shorter-dated maturity and buys a future for a longer-dated maturity, it it is classified as a ‘lend’. This is because when the combination of forwards used to switch the delivery are analysed from an economic perspective, the metal is being delivered out for one settlement date but being repurchased for delivery at a future date. This is similar in structure to a gold swap analysed in Chapter 4. Readers familiar with the foreign exchange markets would recognise this type of transaction as an FX swap. An example will illustrate the concept. Let us assume that after one month the market is still in contango and the prevailing two- and three-month forward prices are USD 2,600 and USD 2,650, respectively. From the consumer’s perspective the original long forward at USD 2,500 is closed out by selling a two-month forward at USD 2,600 to yield a profit at the prompt date of USD 100.00. Simultaneously, the consumer initiates a new long position for delivery in three months at the now prevailing price of USD 2,650, which is higher than the original forward price of USD 2,500. However, the hedge cost will be reduced by the USD 100.00 profit received on close out of the original exposure. This would give a new forward purchase cost of USD 2,550 (USD 2,650 – USD 100.00) if one ignores the time value of money. If the profit of USD 100.00 made from closing out the original futures position could be put on deposit to earn interest between months two and three, the final purchase cost would be further reduced. The opposite of a lend is a borrow; a combination strategy where the metal is bought for near-dated future delivery and sold for a far-dated future delivery.

5.9.3

Vanilla option strategies

One of the drawbacks for a consumer buying metal on a forward basis is that if the price of the underlying metal declines, they would be locked into paying a settlement price above the current market. The alternative is an option-based strategy. All the following strategies are priced using the following assumptions

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Cash price Three-month forward Option style Implied volatility Maturity

USD 2,400 USD 2,500 European, cash-settled 20% p.a. (no skew) Three months (92 days)

The terms of the options are designed to mirror those of the underlying contract to buy the physical metal. 5.9.3.1

Synthetic long put

In the previous section the manufacturer was short metal for forward delivery by virtue of his physical contract with the supplier. To hedge this exposure the manufacturer could buy a call option with the strike set a level that suits their risk appetite. In many cases an out-of-the-money (OTM) strike is selected to reduce the premium cost. We will assume that the manufacturer decides to execute the call with a strike of USD 2,600, which makes the option OTM with respect to the three-month forward price of USD 2,500. The premium for this option is USD 60.00. Figure 5.5 shows the ‘at expiry’ position for the manufacturer. The vertical axis is defined as the cost of buying the metal while the horizontal axis shows the current price of the metal. The definition of the vertical axis may seem somewhat counterintuitive, but this approach allows for the diagram to incorporate the individual option payoffs using the traditional ‘hockey stick’ orientation. Decreasing cost

Underlying position

Long call option

Increasing cost

FIGURE 5.5 Synthetic long put.

3,027.4000

2,976.2500

2,925.1000

2,873.9500

2,771.6500

2,822.8000

2,720.5000

2,669.3500

2,618.2000

2,567.0500

2,515.9000

2,464.7500

2,413.6000

2,362.4500

2,311.3000

2,260.1500

2,209.0000

2,157.8500

2,106.7000

2,055.5500

Net position

U/L Price

143

Base Metals

Notice how the net position resembles a long put option. Recall the shorthand version of put-call parity (see Chapter 2): +C − P = +F Where: +C = Long call option −P = Short put option +F = Long position in the underlying asset Although strictly speaking this condition only holds if the strike, maturities, and notional amounts are the same, applying the principles intuitively we can rearrange the formula to arrive at: +C − F = +P That is, the combination of buying a call option and a short forward position will be equivalent to a long put. The maximum cost to the manufacturer occurs when the market price rallies. Assume that the settlement price of the metal at the option’s expiry is USD 2,700. The manufacturer: ▪ Buys the physical metal from their normal source and pays the settlement price of USD 2,700. ▪ Exercises its call option and cash settles the contract. The manufacturer receives USD 100.00 per tonne (USD 2,700 − the strike of USD 2,600). This returns a net amount of USD 2,600, a sum equal to the strike of the option. To calculate the next cost the premium paid on the option must be added to this amount. Ignoring time value of money considerations (the premium was paid at the start of the contract and the net cost is calculated at the expiry of the option), the maximum cost of the metal is USD 2,660 (USD 2,700 − USD 100.00 + USD 60.00). A common misconception about this strategy is that it would be appropriate if the manufacturer believed that the underlying price was about to rise. If this were the case, a more effective strategy would be to buy the metal forward at the prevailing price of USD 2,500, as it does not incur an option premium. The purchase of the call option would be appropriate if the manufacturer believed the price was going to fall but could not afford for his view to be wrong. If the price of the metal falls, he forgoes the option and buys the metal in the underlying market at a price lower than the strike, although the premium would represent a sunk cost. If the metal rises in value against his expectations, the call option offers protection by ensuring a maximum purchase price.

5.9.4

Short option positions

As in the previous examples we will assume that the consumer is short the metal for forward delivery.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

5.9.4.1

Selling out-of-the-money (OTM) puts

The manufacturer could buy the physical metal for delivery in three months’ time and sell an OTM put option with the same maturity (see Figure 5.6). Using the principles of put-call parity this net position resembles a short call. Since, +C − P = +F So, −F − P = −C Suppose that the put option is sold at a strike of USD 2,450 generating a premium of USD 76.00 per tonne. This premium can then be used to subsidise the eventual purchase price. If the price of the metal falls below the strike price, the company would have to compensate the bank for the difference. This would end up increasing the cost of the forward purchase. To illustrate, let us assume the price of the metal falls to USD 2,300 per tonne. The manufacturer: ▪ Buys one tonne of the physical metal for USD 2,300 from his usual supplier under the terms their physical contract. ▪ Cash-settles the put option, paying the difference between the strike (USD 2,450) and the spot price (USD 2,300) to the bank (i.e. USD 150.00). ▪ Retains the premium on the option (USD 76.00).

Decreasing cost

Underlying position

2,938.4000

2,888.7500

2,839.1000

2,789.4500

2,739.8000

2,690.1500

2,640.5000

2,590.8500

2,541.2000

2,491.5500

2,441.9000

2,392.2500

2,342.6000

2,292.9500

2,243.3000

2,193.6500

2,144.0000

2,094.3500

2,044.7000

1,995.0500

Short put option

U/L Price

Net position Increasing cost

FIGURE 5.6 Short forward position combined with sale of OTM put.

145

Base Metals

Ignoring the timing of the premium payment, the total cost of buying one tonne of the metal is: USD 2,374 (USD 2,300 + USD 150.00 − USD 76.00) However, if the price of the metal were to rise to an average price of USD 2,700 per tonne the cost of buying the metal would be: ▪ The cost of purchasing the physical metal at a price of USD 2,700 ▪ Less the USD 76.00 premium received on the option, which is not exercised This results in a cost of USD 2,624 per tonne, so the result is that as the underlying price rises, the net cost of buying the metal is subsidized by the option premium. This strategy will reduce the forward cost of the metal if the manufacturer expects the price of the metal to rise. If the settlement price for the metal was below the strike, then on a net basis the consumer will pay a fixed price. 5.9.4.2

Selling OTM calls

In this strategy the manufacturer would buy the metal for delivery on a forward basis and sell a cash-settled call option (see Figure 5.7). The strike of the call option would be set at a price level that the manufacturer does not expect to trade. If the price of the metal falls the options are not exercised and the premium income reduces the purchase cost. A similar situation arises if the underlying market rises but does not hit the strike. If the market trades above the strike, the calls are cash-settled incurring a cost. Notice that the position is relatively risky compared to the previous examples. If the price of the metal falls, the consumer will buy the metal at a lower price and will retain the option premium lowering the net purchase price. A rise in the underlying price beyond the Decreasing cost Short call option

Increasing cost

FIGURE 5.7 Short forward position combined with sale of OTM call.

3,027.4000

2,976.2500

2,925.1000

2,873.9500

2,771.6500

2,822.8000

2,720.5000

2,669.3500

2,567.0500

2,618.2000

2,515.9000

2,413.6000

2,464.7500

2,362.4500

2,311.3000

2,260.1500

2,209.0000

2,157.8500

2,106.7000

2,055.5500

Underlying position

U/L Price

Net position

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

strike of the sold option results in them having to pay increasing amounts for both the physical metal and the short option position. 5.9.4.3

Selling swaptions

Suppose a miner is running a host operation, which is currently not working at full capacity, possibly due to low market prices. The miner would be willing to run at 100% capacity if the price of metal were 15% higher than its current value. This suggests that there is an element of optionality within the operation; the ability but not the obligation to produce. The miner sells a cash-settled call option on the metal. If prices rise and the option is exercised, the buyer will receive the difference between the spot and strike price. To offset this cash payment on the derivative the miner will have to increase production, but this is now down at levels that are economic.

5.9.5

Combination option strategies

Arguably the main motivation behind combination strategies is to offer the client a hedging solution at a lower or no premium cost. 5.9.5.1

‘Min-max’

The min-max option strategy is probably the most common combination strategy seen across all asset classes. As with many option strategies it has different names depending on the underlying asset class: zero-premium collar, range forward, and cylinder are just some of the phrases used to describe the strategy. One way of constructing the strategy is: ▪ Purchase the physical metal for delivery in three months’ time. ▪ Buy out of the money calls at a strike of USD 2,600 to give upside price protection. ▪ Sell OTM puts with the strike set at such a level that the net premium is zero. Based on the prevailing market parameters, the strike of the sold put would be set at USD 2,410. At first glance, it is not necessarily obvious what the option solution offers. However, recall that both short calls and long puts are selling strategies. The strategy fixes the minimum sale price (via strike of the long put) and the maximum sale price (via the short call). If the settlement price applicable to both the metal and option rises to USD 3,000, then the cost of purchasing the metal is reduced by virtue of the long call which pays out the difference between the strike and the final price (i.e. USD 400.00). The put is not exercised leaving the consumer with a net purchase cost of USD 2,600. See Figure 5.8. By the same logic, the impact of the short put position means that if the price of the metal were to fall, the consumer would not be able to benefit from price falls beneath the strike of this component of the transaction. So if the settlement price for the option and the metal was USD 2,000, the put is exercised against the manufacturer who pays USD 410, resulting in a net cost of USD 2,410, which is an amount equal to the strike of the sold put. In between the two strikes neither option is exercised, and the consumer simply buys the metal in the market at the prevailing price.

147

Base Metals Decreasing cost

Long call option Underlying position

2,972.3417

2,922.0917

2,871.8417

2,821.5917

2,771.3417

2,721.0917

2,670.8417

2,620.5917

2,570.3417

2,520.0917

2,469.8417

2,419.5917

2,369.3417

2,319.0917

2,268.8417

2,218.5917

2,168.3417

2,118.0917

2,067.8417

2,017.5917

Short put option

Net position

Increasing cost

FIGURE 5.8 ‘Min-max’ solution. 5.9.5.2

Ratio min-max

In this structure illustrated in Figure 5.9, the strike on the purchased call is kept at USD 2,600. The transaction is still structured to have zero premium, but instead of selling options in equal proportions to the calls, a smaller notional of puts are executed. In this example puts equal to 75% of the underlying exposure are sold, but to ensure the structure is zero premium the strike of the put options has to be moved closer to the current forward price to increase the premium. In this instance it would result in a strike of USD 2,458 on the sold put. As a result, there is no longer a minimum price level at which the hedger will buy the metal. However, they will not get 100% of the benefit of a falling price as the sold put option represents a liability. Since the notional amount on the sold put is 75% of the call option, a one-unit fall in the price below the strike of the put will result in the hedger benefiting by 25% of this change. That is, they can only benefit from the unhedged portion of the transaction. At first sight this strategy is superior to the simple min-max as it does not impose a floor on the purchase of the metal in a falling market. However, like all option strategies it is not possible to obtain something for nothing and there is indeed a trade-off. With the simple min-max solution, the hedger will benefit fully from any decline in price up until the strike of the put. For the ratio min-max solution, although the hedger will benefit in a falling price environment below a relatively higher threshold level, they will only benefit from 25% of the decline, albeit with no floor. 5.9.5.3

‘Three way’

In the ‘three way’ structure (Figure 5.10), the trade consists of a bull spread (constructed using calls) financed by the sale of a put. The structure is zero premium.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Decreasing cost Underlying position

Long call option

2,991.1575

2,940.6075

2,890.0575

2,839.5075

2,788.9575

2,738.4075

2,687.8575

2,637.3075

2,586.7575

2,536.2075

2,485.6575

2,435.1075

2,384.5575

2,334.0075

2,283.4575

2,232.9075

2,182.3575

2,131.8075

2,081.2575

2,030.7075

Short put option

Net position

Increasing cost

FIGURE 5.9 Ratio ‘min-max’ solution. A bull spread is created by the purchase of a low strike call and the sale of a high strike call11 . Since the purchased call is in-the-money and the sold call out-of-themoney, the combined position has an associated cost. This is financed by the sale of a put option with the strike set at a level that results in a zero premium. Using the previous data, one possible permutation is: ▪ Short a put option at USD 2,376, ▪ Long a call option at USD 2,450, ▪ Short a call option at USD 2,550. The final cost to the consumer will vary according to the settlement price at maturity: ▪ If the price is below USD 2,376, the cost of buying the metal will also be USD 2,376 by virtue of the sold put. ▪ If the market price is between the strike of the sold put (USD 2,376) and the purchased call (USD 2,450), the consumer pays the prevailing market price as neither option is exercised. ▪ For market prices between USD 2,450 and USD 2,550, the consumer will pay a strike equal to the purchased call as neither of the sold options is exercised. ▪ Above the strike of the sold call (USD 2,550), the consumer will pay the prevailing price less USD 100.00. This USD 100.00 cost reduction is attributable to the bull 11

Bull spreads are sometimes referred to as ‘call spreads’.

149

Base Metals Decreasing cost Underlying position

Long call option

2,746.3040

2,716.6040

2,686.9040

2,657.2040

2,627.5040

2,597.8040

2,568.1040

2,538.4040

2,508.7040

2,479.0040

2,449.3040

2,419.6040

2,389.9040

2,360.2040

2,330.5040

2,300.8040

2,271.1040

2,241.4040

2,211.7040

2,182.0040

Short call option

Net position

Short put option Increasing cost

FIGURE 5.10 ‘Three way’ structure. spread element of the strategy and is a reflection that prices above USD 2,550, the purchase of a call at USD 2,450 and the sale of a call at USD 2,550, would result in both options being exercised. Since both options are exercised, the consumer will end up with a profit of USD 100.00, which is the difference between the two strikes.

5.9.6

Structured option solutions

The range of option-based strategies widens considerably if one were to include structured solutions that are constructed using exotic options such as barriers. Three possible strategies are highlighted here with an explanation as to how they are structured. As with the previous examples, it is assumed that the consumer has an agreement to buy the metal at a future date based on the price that prevails at the time. As such they are ‘short’ the market for forward delivery. 5.9.6.1

Knock-out forward

This is a standard forward contract that automatically terminates if the cash price trades at, or beyond a predetermined knock out price before expiry. To compensate the investor for the potential early termination of the contract, the forward price is set at a more favourable level than the prevailing market price. The knock-out forward is generally structured for zero upfront cost. Market prices Three-month forward price

USD 2,500

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Contract prices Contract forward price Knock-out price

USD 2,450 USD 2,932

In this transaction the consumer will buy aluminium at a price of USD 2,450 at expiry of the contract as long as the knock-out price of USD 2,932 does not trade during the life of the transaction. If the knock-out price trades, the forward contract is terminated and the consumer is left unhedged at what would now be a disadvantageous price compared to the original three-month forward. See Figure 5.11. The construction of this strategy is based on the principles of put-call parity using barrier options. The contract forward price is created by the purchase of a knock-out call and the sale of a knock out put with the same strike and barrier. +C − P = +F If the two options continue to be active, they combine to give the favourable synthetic forward position. If the knock-out price trades, resulting in the termination of both options, then the consumer is left unhedged in an unfavourable set of market circumstances, i.e. higher prices. 5.9.6.2

Forward plus

In a forward plus contract the client obtains protection against a steep rise in the underlying price by virtue of a zero-premium call option that is struck slightly Decreasing cost

3,308.1667

3,233.9167

3,159.6667

3,085.4167

3,011.1667

2,936.9167

Short knock out put option

2,862.6667

2,788.4167

2,714.1667

2,639.9167

2,565.6667

2,491.4167

2,417.1667

Long knock out call option

2,342.9167

2,268.6667

2,194.4167

2,120.1667

2,045.9167

1,971.6667

1,897.4167

Underlying position

Net position Increasing cost

FIGURE 5.11 Knock-out forward.

151

Base Metals

out-of-the-money. However, the contract contains a trigger level set below the current market price, which if activated, will alter the payoff of the structure. If the cash price trades above this trigger rate during the life of the transaction, the client will retain the right to buy the underlying at the call strike. However, if the cash rate trades below the trigger price, this right becomes an obligation with the client being required to take delivery of the underlying at the call strike price. To illustrate the concept let us assume the following values are observed in the market: Market price Three-month forward price

USD 2,500

Strike price Trigger level

USD 2,600 USD 2,139

Contract price

If the cash price rises during the life of the transaction and the trigger level does not trade, the consumer will buy aluminium at the strike price of USD 2,600. This is less advantageous than the initial forward rate, but this optionality is obtained at zero premium. If the cash price falls below the strike but remains above the trigger level, the consumer can walk away from the call and buy the metal at the lower market price. However, if the spot price falls to the trigger level of USD 2,139, the option to buy at the strike of USD 2,600 now becomes an obligation. This means that the consumer will never pay more than USD 2,600 for the metal but can only benefit from a fall in the price to USD 2,139. The payoff is illustrated in Figure 5.12. This transaction is structured using the following components: ▪ Consumer buys a European-style call option with a strike of USD 2,600 at a cost of USD 60.00/tonne ▪ Consumer sells a knock in put option with a strike of USD 2,600 and a trigger level of USD 2,139 at a cost of USD 60.00/tonne If spot does not trade at or below the trigger level, the consumer is left holding the European call. However, if the trigger level trades and the short put is activated, the combination of options creates a synthetic long-buying position, again through the principles of put-call parity (i.e + C − P = + F). The synthetic forward requires the consumer to buy the metal at the strike price of the two options. 5.9.6.3

Basket options

Since an automotive producer may have a requirement to buy several different metals, an option-based risk management strategy based on individual call options could prove to be very expensive.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Decreasing cost Underlying position

Long call option

3,236.1667

3,158.9167

3,081.6667

3,044.4167

2,927.1667

2,849.9167

2,772.6667

2,695.4167

2,618.1667

2,540.9167

2,463.6667

2,386.4167

2,309.1667

2,231.9167

2,154.6667

2,077.4167

2,000.1667

1,922.9167

1,845.6667

1,768.4167

Short knock-in put option

Net position

Increasing cost

FIGURE 5.12 Forward plus structure. An alternative structure that reduces the cost of protection is an option on a basket of metals. In the following example we will consider an equally weighted, two metal basket option based on copper and aluminium. The payoff on this basket option at maturity is: Basket call option: Max [0, (Q1 S1 + Q2 S2 ) − X] Basket put option: Max [0, X − (Q1 S1 + Q2 S2 )] Where: Q = weight of metal within the basket S = price of the metal at expiry X = strike price The strike price of the option, which is set at the start of the deal, is a weighted strike price. That is, the strike chosen for each individual metal is weighted by the proportion it contributes to the basket. Suppose that the basket strike is based on the current observed three-month futures price for both metals with the respective values being USD 2,500 for aluminium and USD 7,000 for copper. The strike rate for an equally weighted basket would be USD 4,750 (50% x USD 2,500 + 50% x USD 7,000). If a consumer were to buy a call option on this particular basket and the final prices at maturity were USD 2,600 and USD 7,100 for aluminium and copper respectively,

153

Base Metals

ignoring premium costs, the value of the basket would be USD 4,850 (50% x USD 2,600 + 50% x USD 7,100). The payout on the option would be USD 100.00 (USD 4,850 − USD 4,750). In the payoff example illustrated above, note that the basket option paid out a total of USD 100.00 for the two metals. Individual call options on each metal would have paid out USD 200.00. Since the payout on the basket is lower than the two individual calls, then the premium cost will be lower. The premium cost of a basket option is based on the premise that the constituent prices will never all rise and fall in tandem. That is, the correlations between the underlying metals in the basket work as a form of a natural hedge. When pricing a basket option, the key difference in the product’s valuation is the implied volatility input, which incorporates the price correlation between the constituent components. Price correlation describes the tendency of prices to move in the same direction and is expressed along a scale from +1 to −1. Positive correlation implies that both asset prices will tend to move in the same direction, whilst assets that have negative price correlation will tend to move in opposite directions. The form of the implied volatility input has been adapted from portfolio theory (see Schofield, 2017) and is expressed as follows for a two-asset basket: √ 𝜎basket = (w2 x1 𝜎x21 ) + (w2 x2 𝜎x22 ) + 2 × (wx1 wx2 𝜌x1 x2 𝜎x1 𝜎x2 ) where: 𝜎x21 = Variance of asset 1 𝜎x22 = Variance of asset 2 𝜌x1 x2 = Correlation between asset 1 and asset 2 𝜎x1 = Volatility of asset 1 𝜎x2 = Volatility of asset 2 wx1 = Proportion of asset 1 wx2 = Proportion of asset 2 If we assume implied volatilities of 20% for aluminium and 25% for copper, the composite basket volatility for a range of different correlation values and the associated premium for a three-month option with a strike of USD 4,750 are: Price correlation −1.0 −0.5 0.0 +0.5 +1.0

Basket volatility

Option premium

2.50% 11.46% 16.01% 19.53% 22.50%

USD 125.00 USD 155.00 USD 181.00 USD 204.00 USD 224.00

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

All other things being equal if correlation increases, the volatility of the option will increase making the option more expensive. Intuitively, if the two assets are positively correlated, then their prices are more likely to move in the same direction, increasing the magnitude of any expected payment to be made by the seller of a call option. Since the premium on an option can be thought of as the present value of the expected payout, this makes the option more expensive. The option will be less expensive where the asset prices are negatively correlated, as price movements will tend to be offsetting, reducing the expected payout. The cost of the basket option can now be compared to the cost of two individual at-the-money forward three-month call options. Aluminium Strike Implied volatility Premium

USD 2,500 20% USD 99.00

Strike Implied volatility Premium

USD 7,000 25% USD 348.00

Copper

The total cost of purchasing two individual call options is therefore USD 447.00, compared to the maximum cost of the basket option of USD 224.00. Note that there is a relationship between the two individual call options’ assets and the basket option priced with a correlation of +1. At this level of correlation, the implied volatility of the basket option is 22.50% equal to the weighted average of the two volatilities of the individual call options. Also, the premium on the basket option is equal to the weighted average of the premiums on the individual options. However, there is a small difference due to the fact that the individual call options were priced with a closed-form model, whereas the basket option was priced with a binomial model, whose output is sensitive to the number of steps used. However, note that the premium on the basket option is always lower than the individual options because of correlation. Even though anecdotally, it may be perceived that prices of metals may move in the same direction, it is unlikely that they will be perfectly positively correlated.

5.9.7 5.9.7.1

Foreign currency exposures Vanilla FX hedge

Suppose that a consumer has entered a three-month fixed forward contract with a bank to sell 1 tonne of copper with the price expressed in EUR. At the time of the transaction

155

Base Metals

the three-month copper price is USD 7,000. Since the trader must quote the sale in a foreign currency, the first step is to reprice the contract in EUR at the current three-month forward FX rate. In this example, the applicable rate is assumed to be €1 = USD 1.20. This will fix the cost of the metal to the client at EUR 5,833. The transaction now leaves the bank exposed to movements in the price of the metal as well as movements in the foreign exchange rate. The hedging of the metal price risk by the bank could be achieved by either buying it forward from another market participant or buying it now and holding it until maturity. In this example, however, we are less concerned with the metal price risk but rather the foreign exchange rate risk. If the bank does hedge the metal price risk, the trader is due to receive EUR 5,833 in three months’ time from the client, but their own cost of procuring the metal will be USD 7,000. If left unhedged the trader will be exposed to movements in the spot exchange rate. For example, if left unhedged and the exchange rate moved to €1 = USD 1.15 then in three months’ time, the bank would receive EUR 5,833 from the client to settle the metal transaction which would then be sold in the FX markets for USD. At this spot exchange rate, the amount of USD received by the bank would be USD 6,708, which is lower than the amount required to settle the forward purchase of copper from the metals market. To illustrate how this could be hedged the different components of the structure are shown in Figure 5.13. Suppose that the following rates are noted in the FX market: ▪ Spot €∕$ = 1.1962 ▪ 3 m EUR interest rates = 0.25%

Metals market $7,000

Cu

€5,833 Forward FX market

€5,833 Bank

Client

$7,000

Cu

€5,833

Lend €@ 0.25%

Spot FX market

Bank

$6,977

Money market

Borrow USD @ 1.50%

FIGURE 5.13 Hedging the FX exposure of a non-USD sale of metal.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

▪ 3 m USD interest rates = 1.50% ▪ 3 m forward €∕$ = 1.20 In the upper part of the diagram the trader executes three transactions: 1. Sells the client their copper at an agreed EUR price of €5,833∕tonne for delivery in three months’ time. 2. Buys copper three month forward at USD 7,000/tonne. 3. Sells the EUR 5,833 proceeds of the client deal in the forward FX market to receive the USD 7,000 equivalent, which can be used to settle the metals transaction. However, conventions in the wholesale FX market mean that it is unlikely that the bank will be able to hedge the FX exposure with a single forward transaction. Since this deal effectively pushes the exposure to spot rates to the other FX counterparty, such trades are executed with a simultaneous spot FX deal. This transaction is shown on the left-hand side of the bottom part of the diagram. The combination of the two FX deals is referred to as an FX swap. Although it is beyond the scope of this textbook to illustrate this, the bank will have a residual risk to the ratio of interest rates between the two currencies. The final part of the diagram on the bottom right-hand side of the figure acknowledges that not only will the bank have to borrow the USD they are required to deliver on the spot leg, but they will also need to lend the EUR received in return. 5.9.7.2

FX-linked commodity swap

This structure allows a non-USD market participant to hedge the FX component of its commodity exposures. These types of swap are sometimes referred to as ‘compo swaps’. A possible structure is outlined in Figure 5.14. To illustrate the example, we will consider the perspective of a Euro-denominated copper consumer, based on a per tonne basis who agrees to a fixed exchange of USD 1.00 = EUR 1.20. Suppose that at the point of settlement on the swap, the appropriate settlement price of copper is USD 6,500 and the spot exchange rate is USD 1.00 = EUR 1.15. It is assumed that the client has a separate commercial contract to purchase the metal in USD. The cash flows on the commercial metal contract are: Sell EUR 5,652 and buy USD 6,500 to purchase one tonne of metal (Fixed volume of commodity * floating USD commodity price) / Fixed EURUSD exchange rate

Non-USD client

Bank

(Fixed volume of commodity * floating USD commodity price) / Floating EURUSD exchange rate

FIGURE 5.14 Commodity-linked FX swap (I).

157

Base Metals (Fixed volume of commodity * fixed USD commodity price) / Fixed EURUSD exchange rate

Non-USD client

Bank

(Fixed volume of commodity * floating USD commodity price) / Fixed EURUSD exchange rate

FIGURE 5.15 Commodity-linked FX swap (II). (Fixed volume of commodity * fixed USD commodity price) / Fixed EURUSD exchange rate

Non-USD client

Bank

(Fixed volume of commodity * floating USD commodity price) / Floating EURUSD exchange rate

FIGURE 5.16 Commodity-linked FX swap (III). The cash flow payable by the bank in the swap is: One tonne ∗ USD 6,500∕1.15 = EUR 5,652 The cash flow payable by the client in the swap is: One tonne ∗ USD 6,500∕1.20 = EUR 5,417 The net result of the swap and the commercial contract means that the client delivers USD 6,500 to its supplier to receive one tonne of metal at a cost of EUR 5,417, i.e. the EUR cost of the copper is fixed at a level of USD 1.00 = EUR 1.20. A similar swap can be offered to the client, which hedges the commodity risk but not the FX risk, and is shown in Figure 5.15. If the client is looking to hedge both the FX and the commodity risks, then it is possible to combine both of the structures into a single swap to reduce the number of cash flows, as illustrated in Figure 5.16.

5.10

SUMMARY

Base metals are one of the most mature commodity markets and, as such, the principles of risk management are well established within the market. Given the multitude of different types of metals that exist within this segment, the issue of pricing is a central theme. As a result, the role of exchanges such as the London Metals Exchange (LME) and the Shanghai Futures Exchange become pivotal in terms of price transparency and discovery.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

The chapter covered most of the common derivative strategies available to participants along the supply chain. The distinct features of the LME in terms of trading and settlement were discussed as well as some of the contracts that are unique to the market (e.g. futures on market premiums). Following on from this section, examples of popular vanilla and structured option solutions were presented. The chapter concluded by considering the nature of the foreign exchange rate risks faced by banks who are willing to offer risk management solutions in non-USD currencies.

CHAPTER

6

Crude Oil

6.1

OVERVIEW OF ENERGY MARKETS

Within commodities, the phrase ‘energy markets’ is often loosely used to describe a series of markets, which include: ▪ ▪ ▪ ▪ ▪ ▪

Coal Renewables Electricity Nuclear Natural gas Crude oil

Another popular term is ‘hydrocarbons’, which is a term that could be used to describe an organic compound that consists of carbon and hydrogen. This would include coal, crude oil, and natural gas. According to the BP Statistical Review of World Energy 2020, (Figure 6.1) the most consumed form of energy is crude oil (33%), followed by coal (27%), and natural gas (24%). Although much publicity is often given to the increase in the use of renewable energy, particularly as a way of reducing the effects of climate change, the overall global consumption figure from this source remains low at 5%. Since each of these energy sources will be measured in different ways, BP creates an element of equivalence by converting them into a standard measure, referred to as millions of tonnes oil equivalent.

6.2

THE VALUE OF CRUDE OIL

The term ‘crude oil’ does not really describe any specific type of oil, rather the generic state of oils prior to their refinement. For example, the price reporting agency, Platts lists approximately 130 traded crude oils, each with different chemical characteristics that are attractive for different reasons. Thus, when extracted from the ground crude oil may be a pale straw-coloured liquid or a thick tar-like substance. The value of crude oil therefore lies in what can be produced from the refining process. For example, crude oil that

159

160

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Hydro 7%

Renewables 5%

Nuclear 4% Crude oil 33%

Coal 27%

Natural gas 24%

FIGURE 6.1 Relative primary energy consumption by fuel type. Source: BP Statistical Review of World Energy 2020. BP PLC is classified as ‘light’, (i.e. composed of short chain hydrocarbons) is sought for its relatively higher yield of gasoline. Sometimes reference is made to ‘conventional’ and ‘unconventional’ oil. Generally speaking, conventional oil comes from sources that are considered to be relatively straightforward to extract using standard methods. Unconventional resources may include sources such as shale oil or tar sands. These are more complex to extract and as a result, production may only be economically viable once prices reach a certain level. However, although shale oil can be ‘light and sweet’ (see following discussion on crude oil characteristics), tar sands are considered to be low value bitumen and will need to be upgraded in order that it will have characteristics similar to conventional crude oil.

6.2.1

Basic chemistry of oil

Crude oil is made up of hydrocarbons which are molecules comprised of hydrogen and carbon atoms. The carbon atoms may be joined in a chain-like sequence or in a ring formation, with different numbers of hydrogen atoms attached. A certain crude oil may actually comprise of several different individual crudes, which are recovered from wells that are geographically close together and therefore share the same extraction facilities. However, the quality of crude oil is not a constant and could change over time, hence different wells may contribute a variable quality in the overall supply. The quality of the

161

Crude Oil

crude oil is established through an assay, which is a laboratory-based assessment of the quality of the crude. The assay will also establish the various boiling point fractions and the percentage of each refined product that a particular crude can yield. Since crude oil is of limited use in itself, its value lies in what can be produced from the refining process. As a result, it would be fair to say that demand for crude oil is effectively refinery demand. In addition, the value of each refined product may be influenced by unique or independent factors. Take for example one of the more popular refined products such as gasoline. The chemical specification may be influenced by factors such as government regulation (perhaps to reduce the lead content), current market prices, local and seasonal demand. When assessing the value of crude oil, several important characteristics are considered.

6.2.2

Density

Density is a measure of the number of molecules within a defined volume. A simple analogy would be to compare a glass of water of a given volume with the same volume of mercury. Although they occupy the same space, the mercury will weigh considerably more than the water due to its greater density. From a crude oil perspective, density will help in quantifying the volume to weight ratio. The density is usually expressed as an API gravity value. This is a measure of the weight of hydrocarbons according to a scale devised by the American Petroleum Institute. Crude oils that have a high API value are less dense (lighter) and tend to produce greater volumes of higher value products (e.g. the so called ‘distillates’ such as gasoline and kerosene) as part of the refining process. Heavy crude oils with a lower API are more difficult to refine in that they require more processing stages and energy, which adds to the cost of production. They also tend to produce lower yields of the higher value lighter products. As a point of reference, water has an API of 10, so a fluid with a lower API is heavier and will sink in water. A fluid with an API greater than 10 is lighter and will float on water.

6.2.3

Sulfur content

Sulfur is an undesirable property when it appears in large quantities. Generally, crude oil will be classified as being “sweet” when the sulfur content is less than 0.5%, although other percentage values are sometimes cited (e.g. 0.7%).‘Sour’ crude is where the content of sulfur by weight is greater than 0.5%. Crudes with a high sulfur content require more processing and a greater energy input to complete the refining process.

6.2.4

Acidity

Acidity is measured using a Total Acid Number (TAN). High acid crudes are those with a TAN greater than 0.7. Acidic crudes can be corrosive to refinery equipment and will require greater investment to process.

162 6.2.5

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Flow properties

Viscosity is a measure of the ability of the crude oil or refined product to flow or its resistance to pouring and can be measured on several different scales at a range of temperatures. Intuitively, it can be thought of as the friction of a liquid. For example, if a golf ball were dropped into a jar of water, the resistance would be less than that experienced if the ball were dropped into a jar of mayonnaise. The pour point measures the lowest temperature at which either crude oil or a particular refined product flows as a liquid under a set of given conditions. A high pour point indicates that the product has to be heated for it to flow as a liquid. This will have an impact on how the oil is stored or transported.

6.2.6

Other chemical properties

Paraffinic – literally ‘like paraffin’, suggests that the crude has a low viscosity and high flammability. This indicates that the crude could be used in the final production of lubricants. (In the UK, paraffin is the name given to kerosene). Naphthenic – a crude oil with naphthenic properties is one that has a high viscosity but is not highly flammable. This might make it suitable for the production of, for example, bitumen. Intermediate – this describes a crude oil, which has properties that sit between paraffinic and naphthenic properties.

6.2.7

Examples of crude oil

Light, sweet, low TAN oils are easier to process and tend to trade at premiums to heavier, higher-sulfur, more acidic crudes which require additional treatment. Examples of the different chemical characteristics of the crude oil that illustrate the principles are: ▪ Light and sweet crude (with an API of between 33–45) are West Texas Intermediate (US crude oil) and Brent (North West European crude oil). Since they also have lower wax content and fewer long chain molecules, they tend to be less viscous and as such they are easier to pump and transport. They are attractive as production and refining costs are lower and when refined will produce an attractive yield of high-value gasoline. ▪ Heavy and sour (an API of between 10–45) crude oils include Urals crude (Eastern European crude oil), which is used as bitumen feedstock. Heavy crudes tend to have a higher viscosity with a consistency that can resemble molasses to even being a solid at room temperature. They can be difficult to pump out of the ground or send through a pipeline and may contain impurities such as sulfur and metals. In its 2018 energy review ENI argue that the most commonly found quality of crude oil was classified as being ‘medium and sour’, which equated to an API of between 26–35 with a sulfur content greater than 1%. This accounted for 41% of all production, while the ‘light and sweet’ category amounted to 19% (Figure 6.2).

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Crude Oil

Heavy and medium sour 2%

Heavy and sour Ultra light 4% 9% Light and sweet 19%

Heavy and sweet 3%

Light and medium sour 5% Light and sour 3% Medium and sour 41%

Medium and sweet 10% Medium and medium sour 4%

FIGURE 6.2 Relative crude oil demand by quality. Source: ENI

6.3

AN OVERVIEW OF THE PHYSICAL SUPPLY CHAIN

The main elements of the crude oil physical supply are: ▪ Upstream activities – this is the exploration, development, and production of crude oil from either an off- or on-shore location. ▪ Transportation and storage – the crude oil must be moved by pipeline or by tanker to a particular refining location. If the refinery is close to the extraction point, the oil can be stored locally prior to delivery or can be loaded onto ships for onward delivery. ▪ Refining – as crude by itself is of limited use, it must first be refined into a variety of products such as gasoline. ▪ Retail and wholesale distribution – the refined products can then be sold and delivered to the specific location for a wholesale purchaser (e.g. a particular airport for an airline buying jet fuel) or to a network of retail petrol/gas stations. This part of the supply chain can sometimes be referred to as the ‘marketing’ function. ▪ End consumer – either a retail participant (e.g. gasoline) or a wholesale client. The main market participants will either be international oil companies (IOCs), which are privately owned companies such as BP or state-owned national oil companies (NOCs) such as Saudi Aramco. Although the privately owned companies are amongst

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the largest corporates in the world (e.g. ExxonMobil), they are dwarfed in size by the NOCs. There are also ‘independents’ that are primarily active in individual segments of the market such as exploration, production, and storage. Vertical integration is common along the supply chain, but it is not necessarily the preserve of the private oil company. For example, Saudi Aramco is vertically integrated with interests in exploration, production, refining, marketing, and international shipping. Other relevant parties who trade in the market are financial institutions providing risk management solutions to supply chain participants and the commodity trading houses (e.g. Vitol and Mercuria). Commodity trading companies sell to industrial consumers obtaining their products either from third party sources or production assets they own. They may also engage in more speculative ‘view driven’ trading strategies. Crude oil and the refined products are stored at oil depots, which are also sometimes referred to as tank farms, installations, and oil terminals. From here they are transported to the end users or to other storage facilities. They may be located close to oil refineries, marine terminals, or at the terminus of a pipeline. Traditionally crude oil and the refined products are moved mostly by ocean going tankers and pipelines. Initial construction costs on pipelines are higher than ships but offer lower variable costs. Where there are alternatives then pipelines, which tend to be privately owned, is the preferred method of transportation. Tankers used for liquid fuels are classified according to their capacity using the AFRA system (average freight rate assessment) and whether they will carry crude oil (referred to as ‘black’ products) or refined products (‘white’ products). The following classifications are most commonly used for the oil market and are expressed in terms of their dead weight tonnage (dwt – the weight in metric tonnes of the cargo, stores, fuel, and crew): 10,000–60,000 60,000–80,000 80,000–120,000 120,000–200,000 200,000–315,000 320,000–550,000

Product tanker Panamax Aframax Suezmax VLCC (Very Large Crude Carrier) ULCC (Ultra Large Crude Carrier)

As indicated by the names, some of the tankers when fully laden can traverse two key shipping routes, the Suez and Panama canals. In terms of barrels of oil, a VLCC can carry about two million barrels, while the ULCCs are able to cope with twice that volume. The Product and Panamax tankers are mostly used for the transport of refined fuels. Where there is a suitable network of rivers or inland waterways, oil products can be transported across large distances from the coastal refineries to supply domestic markets. Such a system exists in North West Europe utilising the main river arteries and their tributaries to supply local depots. The Rhine, the Seine, the Maas, and the Danube all have significant oil barge traffic supplying central Europe. Barges move much smaller quantities than tankers, typically between 1,000–3,000 metric tonnes.

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Crude Oil

6.4 6.4.1

REFINING CRUDE OIL What is refining?

From a chemical perspective no two crude oils are the same. They are a mixture of hundreds of different types of hydrocarbons (e.g. naphthenes and aromatics) with carbon chains of different lengths, which are separated through the refining process.

6.4.2

What does a refinery produce?

Table 6.1 illustrates the main refined products with some typical uses.

6.4.3

Product yields

Refiners talk of a ‘product yield’ or a ‘product slate’, which describes the different proportions of refined products obtained from refining one barrel of crude oil. Yields may vary slightly over the year if the refiners have the flexibility to respond to changing market demand. On average, a 42-(US) gallon barrel of crude oil will yield about 45 gallons of refined products as the refining process generates a ‘refinery gain’. A tonne of heavy crude oil will occupy a smaller space than a tonne of lighter crude. When the heavy crude is therefore refined into a series of ‘lighter’ refined products, they will occupy a larger TABLE 6.1 Refined products and their applications. Gases and gas liquids – the most significant products in this category are methane, ethane, and propane. Methane is commonly referred to as natural gas and can be used for heating. Ethane is a feedstock for the petrochemical industry that can be used in the production of plastics. Propane may be used for cooking and heating purposes. Naphtha – is most commonly used as a petrochemical feedstock. It can also be used as a solvent in dry cleaning fluids and in paint solvents. It is also an intermediate product that could be further processed to make gasoline. Gasolines – the main use of gasoline is to fuel motor vehicles. The gasoline will need to be of a certain specification, the most widely known being the octane number, which is frequently displayed on the forecourts of petrol stations. There are two ways of measuring this factor: The Research Octane Number (RON) or the Motor Octane Number (MON). Irrespective of which method is used, the higher the octane value the better the quality of the gasoline. Kerosene – the principal use of kerosene is to produce jet fuel, which, similar to gasoline, will have different formulations. In some parts of the world kerosene is used for cooking and lighting. Gas oils/Diesel distillate – these are used to produce diesel engine fuels and for households that use oil as a source of heating. Fuel oils – these are often used as a source of fuel for the power requirements of refineries and power stations. They can also be used as fuel for ships, in which case it is termed ‘bunker fuel’. (A bunker is simply a container in which the fuel for the ship is stored.) Specialty products/Residuals – these include solids such as coke, asphalt tar, and waxes. Typically, the lowest value products produced from the refining process.

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volume for the same weight. Hence it is possible for production of refined products on a per barrel basis to exceed that of crude oil. However, if the values are expressed on a per tonne basis, one tonne of crude could never produce more than a tonne of refined products. For 2017, the US Energy Information Administrations (EIA) provided a breakdown of the different products made from a single barrel: ▪ ▪ ▪ ▪ ▪ ▪ ▪

Gasoline – 20 gallons Ultra-low sulfur distillate (e.g. diesel fuels) – 11 gallons Other products – 6 gallons Jet fuel – 4 gallons Hydrocarbon gas liquids – 2 gallons Heavy fuel oil – 1 gallon Other distillates (e.g. heating oil) – < 1 gallon

On a national scale, the EIA produces annual statistics that show the type of products produced within the USA (Figure 6.3).

6.4.4

How does a refinery work?

No two refineries are the same and their complexity will vary according to their ability to create a high-value product. The first stage of the refining process is fractional distillation. Crude oil is pumped through a furnace to release different liquids and gases, Petroleum coke Refinery gases 8% 5%

Fuel oil 31%

Gasoline 46%

Jet fuel 10%

FIGURE 6.3 US refinery yields. Source: EIA

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Crude Oil

which are then fed into a distillation tower. Inside the tower the liquids and gases separate into different components (referred to collectively as ‘fractions’ or ‘cuts’) each with a different boiling point. The component with the lowest boiling point evaporates first and rises highest in the tower, whilst that with the highest boiling point evaporates last and is collected at the base of the tower. The longer the carbon chain, the higher the boiling point. From the top of the distillation tower downwards the following components (Table 6.2) are collected: TABLE 6.2 Refined products from crude oil. Temperature (∘ C)

Refined Product

Less than −45 −45–35 35–150 150–230 230–340 340–400 More than 400

Gas Liquid Petroleum Gas Gasolines and Naphtha Kerosene Gas oil Heavy gas oil Residue / Fuel oil

Once the crude has been separated into its fractions there is a second stage where they are converted into intermediate products. Some of the fractions such as liquefied petroleum gas may not require much conversion. Depending on the configuration of the refinery, different fractions can be converted into more valuable products. For example, if there is a high demand for gasoline, it can be produced from either naphtha or gas oil, while diesel fuel could be made from either diesel distillate or gas oil. One of the conversion techniques used is referred to as ‘cracking’ as it takes the heavy hydrocarbon molecules (i.e crudes with high boiling points) and breaks them down into lighter products such as diesel and gasoline. Although there are several variants of the conversion process (e.g. fluid catalytic cracking, hydro-cracking) the techniques use a combination of heat, pressure, and a catalyst to achieve the required chemical reaction. The third stage of the refining process purifies the product by removing pollutants and contaminants. The final stage of the refining process involves modifying the intermediate products into the form in which they will actually be consumed. Different fractions and other components are combined to produce finished products that have specific properties. Products such as gasoline will have very tight formulation guidelines that might be specified by law.

6.4.5

Refinery optimisation

Oil refiners function by converting crude oil into finished products with the aim of maximising their net income. In the jargon of the refiner this is referred to as the ‘gross product worth’ or ‘gross production value’. However, to achieve this objective

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the refinery must optimise their operations to get the biggest bang for their buck. Optimisation will need to consider: ▪ Which types of crude oil the refinery can process – some refineries may be able to process several crude oils or may be restricted to a very narrow range. This may be a function of their location. For example, an inland refinery, served by a pipeline, may only be able to take a single type of crude oil, whereas a coastal refinery may have flexibility to receive a variety of different ship-transported oils. ▪ The yield from the crude – the proportion of each refined product that can be made from a particular type of crude oil, which can be established by means of an assay. ▪ The configuration of the refinery – the way in which the refinery has been set up so products can be made. For example, the refinery may choose different ‘cut points’ (the different temperatures at which the refined products are collected). ▪ Relative demand and supply for refined products – although refineries may lack complete flexibility to produce a diverse product slate, it may be possible to alter the proportions of what is produced to meet market demand. To illustrate the principles, consider the following simple example. Suppose a European refinery is configured such that it can accept two types of crude oil: Forties and Oseberg. The oils are trading at USD 64.15 and USD 63.45 a barrel, respectively. The refinery output (and their current market prices) consists of gasoline (USD 558.00/ metric tonne (MT)), jet fuel (USD 582.00/MT), gas oil (USD 615.00/MT) and fuel oil (USD 350.00/MT). In order to optimise their production the refinery will need to know what product yields can be derived from their source crude oils. A hypothetical set of product yields is shown in Table 6.3. As is common with refined products the unit of trading (e.g. metric tonnes) may be different than that of the source crude (e.g. barrels). The following conversion factors have been used to convert metric tonne prices to their barrel equivalent and based on common market conventions1 . Gasoline Jet fuel Gas oil Fuel oil

8.35 7.88 7.46 6.35

TABLE 6.3 Hypothetical product yields from two types of crude oil.

Gasoline Jet fuel Gas oil Fuel oil 1

Forties

Oseberg

35% 10% 20% 35%

25% 15% 15% 45%

The conversion factors are taken from BP’s annual statistical review of the energy markets which can be accessed via their website.

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Crude Oil

TABLE 6.4 Gross product worth and associated profit margins.

Gasoline Jet fuel Gas oil Fuel oil Gross product worth Cost of crude oil Profit margin

Forties

Oseberg

23.39 7.39 16.49 19.29 66.55 64.15 2.40

16.71 11.08 12.37 24.80 64.95 63.45 1.50

Table 6.4 Simplified calculation of a refineries gross product worth and overall profit margin are expressed in USD. Operating costs are ignored for ease of illustration. The gross product worth (GPW) and the associated profit margins are shown in Table 6.4. For ease of illustration, all operating costs have been ignored. The calculation for gasoline refined from a barrel of Forties is: USD 558.00∕8.35 × 35% = USD 23.39 So, the income from gasoline on a per barrel basis is USD 66.82 (USD 558.00/8.35) and 35% of a barrel of Forties is refined into gasoline resulting in revenue of USD 23.39. The GPW is calculated as the sum of the revenue generated from the sale of the refined products. The margin is the GPW minus the cost of the crude oil. Based on this simple analysis, although Forties was trading at a higher price, the refiner should logically choose this oil as it generates the greatest margin.

6.4.6

Refinery yields and relative crude oil prices

One of the features of the crude oil market is that most crude oils are traded as a differential to a benchmark oil such as Brent or West Texas Intermediate (WTI). These light sweet crudes will tend to trade at a premium to heavy sour blends such as Urals (Russia) or Maya (Mexico). In theory, the difference in price should be reflective of the different value of the product slate produced from refining the different crudes. So if the refined products produced from refining WTI return a value that is USD 5.00 higher than that from the distillation of a grade such as West Texas Sour (WTS) Midland then it would seem reasonable to assume the latter would trade at a USD 5.00 discount to the former. Another way of looking at this differential is as a breakeven value. It represents the discount that would need to exist such that the refiner could generate the same margin from processing the benchmark crude as an alternative fuel. This would suggest that at the discounted price the refinery would be indifferent between running the alternate crude or the benchmark crude.

6.4.7

Measuring profitability

Generally, refining capacity has increased over the last few years (Figure 6.4).

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120,000 Africa S & C America CIS

100,000 80,000

Middle East Europe

60,000

N America

40,000 20,000

Asia Pacific

0 19 20 17 20 15 20 13 20 11 20 09 20 07 20 05 20 03 20 01 20 99 19 97 19 95 19 93 19 91 19 89 19 87 19 85 19 83 19 81 19 79 19 77 19 75 19 73 19 71 19 69 19 67 19 65 19

FIGURE 6.4 Global refining capacity 1965–2019. Thousands of barrels daily. BP Statistical Review of World Energy 2020. BP PLC. The figure shows that although the refining capacity of some countries has not changed much (e.g. USA), other regions such as Asia Pacific have invested significantly. It is very common for the reference to be made ‘refining margins’, which are calculated in a similar fashion to those illustrated in Section 6.4.5. Since it has been argued that every refinery is different, it would be incorrect to say that there was a single margin value that would apply to the entire industry. So, it is common for price reporting agencies to publish ‘indicator’ margins, which are essentially a generalised representation of the health of the downstream oil sector. They are more commonly referred to as ‘crack spreads’. In order to calculate these generic values, some assumptions have to be made about how a ‘typical’ refinery in the respective region would be configured. Figure 6.5 shows three such generic margins: ▪ US Gulf Coast sour cracking, ▪ Singapore medium sour hydrocracking, ▪ North West Europe light sweet cracking. A 3-2-1 crack spread assumes three barrels of crude oil could be refined into two barrels of gasoline and one barrel of fuel oil. This could be also be expressed as 1:0.67:33. Suppose that crude oil is trading at USD 50.00/bbl., while gasoline is trading at USD1.40/gallon and heating oil at USD 1.20/gallon. Assuming there are 42 gallons in a barrel, the crack spread is therefore the sum of the refined products minus the cost of the crude oil. = Gasoline + heating oil − crude oil = (USD 1.40 × 42 × 0.67) + (USD 1.20 × 42 × 0.33) − USD 50.00 = USD 39.40 + USD 16.63 − USD 50.00 = USD 6.03

171

Crude Oil $30 $25 $20 $15 $10 $5 $0

3Q 0 2Q 0 0 1Q 1 0 4Q 2 0 3Q 2 0 2Q 3 0 1Q 4 0 4Q 5 0 3Q 5 0 2Q 6 0 1Q 7 0 4Q 8 0 3Q 8 0 2Q 9 1 1Q 0 1 4Q 1 1 3Q 1 1 2Q 2 1 1Q 3 1 4Q 4 1 3Q 4 1 2Q 5 1 1Q 6 1 4Q 7 1 3Q 7 1 2Q 8 19

-$5

USGC Medium Sour Cracking

Singapore Medium Sour Hydrocracking

NWE Light Sweet Cracking

FIGURE 6.5 Refining margins 2000–2019. USD/bbl. Source: BP Statistical Review of World Energy 2020. BP PLC. It is also possible to measure product cracks. They would represent the added value of converting, say, a barrel of heating oil into something more valuable such as gasoline.

6.4.8

Drivers of refinery performance and profitability

Almost by way of summary, the following factors would have an impact on refinery profitability and performance. In very simple terms it is useful to consider those internal factors over which the refinery has some control and external factors that are more reflective of macroeconomic trends. Internal factors ▪ The value of the product slate that is produced. ▪ The choice of crude oil to be used in the refining process. ▪ How the refinery is configured in relation to what type of crude oil it can process, and which refined products are made. ▪ The reliability and efficiency of the plant. ▪ The location of the refinery will affect how much it costs to ship the freight and the resultant products. ▪ The ability to produce specialty products with higher margins. ▪ Operating costs such as labour. ▪ Level of the refiner’s own inventories. External factors ▪ Demand for refined products. ▪ The general level of inventories held by the market. Typically, there is an inverse relationship between the level of inventories and price.

172 ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Seasonality of demand. Crude oil prices. Ability to import or export products to manage a surplus or deficit. Possibility to substitute one fuel for another. Change in domestic product specifications. Advent of new technology. Change in relative demand (e.g. gasoline vs. diesel). Weather.

6.5

THE DEMAND FOR AND SUPPLY OF CRUDE OIL ‘ . . . as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know’. —Donald Rumsfeld

6.5.1

Proved oil reserves

According to BP’s statistical review of world energy (2020), proved oil reserves are ‘generally taken to be those quantities that geological and engineering information indicates with reasonable certainty can be recovered in the future from known reservoirs under existing economic and operating conditions’. Figure 6.6 shows the different regional proportions of proved reserves as of 2019, while Figure 6.7 shows how these reserves have evolved over time. Figure 6.6 shows that the vast majority of proved reserves exist in the Middle East. However, the charts indicate that despite anecdotal concerns over the scarcity of crude oil, the apparent level of reserves is increasing. At the end of 1980, the total recorded figure was 684 thousand million barrels (tmb) but had risen to 1,734 tmb by the end of 2019. It may seem puzzling to hear stories of declining oil reserves and then see such contradictory data as presented here. However, the definition of reserves would suggest that an increase in price and/or the implementation of new technology might account for the increase.

6.5.2

R/P Ratio

The Reserves to Production (R/P) ratio indicates the length of time (in years) that a country’s remaining reserves would last if production were to continue at current levels. It is calculated by dividing the reserves remaining at the end of a year by the production in that year. The data used in the first edition of the book (2005) indicated that on a global basis, the values would suggested there would be sufficient reserves for another 41 years of consumption at production levels that prevailed at the time. Using the 2019 figures, that value has increased to about 50 years. This means that the number has

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Europe 4% Africa 13%

Middle East 23%

CIS 8%

N America 8%

S & C America 44%

FIGURE 6.6 Relative proved reserves by region 2019. BP Statistical Review of World Energy 2020. BP PLC.

2000 Europe Asia Pacific Africa

1800 1600

CIS

1400

N America

1200 1000

S & C America

800 600 400

Middle East

200 0

18 20 16 20 14 20 12 20 10 20 08 20 06 20 04 20 02 20 00 20 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 19 80 19

FIGURE 6.7 Evolution of proved reserves 1980–2019. Thousand million barrels. BP Statistical Review of World Energy 2020. BP PLC.

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Asia Pacific Africa Middle East CIS Europe S & C America North America 0

20

40

60

80 2004

100

120

140

160

2019

FIGURE 6.8 R/P ratios in 2004 compared to 2019. Source: BP Statistical Review of World Energy 2020. BP PLC. to be treated with some caution and is only a snapshot at any point in time. It may change if new reserves are found or if demand for oil declines due to an increased use in alternative sources of energy. Figure 6.8 shows how the R/P ratio has changed on a regional basis when comparing 2004 with 2019.

6.5.3

Production of crude oil

Figure 6.9 shows that between 1965 and 2019, production of crude oil rose from an annual figure of 31,799 in 1965 to 95,192 thousand barrels daily (tbd) by 2019. Figure 6.10 illustrates the different proportions of production on a regional basis as of the end of 2019. One of the simple messages to highlight is that there is a big difference between the location of the reserves and production. So, although South and Central America have 19% of the world’s proven reserves, they only account for 6% of global production. In Section 6.4.5 it was argued that most crude oils are priced relative to a particular benchmark. Peak production for one of the key benchmarks (Brent, North Sea oil) was reached in 1999 with a total of 2,909 thousand barrels per day (mbd), which made up about 2.5% of the total world production. By the end of 2019, this figure had fallen to just 1,118 mbd, amounting to just over 1% of world production. This has called into question whether this particular stream of crude oil is truly representative of the global demand and supply trends. Figure 6.10 also shows the impact of shale oil on the US market as growth rates for US crude production in the decade 2008–2018 were 8.5%; this after a period in which US production rates had been falling.

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Crude Oil

120,000

100,000

Europe S & C America Asia Pacific

80,000

Africa 60,000

CIS

40,000

N America

20,000 Middle East 0 19 20 17 20 15 20 13 20 11 20 09 20 07 20 05 20 03 20 01 20 99 19 97 19 95 19 93 19 91 19 89 19 87 19 85 19 83 19 81 19 79 19 77 19 75 19 73 19 71 19 69 19 67 19 65 19

FIGURE 6.9 Evolution of crude oil production between 1965 and 2019. Thousand barrels daily. Source: BP Statistical Review of World Energy 2020. BP PLC.

S & C America 6%

Europe 4%

Asia Pacific 8%

Middle East 32%

Africa 9%

CIS 15% N America 26%

FIGURE 6.10 Relative crude oil production by region. Source: BP Statistical Review of World Energy 2020. BP PLC.

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6.5.4

Consumption of crude oil

Figure 6.11 shows the consumption of crude oil over time on a regional basis, while Figure 6.12 presents the proportion of regional consumption for the end of 2019. The significant facts are: ▪ The consumption of crude oil has continued to rise globally. ▪ Asia-Pacific is the largest single consuming region, accounting for 37% of the total world consumption. ▪ China continues to consume more oil on an absolute and percentage basis. For example, in 2005, China consumed about 8.5% of world production. By 2019, it consumed about 14% of a greater overall consumption amount. ▪ There is a mismatch between the location of reserves, the amount produced, and the amount consumed. So, although the Middle East has 23% of proved global reserves, it produces over 32% of the world’s crude oil and only consumes 10% of the total.

6.5.5

Crude oil trade

One of the themes highlighted in the previous section is that the location of oil reserves, where it is produced and where it is consumed can differ significantly. This gives an 120,000

100,000

80,000

Africa CIS S & C America Middle East Europe

60,000 N America 40,000

20,000

Asia Pacific

0

19 20 17 20 15 20 13 20 11 20 09 20 07 20 05 20 03 20 01 20 99 19 97 19 95 19 93 19 91 19 89 19 87 19 85 19 83 19 81 19 79 19 77 19 75 19 73 19 71 19 69 19 67 19 65 19

FIGURE 6.11 Evolution of crude oil consumption on a regional basis. 1965–2019. Thousand barrels daily. Source: BP Statistical Review of World Energy 2020. BP PLC.

177

Crude Oil

S & C America 6%

CIS 4%

Africa 4%

Asia Pacific 37%

Middle East 10%

Europe 15%

N America 24%

FIGURE 6.12 Relative consumption of crude oil 2019. Source: BP Statistical Review of World Energy 2020. BP PLC. insight into the nature of the international trade for crude oil. Figure 6.13 shows some of the regional flows of crude oil. For presentation purposes the diagram shows the main regional flows of crude oil and illustrates how certain areas (e.g. West Africa and the Middle East) will transport crude oil to those regions with the greater demand (USA, Europe, and China).

6.5.6

Demand for refined products

The BP statistical review provides a regional breakdown of the demand for the refined products (Figure 6.14). Three of the categories are: ▪ Light distillates – aviation and motor gasolines and light distillate feedstock. ▪ Middle distillates – jet and heating kerosenes; gas and diesel oils. ▪ Fuel oil – marine bunkers and crude oil used directly as fuel. Perhaps somewhat unsurprisingly, the demand for light and middle distillates dominates all the other categories.

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FIGURE 6.13 Inter-regional movements of crude oil. Million tonnes. Source: BP Statistical Review of World Energy 2020. BP PLC.

Africa CIS Middle East S & C America Europe N America Asia Pacific 0

2,000

4,000 Fuel oil

6,000

8,000

Middle distillates

10,000

12,000

14,000

Light distillates

FIGURE 6.14 Regional consumption of different refined products. Thousand barrels daily. Source: BP Statistical Review of World Energy 2020. BP PLC.

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Crude Oil

6.5.7

Security of supply (and demand)

One of the key themes in most energy markets is the security of supply. This can be interpreted in a number of ways but at a simple level if can be thought of as the ability of any country to ensure there is a sufficient ongoing supply to meet expected demand. One of the ways in which this can be achieved is by diversifying the sources of supply. The largest individual crude oil importers as of 2019 are: ▪ Europe: 522 million tonnes ▪ China: 507 million tonnes ▪ USA: 338 million tonnes For each of those countries the three main sources of supply are (in descending order of volume): ▪ Europe: Russia, Other CIS, West Africa; ▪ China: Middle East, West Africa, Russia; ▪ USA: Canada, South and Central America, Saudi Arabia. Likewise, producers of crude oil are equally sensitive to changes in demand patterns and should therefore have several different supply destinations. Examples of a concentration of supply include Russia, whose main export location is Europe.

6.6

PRICE DRIVERS ‘Oil is not ours, it’s theirs. You don’t find oil in Switzerland; when prices go up, everyone wants to share the bonanza’. —Paolo Scaroni, Chief Executive of ENI

There are several factors that drive the price of crude oil. For convenience, the issues have been collated under three generic headings: supply chain considerations, geopolitics (i.e. the study of relationships between nations), and macroeconomic issues. In addition, there will be a series of factors that influence the demand and supply for the various refined products, which may feed back to the price of crude oil. Ultimately, the market for crude oil is demand led with money flowing to the producing countries.

6.6.1

Macroeconomic issues

Economic Activity If there is strong growth in Gross Domestic Product (GDP), signifying increased economic activity, then it is likely that the price of crude oil will increase accordingly. This may also have another effect in that if consumers believe that prices will be higher in the future, they may be tempted to buy forward. Sellers on the other hand will be happy to enjoy the benefits of a higher price and may remain unhedged.

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Reserves and production Arguably, the most contentious question that arises with respect to crude oil is how much is left? Undeniably, crude oil is a finite resource, which at some point will be exhausted. When discussing this issue, reference is often made to the concept of Hubbert’s peak. Hubbert, a US geologist, predicted in the 1950s that US crude oil production would peak in the early 1970s; according to BP’s annual energy review, an apparent peak was reached in 1972 (11.1 m barrels a day). Thereafter US production declined until 2008 (6.8 m barrels a day). However, the introduction of shale oil production led to a substantial increase and by the end of 2019, the US was producing just over 13 m barrels daily. On a global scale after a decline in the early 1980s production has generally increased (see Figure 6.15). For existing wells, the issue is more of how to extract what remains, and as a rule of thumb, reservoir recovery rates are about 30%, but this could vary considerably (e.g. 10–70%). At a very simple level it has to be economically viable for a producer to recover what is remaining. Although this will be a function of several variables, it would seem reasonable to suggest that a producer has to earn an acceptable return on capital invested to make such extraction worthwhile. This means that the effectiveness of technology to retrieve the oil and the price they will receive for it plays an important role. There will also be known reserves that are difficult to access but with improved technology, and an increasing price, may become worthwhile to extract. Then there is ‘unknown’ technology where economic circumstances may act as a spur for further innovation that is at present inconceivable. It also may be that there are large reserves that are as yet undiscovered. Despite the oft made remark that the world is getting smaller, there are large areas of many existing oil producing countries that remain un-surveyed in terms of potential oil production. As a result, companies will continue to search for oil in the hope that they discover a major reservoir, sometimes referred to in the industry as an ‘elephant field’. 120,000 100,000 80,000 60,000 40,000 20,000 0 19 20 17 20 5 1 20 3 1 20 11 20 9 0 20 7 0 20 05 20 3 0 20 1 0 20 9 9 19 97 19 5 9 19 3 9 19 91 19 9 8 19 7 8 19 85 19 3 8 19 1 8 19 9 7 19 77 19 5 7 19 73 19 1 7 19 69 19 7 6 19 5 6

19

FIGURE 6.15 Global oil production. 1965–2019. Thousand barrels daily. Source: BP Statistical Review of World Energy 2020. BP PLC.

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Availability of Strategic Reserves The USA maintains a Strategic Petroleum Reserve, which was designed to provide the country with an emergency supply of crude oil. It is a US government complex that consists of four sites with deep underground storage caverns created in salt domes along the Texas and Louisiana gulf coast. The reserve can hold some 727 million barrels. Possibility of substitution One of the effects of the substantial rise in oil prices in the 1970s was that it ultimately encouraged oil users to switch to alternative sources, notably to natural gas. This movement away from crude oil was partly responsible for the low crude oil prices of the 1980s. With the prospect of many carbon fuels being eventually exhausted and 65% of each barrel of oil being consumed by the transport sector, many oil companies are now attempting to diversify into alternative sources of energy. As the price of crude oil rises and concerns over climate change increase, there is an incentive to switch to alternatives such as biofuels (ethanol), gas-to-liquids technology (a process that can be used to turn gas or coal into products normally produced from crude oil), hydrogen fuel and fuel cells, solar energy, nuclear power, and wind and wave technology. The use of hydrogen as a replacement for gasoline has been mooted as a substitute due to the lack of side effects. Hydrogen is added to a fuel cell and mixed with oxygen, which chemically reacts to produce electricity. This powers an electric motor, which propels the car. The resultant exhaust comprises nothing more than water or vapour. Even this technology is not without problems as one of the likeliest sources of hydrogen is expected to be natural gas. To date production of the cars in significant numbers has not transpired to date. A major obstacle to its development is the significant cost of the attendant global refueling infrastructure. A rising oil price may encourage users to seek out alternative products, but it may also encourage companies to look for oil in remote parts of the world and even in deep-water areas. One of the more unconventional areas of development is the Canadian oil sands of Alberta. Oil sands generally refer to mixtures that have the consistency of molasses but may comprise several organic materials such as bitumen. Bitumen has naphthenic properties in that it has a high viscosity and is not particularly flammable. The API gravity of the bitumen found in the Canadian oil sands varies between about 7–13, while the sulfur content is 4–6%. Once recovered from the earth, it is upgraded to heavy crude oil before being transported along pipelines to a refinery where it can be processed and refined. The attractiveness of the project is that it offers a source of crude oil supply many times greater than that of Saudi Arabia. However attractive this may seem, there are some drawbacks. Two tonnes of oil sands yield about 1.25 barrels of bitumen and a single barrel of crude. Secondly, the energy required for extraction is considerable and would consume a large proportion of the country’s natural gas output. The extraction process also requires a significant amount of water and there are the related issues of origin, storage, and transport. In addition, the environmental issues of restoring the countryside to its natural state can no longer be ignored.

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Price of other crude oils Since most crude oils are priced as a differential from a series of core marker crudes such as WTI and Brent, movements in one of the market crudes will have a knock-on effect to the remaining market Demand for refined products Each refined product will have its own unique supply and demand dynamics and in some cases, these may feed back into the crude oil market. For example, in winter crude oils that are favoured to produce heating oils will gain in value, while a similar effect is seen in the summer for the crude oils that yield larger amounts of gasoline. Taxation In the late twentieth century, European governments gave drivers substantial tax incentives to buy diesel-powered cars partly in the belief they emitted fewer greenhouse gases. This led to an increase in the proportion of diesel cars sold in Europe and as a result, consumption of diesel increased accordingly. However, the increase in demand was not matched by a similar investment in refining technology that would allow the conversion of heavier fuel oils to the more attractive middle distillates such as diesel. As a result, diesel prices rose above those for gasoline. At the time of writing, there has been some negative publicity over the environmental impacts of diesel, which has subsequently led to a reduction in demand for this type of vehicle. Similarly, some governments have introduced subsidies to encourage drivers to switch to electric vehicles. The pump price of gasoline is made up of several components: ▪ ▪ ▪ ▪

The cost of the crude oil. The refinery’s margin. Taxation. Sales margins.

The taxation of gasoline is always a politically sensitive subject, which in some countries has given rise to civil unrest. The level of taxation could have an impact on consumer behaviour, which could feasibly feed back along the supply chain. Transportation trends This could manifest itself in several ways: ▪ A shift away from diesel cars. ▪ An increase in demand for electric vehicles (EVs). ▪ Changes in regulation that impact the technical specification of a particular type of fuel (e.g. sulfur limits in fuel oil). For example, if there is an increase in EVs, then one might expect a decrease in the demand for gasoline and hence crude oil and an increase in demand for those fuels that are required to produce electricity (e.g. coal and natural gas).

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Investor and speculative activity A key theme over the last few years has been changing interest shown in commodity markets by financial participants. Given the size of their interest and money flowing into the market, their activities are often cited as being responsible for creating both upward and downward price spirals. Since most investors would be reluctant to take delivery of the physical commodity, the most popular method to take exposure to commodities is by the futures market. However, some funds may be constrained in their ability to transact futures and so exposure is taken via a total return transaction. Here the investor enters into an agreement with an investment bank where they receive a cash flow that mimics the return on a commodity index such as the S&P GSCI®. This index takes its value from the prices of several commodity futures and has a significant crude oil weighting. Although the nature of the index will be considered in more detail in a subsequent chapter, the ‘rolling’ of futures contracts generates part of the return to an investor. The futures roll describes the process of selling the front month contract (the ‘prompt’ contract) as it approaches maturity and buying the next delivery month to maintain exposure to the commodity. With significant investor inflows into the index, this activity can be significant and may result in an element of distortion in the shape of the short end of the forward curve. Investment in the S&P GSCI is essentially passive in nature as the index is compiled according to a predetermined set of rules. It is attractive to ‘real money’ accounts such as pension funds and mutual funds as it represents an unleveraged ‘long only’ futures investment. Active investors (such as hedge funds or commodity trading advisors) may consider an index approach somewhat restrictive and seek to earn an enhanced return that exceeds the performance of the index. Index investors will earn a return equal to the market, which is sometimes referred to as ‘beta’. Active investors try to outperform the index, the enhanced return being referred to as ‘alpha’. Speculative activity has long been seen as some form of evil that causes commodity prices to move from some notion of ‘fair value’, which of course is never actually revealed. This takes us back to the issues of price formation, which were considered in Chapter 2 using the toddler and robot argument. The author feels that it is fair to say that it is likely that speculative flows may have some impact on prices, but it would be incorrect to say that they are always the dominant factor. If they were, then all the other factors influencing price would have to have very little impact, which is unlikely. Movement of the USD Like most commodities, crude oil is priced in US dollars, and so a weakening of the currency should lead to an increase in the demand for the commodity from non-dollar users, as the cost is now lower in domestic currency terms. Weather Weather and other seasonal factors will also play an important role in the balance of demand and supply. An obvious example would be the increase in demand for

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heating oil during winter. The US ‘driving season’, which extends roughly from June– September is a period where demand for gasoline increases as people take vacations. Another impact of weather is that very severe events such as hurricanes may impact production and refining capabilities.

6.6.2

Supply chain considerations

Upstream production This is the capacity at the point of (on- or offshore) extraction. Some large producers have chosen to keep a certain amount of idle capacity to respond to any sharp increase in demand. Typically, Saudi Arabia has retained sufficient capacity to meet any temporary upswing in demand, but this should not suggest that they have an infinite capacity to be able to perform this function. Indeed, their spare production capacity is in the heavier crudes with higher sulfur content. This will only be of use if there is sufficient refining capacity for this type of crude oil. Like many industries, the impact of technology will have an impact on production. Generally, only about 30% of oil is recovered2 from a particular well as it is not always cost effective. As technology improves, it is likely that the amount of oil that can be extracted will increase. Costs of production There are three main categories of cost in producing a barrel of oil. Exploration costs capture the cost of finding the oil (e.g. exploration and appraisal drilling). Development costs include the procurement of equipment, facility construction, drilling, engineering, and project management. Operating costs are essentially the day-to-day expenses of running the site. The Wall Street Journal (2016) looked at the average cash cost to produce a barrel of oil, which varied from about USD 9.00/bbl. for Saudi Arabia to USD 44.00/bbl. for the UK. Oil field Activity Market participants closely monitor current production to identify any possible supply disruptions. For example, a monthly count of all rotary rigs is published, while the maintenance of existing fields is also closely scrutinised. Refining capacity If there is a sudden increase in demand, there may not be sufficient physical refining capacity resulting in an increase in the price of oil. The construction of oil refineries has a very long lead-time, is expensive, and must overcome many environmental considerations. For example, expansion of an existing facility could take at least two years while

2

Recovery rates can vary considerably from about 10–80%.

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construction of a new refinery, upwards of five years. In the USA in 1981, there were 325 refineries with a total capacity of 18.6 million barrels a day. By late 2005, there were 148 refineries, and by 2017 this fell to 135. Global estimates suggest there are about 700 facilities. Environmental considerations As many governments increase the environmental regulations the possibility of building large infrastructure projects decreases. Take the construction of a refinery in the USA; from the mid-1990s onwards refiners spent some USD 47 billion meeting the demands of a plethora of environmental laws. According to the Energy Information Administration (EIA) there were no refineries built between 1998 and 2014 in the USA. Refinery yields and margins One of the key price relationships within the crude oil market, which measures the relative attractiveness of the refined products to crude oil, is the crack spread. This measures the difference between the income generated by the refined products and cost of the crude oil used in the refining process. This aspect of refinery profitability is considered in Section 6.4.7. If the oil market experiences a general fall in supply, those refineries that can only process lighter crudes will bid up the price of this type of oil. This may result in the price differential between light and heavy crude oils moving beyond its theoretical value3 . In a rising price environment a complex refinery that has the ability to take the heavier and more sour crude oils and refine them into higher value products will be able to generate greater margins as these types of crude will tend to trade at a higher discount to the lighter, sweeter crudes. Storage capacity and inventories When asked what key variable he looked at every day, the veteran oil trader Gary Ross declared it all boiled down to one thing. ‘What is the demand for inventory? It is in the mind of everyone who buys and sells oil . . . and that’s driven by psychology’. (Financial Times, 2019) According to the EIA, US storage capacity in 2018 was just over 710 million barrels, and given it is finite its availability will have an impact on price. Take a situation where there are concerns about the future security of crude oil supplies, encouraging participants to build their crude oil inventories. Storage should become more expensive, driving up the cost of oil for forward delivery. However, if there is nowhere to store the crude oil, producers may eventually be forced to cut production, increasing the cost of shorter-dated crude oil relative to longer-dated maturities. Another related statistic relates to the relative utilisation of the capacity, which captures the current level of inventories. A high level of storage utilisation would indicate a high level of inventories relative to demand, which may have a negative impact on price. 3

See 6.4.6 for an explanation of crude oil differentials.

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Availability of supporting resources Although much is made of the production/refining/consumption triangle, an often-overlooked feature of the supply chain is the availability and cost of such items as oil rigs, tankers, and a skilled workforce. A rise in commodity prices would increase the cost of raw materials such as steel, thus raising the cost of large projects such as oil rigs and refineries. This has a knock-on effect in that it increases the cost of producing a barrel of oil. One interesting example relating to the cost of associated services is the cost of shipping oil. In mid-2006, BP announced the shutdown of crude oil production at Prudhoe Bay in Alaska due to maintenance issues. At the time, the field was producing about 400,000 barrels of crude oil every day and was a major source of supply for refineries on the West Coast of the USA. To meet its existing commitments BP was forced to look overseas at alternative sources of supply. Estimates4 suggested that it would take 12 very large crude carriers (VLCCs) over a 60-day period to transport the deficit in production to the USA. In a market where the number of vessels capable of moving this amount of crude oil was estimated at 400 to 450, the extra demand for the freight would move charter prices significantly and have a knock-on effect on margins. Infrastructure spending In theory, a rising oil price should encourage producers to spend more money on improving the existing infrastructure and to invest in new production opportunities. However, producers have very bad memories of crude oil priced at USD 10.00/bbl. and are often reluctant to invest in times of high oil prices in case of a subsequent fall. Distribution This relates to the movement of crude oil along the supply chain. Markets such as the US are generally pipeline based, but Europe will tend to be more waterborne. So relevant issues include: ▪ ▪ ▪ ▪

The demand for and supply of tankers, Seaborne disruptions such as piracy, Port capacity and berth availability, Pipeline capacity and associated demand.

Natural Disasters In a similar vein, natural disasters that lead to shutdowns of rigs, entire fields, or refining capacity will have a substantial impact on the price of crude oil. For example, Hurricane Katrina hit the US Gulf Coast in the summer of 2005. This led to the closure of approximately 10% of the nation’s refining capacity and 90% of the US Gulf of Mexico output. Shortly afterwards, Hurricane Rita led to a temporary shutdown of 27% of refining capacity. 4

Financial Times, (15th August 2006) The dramatic knock on effect of BP’s Prudhoe shutdown

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Quality of Crude Oil The quality of oil from a particular field is not necessarily constant. Since oil extracted from different wells within a designated area may be collected into a single system, the quality of each constituent crude oil may be different.

6.6.3

Geopolitics

War, Terrorism, and Sanctions Although the motives for the major Middle East conflicts are outside the scope of this book, the impact on production and consequently price of crude has been significant. A country with substantial reserves such as Iraq will influence global production when physical capacity to produce and deliver is destroyed. Figure 6.16 shows that after the First Gulf War in 1991, Iraq production fell significantly and took many years to recover. Associated with the various conflicts have been acts of terrorism in the Middle East and East African region. One concern relating to a potential terrorist attack is Saudi Arabia where two-thirds of production is moved through two processing plants and a single terminal. The imposition of sanctions on countries such as Iran would also have price implications. Internal unrest Oil rich countries such as Venezuela and Nigeria have suffered bouts of internal unrest that have threatened to reduce crude oil production in their respective countries. 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0 19 20 17 20 15 20 13 20 11 20 09 20 07 20 05 20 03 20 01 20 99 19 97 19 95 19 93 19 91 19 89 19 87 19 85 19 83 19 81 19 79 19 77 19 75 19 73 19 71 19 69 19 67 19 65 19

Iran

Iraq

FIGURE 6.16 Iran and Iraq production 1965–2019. Thousand barrels daily. Source: BP Statistical Review of World Energy 2020. BP PLC.

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Political tensions and the security of supply Reference is often made to the ‘fear factor’ within commodity markets and usually in relation to concerns over the security of supply. There are ongoing concerns relating to the nuclear capability of Iran. As China continues to industrialise, it has shown that it is prepared to secure supplies from countries with which the USA has refused to deal (e.g. Iran, Sudan, Angola). This has led some commentators to speculate on future tensions between the superpowers as they both wrestle for control of strategic oil supplies. It is sometimes assumed that the suppliers of crude oil exert more influence over the price than the buyers. However, this is not always the case, and it is valid to consider the notion of ‘security of demand’. That is, oil-producing companies must be certain that they will be able to find a buyer for their output. This means that while buyers are looking for diversification of supply, producers are looking for certainty of demand. Resource Nationalism In some oil countries the substantial price rises of the early twentieth century led to an increase in nationalism as newly elected governments threatened to nationalise oil production in their respective countries (e.g. Bolivia, Ecuador, Venezuela). Russia has also reasserted control over some aspects of energy production as prices have risen. However, resource nationalism may manifest itself in less obvious forms as for example, at the time when concerns were being raised about nationalisation in South America, the UK increased taxes on revenues earned by oil companies operating in the North Sea. Access to new reserves National (i.e. government owned) oil companies own a significant portion (about 75%) of the world’s oil. These entities may choose to allow international oil companies access to the oil where they themselves do not possess a certain technical capability. This has made it difficult for private oil companies to replenish their reserves and has driven them into new areas of research (e.g. gas-to-liquids technology) or risky areas of exploration (e.g. Canadian oil sands or 10,000-foot-deep waters off Mexico). Organisation for Petroleum Exporting Countries (OPEC) According to the organisation’s website their mission statement is: ‘ . . . to coordinate and unify the petroleum policies of Member Countries and ensure the stabilisation of oil prices in order to secure an efficient, economic and regular supply of petroleum to consumers, a steady income to producers and a fair return on capital to those investing in the petroleum industry’. The current list of the 14 OPEC members: ▪ ▪ ▪ ▪

Algeria Angola Congo Ecuador

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▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪

Equatorial Guinea Gabon Islamic Republic of Iran Iraq Kuwait Libya Nigeria Saudi Arabia United Arab Emirates Venezuela

OPEC meets twice a year and the main technique used to achieve their objectives is to target output quotas for each of the member countries. Although the countries collectively do not produce the entire global output of oil (they are believed to control about 37%5 ), their output is significant, and the market closely monitors their activities. Based on the different price factors presented in this section, it would be perhaps unrealistic to say that OPEC controls the price of oil, but its prominence in terms of overall production cannot be ignored. The relative power that they can exert would be greater if the market was relatively short of oil, but with the advent of new sources such as shale, this influence is arguably lower. This has given rise to the idea of the ‘OPEC Call’ – if non-OPEC members require additional supply, then it could in theory be met from OPEC production.

6.6.4

Analysing the forward curve

So far, the analysis has concentrated on generic price factors without necessarily considering their term structure. Davis argues that the term structure of oil can be broken into two segments: 0–18 months and beyond 18 months. He argues that the 0–18-month segment is closely linked to the physical market and reacts mostly to issues such as demand and supply, the level of inventories, availability of storage, and security of supply. Beyond those maturities, market activities focus more on financial rather than physical concerns; this may include expectations over interest rates and inflation. It is also where market participants are likely to express their views on proposed capital expenditure and anticipated infrastructure projects. He also notes that the term structure is more volatile than financial markets, may display seasonality, and that crude oil prices tend to display mean reversion over the longer term.

6.7 6.7.1

THE PRICE OF CRUDE OIL Defining price

The price of crude oil is expressed in US dollars per barrel, sometimes shortened to USD/bbl. The origin of the abbreviation ‘bbl.’ is unclear with two competing explanations. One story argues it derived from the practice of storing crude oil in blue coloured 5

BP Annual Statistical Review of Energy 2020

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barrels, whereas some argue that the abbreviation arose from the fact that beer barrels were originally used for storage. A barrel will hold 42 US gallons or 159 litres.

6.7.2

The evolution of crude oil prices

High crude oil prices are often seen as a modern-day problem. However, if one adjusts for the effect of inflation a very different picture emerges. Figure 6.17 indicates that when adjusted for inflation there are two significant price peaks. The first was in 1864 (an early ‘boom and bust’ period in the oil industry) when the price exceeded USD 100.00/bbl. and in 1980 when the price nearly touched USD 110.00 (the first global oil crisis). One of the interesting questions about high oil prices is whether they will trigger a global recession. If the price rise has been caused by a restriction in the supply of crude oil, there may be a tendency for inflation to rise and output to fall. But if there has been an increase in demand brought about by a significant increase in productivity growth in oil importing countries, or increased spending in the oil exporting countries then a high oil price could be consistent with greater economic expansion.

6.7.3

Delivered price

What will be delivered and the nature of the price to be paid must be specified on the contract, which typically will include the following: ▪ Price (usually expressed in USD/bbl.). ▪ Whether the contract is to be priced off an index or a‘marker’ crude. ▪ Any differential that should be applied to the price. 140 120 100 80 60 40 20 0 16 20 1 1 20 6 0 20 1 0 20 96 19 1 9 19 6 8 19 81 19 6 7 19 71 19 6 6 19 61 19 6 5 19 51 19 6 4 19 41 19 6 3 19 1 3 19 26 19 1 2 19 6 1 19 1 1 19 6 0 19 01 19 6 9 18 1 9 18 86 18 1 8 18 76 18 1 7 18 6 6 18 1 6 18

$ money of the day

$2019

FIGURE 6.17 Price of crude 1861–2017; USD/bbl. Expressed as inflation adjusted (USD 2019) or in the money of the day. Source: BP Statistical Review of World Energy 2020

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▪ ▪ ▪ ▪

Quality (e.g. sulfur content). When it will be delivered. Where it will be delivered. Whether the price is CIF or FOB.

The price of crude oil is usually expressed in one of two ways: Free on Board (FOB) or Cost, Insurance, and Freight (CIF). An FOB price is the most common pricing method as it represents the price of the commodity at the point of loading and therefore allows comparisons to be made between different crude oil prices around the world. However, a purchaser of crude is going to be more interested in the CIF price as it gives an indication of the total cost. Typically, the cost of delivering crude oil to a purchaser will include: ▪ The quoted FOB price. ▪ Shipping costs. ▪ Any associated secondary transportation expenses such as pipeline costs (if the refinery is not based on the coast). ▪ Losses due to factors such as evaporation. ▪ Insurance costs. ▪ Cost of financing oil purchased while in transit and prior to product production (there will be a gap between when oil is paid for and when the refined products are sold to generate income).

6.7.4

Marker crudes

In Section 6.2 it was noted that the price reporting agencies often quote prices for over 100 different types of crude oil. Section 6.4 noted that many crude oils were quoted as a differential to a so-called ‘marker’ crude. In theory this differential is a reflection of the discount (or premium) that should be applied to a particular grade of crude oil relative to another crude such that a refiner would be indifferent in using either to produce a given product slate. The key global marker crudes that are used as pricing benchmarks are: ▪ West Texas Intermediate (USA origin; global benchmark) ▪ Light, sweet crude oil with an API of 39.6 and a sulfur content of 0.24% ▪ Brent (North West Europe origin; global benchmark) ▪ Light, sweet crude with an API of 38.8 and a sulfur content of 0.37% ▪ Tapis/Oman (Malaysian/Middle East origin; Asia Pacific benchmark) ▪ API of 46 and a sulfur content of 0.03% ▪ Urals (Eastern Europe origin; Mediterranean benchmark). ▪ API of 31.7 and a sulfur content of 1.35% The selection of a crude oil as a benchmark does not follow any predetermined formula. For example, Brent is a key global benchmark, even though it now only constitutes about 0.3% of total global output. However, an advantage is that it originates from a politically stable region and is supported by an actively traded derivatives market, like

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West Texas Intermediate (WTI) in the USA. Even within a single type of crude oil there may be different benchmarks. For example, the price for physical Brent crude (‘Dated Brent’) may be used to price certain commercial contracts whereas other participants may prefer Brent futures. Other benchmarks may appear for different reasons. The use of Light Louisiana Sweet has become a useful domestic US benchmark for Gulf Coast refiners, with Mars being a popular domestic sour crude benchmark. However, even the global markers such as WTI may be subject to unpredictable behaviour. The CME crude oil future is a physically settled crude oil with the delivery point in Cushing, Oklahoma. The supply and demand for crude in this area can have an impact on its price. So, if there were, say, an unplanned outage in a local refinery there would be knock-on effect that would increase the level of inventories and put downward pressure on price. As a result, some consider WTI to be more of a ‘land locked’ crude oil not representative of global conditions but perhaps more relevant to US mid-continent producers and refiners. The price of crude oil referred to by OPEC is based on a basket of oils (ORB – OPEC Reference Basket) produced by the member countries. The ORB is made up of the following crudes: ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪

Saharan Blend (Algeria) Girassol (Angola) Djeno (Congo) Oriente (Ecuador) Zafiro (Equatorial Guinea) Rabi Light (Gabon) Iran Heavy (Islamic Republic of Iran) Basra Light (Iraq) Kuwait Export (Kuwait) Es Sider (Libya) Bonny Light (Nigeria) Arab Light (Saudi Arabia) Murban (UAE) Merey (Venezuela)

However, OPEC countries are free to use different approaches to price their own physical contracts. For example, Saudi Arabia will price its oil depending on its destination. So, if the crude is going to the USA, it is priced as a differential to WTI or to the American Sour Crude Index; crude going to Europe is priced as a differential to Brent. It may seem surprising that given Saudi Arabia holds a significant proportion of the proven reserves of crude oil, as well as being a key supplier, that its crude oils are not considered as global markers. The reason for this dates to the 1980s when the crude oil producers introduced ‘net back pricing’. Producing nations rationalised that the value of crude oil lay in the different products that could be produced from the refining process. At the time, the refined products were trading at relatively high prices and so the producers set the price of crude based on these higher values, less a margin for refining and transportation. Under this system, the refiners would earn a fixed margin irrespective

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of how much they produced and so were incentivised to run at high capacity. This led to an oversupply of products, whose prices fell significantly as well as those for crude oil. As a result it is more conventional for Saudi crude oil to be priced according to the terminal location or according to the date of final delivery (e.g. 40 days after loading – the time taken to transport the crude oil). One of the consequences of this was that Saudi Arabia introduced a clause into their sales contracts that would only allow for the crude oil to be refined by the original purchaser. Transfer of ownership is prohibited (without the express permission of the original seller) and as a result there is no actively traded market for Saudi crude oil. Contracts for the supply of Saudi crude oil tend to be ongoing (‘evergreen’) and buyers will nominate to receive an amount. The Saudis will then decide on how much to deliver.

6.7.5

Pricing sources

When pricing crude oil contracts, participants need to be aware of the current prices. There are several price reporting agencies that specialise in compiling and publishing reference prices based mainly on physical market activity, with S&P Platts and Argus Media being the mostly widely referenced. Depending on the chosen benchmark, prices may be taken from exchange traded futures such as those published on the CME Group (WTI) or the ICE (Brent).

6.7.6

Pricing methods

There are several different approaches to establishing the price of a crude contract as follows: Official selling prices – this was a traditional method of pricing oil where governments would announce the price for the sale of crude for a fixed period such as one year, typically to long-term customers. Fixed price – here the price to be applied has been bilaterally negotiated at a given level. Anecdotally, it is believed that about 90–95% of crude oil sold is on a long-term fixed price basis and so therefore the spot market makes up no more than 5–10% of the market. Floating price – this uses a price quoted by companies such as S&P Platts or Petroleum Argus, which is not fixed in advance. The process to determine the actual price is specified in the contract and may be the average of prices covering a short period around the delivery date. Sometimes referred as a ‘floating forward’ – a forward contract whose price at the settlement date will be determined based on a series of previous traded prices (e.g. the average of daily prices over the previous month). Differential to a marker crude – this is where a particular crude oil is quoted as a differential to one of the marker crudes noted earlier. The differential could move according to a variety of market factors and could either be positive or negative. For example, a crude oil that produces a higher yield of gasoline would be in greater demand during the summer months and so the differential may increase. Equally

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a crude oil that yields a higher proportion of heating oil may be in greater demand in the winter months, again affecting the size of the differential. Futures price – this might be relative to a futures price on a particular date or an average of prices over a previously agreed period. It should, however, be noted that a futures market does not exist for every type of crude. Exchange for physicals – this pricing method allows two counterparties to a physical trade to fix a price using the futures market. A simple numerical example of this approach is outlined in Section 6.9.

6.7.7

Pricing a cargo of crude oil

When pricing a cargo of crude oil, the contract between buyer and seller will need to specify certain items: ▪ ▪ ▪ ▪

The underlying benchmark price and its source. Any agreed differential to the benchmark price. The pricing period. Whether the price is FOB or CIF (or another incoterm). To illustrate the concept, consider the following stylised example: ‘S&P Platts Dated Brent + USD 1.00/bbl., FOB, pricing 2-1-2’

The benchmark is the price for Dated Brent (see Section 6.8) as published by the price reporting agency S&P Platts plus a differential of USD 1.00/bbl. The oil will be delivered on a Free on Board (FOB) basis. The last part of the pricing clause requires a little more explanation. This example illustrates a floating price example, where the price to be applied to the cargo will be the unweighted average of the published Dated Brent price around a five-day period (2-1-2). A key part of this formula revolves around the Bill of Lading date. A Bill of Lading is part of the shipping documentation, which fulfills three main roles: ▪ It acts as a receipt for the cargo being carried by a vessel. ▪ It is a contract for the carriage of goods. ▪ It is a document of title to the goods being carried. So, in our example, the pricing period covers the two days prior to, the date of and the two days following the signing of the Bill of Lading. This may not coincide exactly with the dates that the crude oil is loaded. One way to think about such a pricing period is that from the buyer’s point of view their exposure to the price of crude oil is increasing every day. So, if they agreed to a cargo of 600,000 barrels and a five-day pricing period then every day their exposure to the crude oil price increases by 120,000 barrels. The pricing process in this example is merely illustrative and may vary; participants may agree, say, the five days after loading or some form of ‘average of month price’.

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6.8

TRADING CRUDE OIL AND REFINED PRODUCTS

6.8.1

Overview

There are many crude oil markets, and each has its own quoting conventions, contract types, and liquidity issues. There are however, arguably, two key global physical markets, namely those for North Sea Oil and West Texas Intermediate. The details of these markets are considered in Section 6.8 while this section considers some generic trading principles. Why are crude oil and the refined products traded? At a very simple level, trading opportunities can arise for a variety of reasons: ▪ A producer has crude oil available to sell on the open market. ▪ Demand exists within the supply chain (e.g. at the refinery level) for a particular crude oil. ▪ A crude oil with a particular quality is in demand. ▪ A trader has identified the possibility of making money. According to their 2017 annual report, on average BP ▪ Produced 1.2 m barrels of crude oil. ▪ Refined 1.7 m barrels of crude oil. ▪ Sold 2.7 m barrels of refined products to retail or commercial customers. To balance this demand and supply, BP will buy and sell both crude oil and the refined products from other wholesale sources on an ongoing basis. The annual report notes that during the period the company traded 2.6 m barrels of crude oil and 3.1 m barrels of refined products. This would suggest that what they produced was not necessarily refined, but may have been sold to other companies. The annual report also points out that the company would buy crude oil from other suppliers to optimise their refinery output. This provides the first definition of trading: buying and selling to balance supply and demand. Who participates in trading? Typical market participants include: ▪ ▪ ▪ ▪ ▪ ▪

National oil companies. Producers. Refiners. Integrated oil companies. Financial institutions with the capacity to trade the physical products. Trading houses – for example, in 2017 Vitol traded or shipped around 3.6 million barrels of oil.

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What risks arise from buying and selling in the physical markets? Over time a crude oil trader will end up with a portfolio of crude oils. The portfolio will be comprised of a variety of different exposures: ▪ Crudes priced on different bases (e.g. fixed; floating; futures prices). ▪ Different grades of crude that may be priced off a differential to a certain market crude. ▪ Crudes that will be bought/delivered on different dates. ▪ Crudes that need to be bought/delivered in different locations. This gives a second perspective on trading: the mitigation or transformation of the market risks that arise in the process of buying and selling crude oil. These risks can be managed by using derivatives. View driven trading activities The third and final trading perspective relates to market participants that may wish to express a view on price movements without necessarily having an underlying economic exposure to manage. Here the motive is to make money from an anticipated move in some market variable. These strategies could be implemented using exchange traded futures or options. Possible strategies include taking views as follows: ▪ Direction of the price – where the trader buys the commodity if the price is expected to rise and sells it when the price is expected to fall. ▪ Grade differentials – here the expectation is that the differential to a marker crude will change. ▪ Shape of the forward curve – when the trader expects a change in the demand and supply fundamentals at different maturities. These are sometimes referred to as time spreads. Examples might include: ▪ Trading one quarter or season against another (e.g. Q1 vs. Q; winter vs. summer) to capture some form of seasonality. Some futures contracts will allow the trader to bundle together individual contracts to form a single longer period or the trader may have to do this manually by buying or selling a ‘strip’ (e.g. a series of consecutive contracts). ▪ Trading one calendar year against another. ▪ Freight rates – when rates change due to a sudden change in demand at a certain geographical location. ▪ Relationships between different crude oil markets – where the trader takes a view on a particular price relationship that might exist between two markets (regional spreads). One example of this is the price of Brent crude compared with the price of WTI. Theoretically, WTI should trade at a premium to Brent but this relationship can change for several reasons such as: ▪ Declining North Sea output in a period of growing demand. ▪ Maintenance of oil rigs in the North Sea that might lead to a temporary reduction in output.

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▪ ▪

▪

▪

▪

197

▪ High levels of US stocks exerting downward pressure on WTI prices. ▪ Disruption to the supply of other crudes that are considered substitutes for Brent (e.g. Bonny Light in Nigeria). The relationship between crude oil differentials, e.g. WTI vs. WT Sour or Bonny Light vs. Brent. The crack spread relationship – this is the difference between the price of a finished product such as gasoline or heating oil and the price of crude oil. There are several variations of this trade and one example is the gas oil ‘crack’. The price of gas oil can be broken down into a Brent component and a gas oil crack: Gas oil price = Brent price + gas oil crack If gas oil is trading at USD 72.00/bbl. and Brent is trading at USD 60.00, the gas oil crack would be USD 12.00/bbl. In very simple terms, the gas oil crack spread presented here could be interpreted as the refiner’s profitability from taking a barrel of crude and converting it into a higher-value refined product. This gas oil crack is not a fixed number and will change depending on the relative demand and supply of the two constituents. Relationships between the same product traded in different areas – e.g. gasoline traded in different areas within the same country (Gulf Coast vs. NY Harbor) or perhaps fuel oil in different continents (e.g. Europe vs. USA). Product spreads – typical price spreads that might be traded include gasoline and heating oil or perhaps interfuel spreads such as natural gas against Ultra Low Sulfur Diesel (ULSD). Price volatility – option traders will execute option strategies to exploit the perceived riskiness (i.e. the implied volatility) of the crude oil market. In a similar vein, certain option strategies are designed to profit from current volatility of the market, such as gamma trades.

How are oil products traded? Trading of crude oil and the refined products can be undertaken by a variety of mechanisms. There may be a physical trade, an over-the-counter trade forward or an exchange traded future. The forwards and futures trades will require physical settlement unless they have been set up to be cash-settled or closed out prior to expiry. It is possible to buy options for physical delivery and swaps are also used extensively in the market, but these will always be cash settled. Option trades may be used as a mechanism to obtain or dispose of supplies but also as a mechanism to exploit the magnitude of price movements. Arbitrage: a question of definition? ‘Arbitrage’ is a word that is often misused in many markets, although in the end its interpretation is just a question of definition. True arbitrage is the opportunity to buy a commodity at a certain price and sell it in the same or another market at a higher price to make a risk-free profit. It is sometimes confused with a spread trade, where the motive is to exploit an expected change in the relationship between two related, but ultimately different, commodities.

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A possible true arbitrage for crude oil was illustrated in Chapter 2 and would involve: ▪ Buying a particular oil in one geographical market. ▪ Knowing what crude products the grade could produce and the total associated revenues. This would establish the value of the crude to a buyer in the delivery location. ▪ Adding the cost of freight to the destination. ▪ Adding any associated costs (e.g. insurance costs, costs of financing cargo while in transit). ▪ Ensuring the income from the final sale at the location of delivery is greater than all the associated purchase costs.

6.8.2

The Brent complex

At first glance it would appear the phrase ‘Brent Crude Oil’ is referencing a single crude oil produced in the North Sea. However, nothing could be further from the truth. This is because the market for Brent (sometimes referred to as the ‘Brent complex’) comprises of many different components with varying degrees of complexity. It is not helped by the fact that much of the terminology associated with the market can be confusing. North Sea crude oil is made up of a variety of different grades, which include: ▪ ▪ ▪ ▪ ▪ ▪ ▪

Brent Blend Forties Oseberg Ekofisk Troll Statfjord Flotta

For many years, the representative price of North Sea Oil was Brent Blend, which itself is a mixture of crude oils from two different systems (Brent and Ninian) and several different fields therein. As a result of a decline in North Sea production, the definition of the Brent crude oil price has widened to include activity in a total of five crudes that are, broadly speaking, chemically similar: Brent Blend, Forties, Oseberg, and Ekofist and Troll. These crudes are collectively referred to by the acronym BFOET. There are a variety of contracts available to trade North Sea oil and they include: ▪ ▪ ▪ ▪ ▪

Dated Brent Brent Forwards Contracts for Difference Brent Futures Exchange for Physicals

6.8.2.1

Dated Brent

The first component of the North Sea market is Dated Brent, which is also sometimes referred to as ‘North Sea Dated’. As was pointed in the previous section, this is not the price of a grade of crude oil but a benchmark value that is determined through a

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published methodology. As such, it does not have an API density or sulfur specification. Reference to either of these values is usually referencing one of the constituents, typically Brent Blend. The methodology used by the price reporting agencies (PRAs) means that the price assessment is based on the lowest price of the five constituent crudes. However, one of the problems witnessed by the market is that the widening of the basket has resulted in a significant variation in the quality of crudes, which meant that to fulfill a commercial contract, producers would often deliver the cheapest of the five crudes. This oil was termed the ‘cheapest to deliver’. The PRAs have therefore introduced a process that attempts to adjust for these quality differentials to make a participant indifferent as to which oil is delivered. One of the reasons for the continued popularity of Brent as market crude is the fact that is sometimes considered a spot contract and allows for the pricing of short-dated crude oil cargoes. However, the term ‘spot’ in relation to the crude oil market warrants further description, as the term would normally be associated with immediate delivery. For Brent, normal market practice rarely sees cargoes bought or sold for delivery in less than 10 days. Dated Brent is a price, which is published daily, and the definition used by S&P Platts gives an insight into how this part of the market trades. Their price assessment ‘reflects the value of physical crude oil loading 10 days forward from the date of publication to one full month ahead. The assessed date range will typically stretch to the equivalent dates of the following month’. So, a price assessment made on 2 January would cover transactions from 12 January–2 February; an assessment made on 15 January would cover transactions from 25 January–15 February. The Dated Brent price for any single day is therefore based on volume-weighted prices for transactions encompassing an approximate6 21-day period starting in 10 days’ time. The price quoted for Dated Brent is a rolling price assessment so that on each day the activity period will move forward by one day. It should be noted, however, that the above example describes how a price for Dated Brent would be assessed for publication by a PRA such as S&P Global Platts. The pricing of a physical cargo that references Dated Brent as the benchmark would be based on an average of pre-specified published Dated Brent prices around the time of loading. So if the agreed loading period were a three-day window, then the cargo would take its value from an average of the three Dated Brent prices quoted by the designated PRA during this time. The respective delivery points for the five crudes in the BFOET basket is shown in Figure 6.18. The terminal operators will notify producers in advance as to when they will be able to take possession of their crude oil by means of a tanker over a specified three-day window. Once a specific three-day loading window has been agreed to then this cargo will be classified as Dated Brent or a ‘wet’ cargo. In February 2021, S&P Global Platts announced it would include US WTI Midland crude in its Dated Brent benchmark, with the change becoming effective in July 2022. This was designed to reflect the decline in output from North Sea crude oils as well as an increase in imports of US crude oil. At the same time, the price assessment process would change to a Cost, Insurance and Freight (CIF) Rotterdam basis, meaning crudes will be assessed on the basis of deliveries into Europe’s largest trading hub, rather than including loadings at terminals around the region. 6

The exact number of days will depend on weekends and public holidays.

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FIGURE 6.18 Delivery locations for BFOET crude oils. 6.8.2.2

Brent forwards

In the Dated Brent scenario, if a producer is integrated along the supply chain, they may wish to pick up their crude oil and transport it directly to a particular refinery. However, a producer knows that since they will be able to load crude oil from the terminal during any future month, it is possible for them to forward sell a cargo to a buyer who may be looking to secure their supply. In this situation, it is not possible initially to agree to a specific loading date with the counterparty and so only the month of delivery is agreed. The two parties will subsequently agree to the loading dates once the terminal operator has announced them. This type of forward transaction is often referred to as a ‘paper’ transaction given the lack of a specific loading date. So, Brent forward contracts lock in the price at the time of contracting of a commodity for delivery in a specific future month beyond the Dated Brent assessment period. Somewhat confusingly, forward contracts in Brent may be referred to in several different ways as: ▪ ▪ ▪ ▪ ▪

Brent forwards Paper Brent Cash BFOET Paper BFOET Cash forwards

For simplicity, these types of contracts will be referred to in the text as forwards. The price quotation for this type of forward represents the value of a cargo for physical delivery within the month specified by the contract. At the time of writing, for a given day, S&P Global Platts will quote a value for Dated Brent as well as three Brent forwards. If it is early March, they will quote forward price

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for May, June, and July. These three months will be quoted for the remainder of March when the contract months will ‘roll’. So, from April, the forwards quoted would be June, July, and August. The way in which this paper forward turns into a wet Dated Brent contract is outlined in standard market documentation referred to as ‘SUKO 90 terms’ (Shell UK Oil Company). The terms state: ‘Seller shall declare to the buyer the grade deliverable, the laydays and the cargo reference number in respect of the cargo between 0900 and 1600 hours (London time) . . . not later than on the last day of nomination . . . The last day of nomination shall be one full month prior to the first day of the laydays . . . ’ Assume that on 7 March of a given year, a Brent forward is executed for delivery in May. In the month prior to delivery (April in this case) the managers of the loading installation will list the dates in May when the contract seller can load oil. This set of dates is referred to as the ‘laycan’, which is the three-day window where the buyer can arrange for a vessel to arrive for loading. For example, the assigned loading dates may be 1–3, 10–12, 20–22 and 26–28. In the Brent Forward market, the contract seller has the right to nominate any of the loading dates to another buyer so long as they give the requisite one-month notice. If on 17 April the seller wished to nominate a particular set of delivery dates to physically settle the forward, they would no longer be able to use the first two sets (1–3 May and 10–12 May) due to the requirement to give one month notice. Cargos for delivery on those earlier dates would be classified and traded as Dated Brent. If the parties to an agreed trade do not wish the deal to go to physical delivery, it will have to be cash settled or ‘booked out’ to use the industry jargon. Table 6.7 illustrates the main characteristics of the Brent forward contract, which although OTC in nature, does have an element of standardisation within the market. Reference may sometimes be made to partial contracts, which describe a forward contract with‘standard’ terms apart from the fact that the trade size will be less than the 600,000 barrels. 6.8.2.3

Contracts for Difference

Brent Contracts for Difference (CFD) are one period swaps that give a user exposure to the differential in price between Dated Brent and a Brent Forward Contract. However, this differential is not the difference between the current Dated Brent value and the first available Forward Brent Contract. This type of transaction within exchange traded futures markets would be referred to as the ‘dated to frontline’ contract. CFD quotes represent the difference (either positive or negative) between the current third month7 Brent forward quote and Dated Brent for a stated future period, in USD/bbl. Therefore, the CFD quote represents the value of time between the maturities of the two contracts. The quote for a given period will change as the relative demand and supply for the two constituent components evolves. 7

Confusingly, S&P Global Platts describe this as the ‘M2’ contract.

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The relationship could therefore be expressed as follows: CFD quote = Forward Dated Brent minus Third Month Brent Forward However, since both the CFD and the Brent Forward are observable it is perhaps more useful to rearrange the formula to derive an implied Dated Brent value for a forward period. Rearranging the formula gives: Forward Dated Brent = CFD plus Third Month Brent Forward Another interpretation of the equation is that buying a CFD and taking a long position in the third forward month will lock in the purchase price for Dated Brent at a certain time in the future. Say it is early March and the following bid and offer prices are being quoted in the Brent market: Dated Brent Brent forwards May Brent June Brent July Brent Contracts for difference CFD 1-week 06–10 March CFD 2-week 13–17 March CFD 3-week 20–24 March

USD 65.00–65.02 USD 67.90–67.92 USD 68.70–68.72 USD 69.49–69.51 −2.01/−1.99 −1.60/−1.58 −1.41/−1.39

CFD 8 − week 24 − 28 April − 0.35∕ − 0.33 Diagrammatically, this is shown in Figure 6.19. For brevity purposes only the offer prices are shown. The normal market size for Brent CFDs is between 50,000 to 100,000 bbl. and they are traded with weekly maturities out to eight weeks. They can also trade for bi-monthly and monthly periods. Like any contract for difference, the counterparties agree to a fixed differential at the point of the trade and then subsequently settle on the actual differential (sometimes referred to as the ‘floating’ rate) at the contract maturity. Settlement at Dated Brent

Contracts for difference (CFDs)

Brent forwards

Mar 3

Mar 06–10

Mar 13–17

Mar 20–24

Mar 27–31

Apr 03–07

Apr 10–14

Apr 17–21

Apr 24–28

May forward

June forward

July forward

65.02

-1.99

-1.58

-1.39

-1.17

-0.97

-0.68

-0.51

-0.33

67.92

68.72

69.51

FIGURE 6.19 The relationship between, Dated Brent, Contracts for Difference and Brent forwards.

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TABLE 6.5 Interpreting a CFD quote.

Market maker

Market user

Bid

Offer

Buy Pay quoted differential (fixed) Receive actual differential (floating) Profits if actual differential is more positive/less negative than quoted differential Sell Receive quoted differential (fixed) Pay quoted differential (floating) Profits if actual differential is less positive/more negative than quoted differential

Sell Receive quoted differential (fixed) Pay quoted differential (floating) Profits if actual differential is less positive/more negative than quoted differential Buy Pay quoted differential (fixed) Receive actual differential (floating) Profits if actual differential is more positive/less negative than quoted differential

maturity is based on the average of the daily differential between Dated Brent and the original Brent Forward contract. CFD are quoted on a bid/offer basis (see Table 6.5) so when the market is in contango, the quote is negative and the CFD bid price is greater than the offer. This ensures that when the implied forward price for dated Brent is derived it will follow the normal convention of low bid, high offer. A market in backwardation will result in a positive CFD quote with the bid price lower than the offer. The fact that the CFD quote may be negative combined with the use of ambiguous phrases such as ‘spread widening’ and ‘narrowing’ can make the interpretation of CFD quotes confusing. To illustrate the principles, consider an example of a CFD quote of +USD 1.50/+ USD 1.55. If a trader believed that the differential would increase (i.e. become more positive), then they would buy the CFD at the offer side of the market as a market user. If at settlement the actual differential had increased to USD 1.75, a payment of USD 1.55 would be made and a payment of USD 1.75 received, representing a USD 0.20 net receipt per barrel. If it were assumed that the deal was executed on a notional basis of 50,000 barrels, this would equate to a cash settlement of USD 10, 000 (50,000 barrels x USD 0.20) Now consider that the quote is −USD 2.10/−USD 2.05. Once again it will be assumed that the trader believes that differential will increase (i.e. become less negative) and so decides to buy the CFD at the offer side of the market. If at settlement the actual differential had increased to −USD 1.85 the terms of the contract necessitate making a payment of −USD 2.05 and receiving a payment of −USD 1.85. But a payment of a negative sum is a receipt as two negatives make a positive! A receipt of a negative sum would therefore represent a payment and the trader would be a receiver of USD 0.20 a barrel, which makes the two examples consistent. The previous CFD example focused on the use of the instrument to exploit how the relative prices of Dated Brent and Brent Forward were expected to evolve. CFD can also be used as a mechanism to hedge a position in Dated Brent. Let us assume that it

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TABLE 6.6 Prices used to settle a Contract for Difference.

Date Monday, 20 March Tuesday, 21 March Wednesday, 22 March Thursday, 23 March Friday, 24 March

Dated Brent (USD)

June forward (USD)

Differential of Dated Brent minus June forward (USD)

69.48 69.49 69.50 69.51 69.52

70.79 70.78 70.80 70.82 70.81

−1.31 −1.29 −1.30 −1.31 −1.29

is early March and a trader has agreed to buy a cargo of crude that will be priced on a floating basis using Dated Brent. Since he has not yet taken delivery of the crude, in market jargon he is said to ‘short crude for forward delivery’. The cargo will be loaded on 21–23 March and the invoice price will be based on an average of Dated Brent prices centered on the loading date. The trader looks at the price screen and notes that the current value for Dated Brent is USD 65.02. He is concerned that the price of Dated Brent will rise and so decides to hedge his exposure. He could use the May forward to hedge the risk but runs a risk that the price of the forward may not track the movements in Dated Brent used to price his physical contract (‘basis risk’). To hedge this exposure the trader will have to do the following: ▪ Buy a CFD that covers the week in which the physical cargo will be priced and, ▪ Take out a long position in the third month Brent Forward contract from which the CFD is priced. Using the figures quoted earlier the trader’s position using market user rates would be: ▪ Long one cargo of BFOET loading 21–23 March; priced at an average of Dated Brent around the time of loading. ▪ Buy a CFD for the week 20–24 March; priced at −USD 1.39. Since the price is a negative, they will receive this value and pay the realised differential at settlement. ▪ Long one Brent Forward for June delivery at USD 68.72. Using the relationships established earlier it is possible to back out an implied forward value for Dated Brent for the delivery week of 20–24 March. Since mathematically the CFD quote is the Forward Dated Brent value minus the second month Brent Forward, we can back out the Forward Dated Brent price. −USD 1.39 = Implied Forward Dated Brent − USD 68.72 Implied Forward Dated Brent = 68.72 − 1.39 = 67.33 Buying the CFD and going long the third month forward is now economically equivalent to buying Dated Brent on a forward basis at a price of USD 67.33. Assume that over the course of the loading week (i.e. the week ending 24 March), the prices in Table 6.6 are observed.

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The result of the hedge will be: ▪ The physical cargo will price as the average of the Dated Brent contracts that were observed on 21–23 March. This returns a value of USD 69.50. ▪ The average of the Dated Brent to June forward differentials observed over the week is used to settle the CFD week. The average is calculated as −USD 1.30. The trader receives USD 0.09/bbl. ▪ The trader closes out their June forward position. If this is assumed to be done at the Friday, 24 March price shown above, then they will show a profit of USD 2.09 ▪ The total cost per barrel is therefore USD 69.50 − USD 0.09 − USD 2.09 = USD 67.32. This price is within USD 0.01 of the implied Forward Dated Brent value calculated earlier. The difference is attributable to the fact that the CFD is calculated as the average of five values, but the June forward is closed out using a single value. This may seem somewhat complex and so in order to make the hedging of the physical exposure easier, the purchaser may opt to go for a futures based pricing agreement, which could then be hedged by purchasing the same futures contract. 6.8.2.4

Brent futures

There is also an active exchange traded futures market that allows for crude oil to be traded for delivery in a specified future month. As with any futures contract, it will have standardised terms and conditions. The main Brent contract is traded on the Intercontinental Exchange (ICE). According to the ICE, ‘The ICE Brent Crude futures contract is a deliverable contract based on EFP delivery with an option to cash settle against the ICE Brent Index price for the last trading day of the futures contract’. Trading in the Brent futures contracts ceases at the close of business on the last business day of the second month preceding the relevant contract month. So, the March contract will expire on the last business day of January. Contracts are available for maturities out to 96 months but the longer-dated contracts may offer different degrees of liquidity. One of the characteristics of every futures contract is that the price of the future should eventually converge to that of the underlying. So, upon the expiry of the futures contract, its value should be the same as the asset to which it is referenced. If this were not the case, then in theory it should be possible to buy and sell the physical and the future and make a risk-free profit. The futures contract settles against the ICE Futures Brent Index: ‘The cash settlement price for the ICE Brent Future is based on the ICE Brent Index (‘The Index’) on expiry day for the relevant ICE Brent Futures contract month. The Index represents the average price of trading in the BFOET (Brent-Forties-Oseberg-Ekofisk-Troll) cash or forward (‘BFOET Cash’) market in the relevant delivery month as reported and confirmed by the industry media. Only published cargo size (600,000 barrels) trades and assessments are taken into consideration in the calculation”.

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Exchange for Physicals

The specification of a crude oil futures contract can vary between exchanges. Some of the contracts will involve physical delivery while others may cash settle; some contracts may offer an element of both. Additionally, only a small proportion of all futures contracts will go to final delivery for a variety of reasons: ▪ The contract maturity may not match the timings of the underlying exposure. ▪ The type of crude oil referenced by the future may differ from the underlying exposure. ▪ The location of any physical delivery may differ from the underlying exposure. ▪ If the contract is physically delivered, the exchange’s settlement algorithm may select an unfamiliar entity or indeed multiple entities with which they must deal. Exchange for Physicals (EFP) is an instrument that helps manage these types of issues. As the name suggests there is an exchange of a physical holding of crude oil against an equivalent futures position. EFPs are quoted as a differential, which attempts to capture three main elements: ▪ Time – since the two holdings have different times to delivery (immediate against some future date), then it is unlikely that they will have the same value. For example, the shape of the forward curve is likely to have some impact with the parties wishing to consider whether the market is in backwardation or contango. ▪ Quality – participants can also agree to a transaction where the physical crude oil differs from that referenced by the future so a quality differential will need to be agreed. ▪ Location – they can also negotiate the actual location where the physical crude oil will be delivered, which again could differ from that outlined in the future. EFPs are quoted as a differential to a particular futures maturity, which can be agreed between the two participants. The EFP does not necessarily need to reference the futures contract with the earliest maturity. So, if the agreed future were trading at USD 62.00/bbl. and the EFP was quoted at +USD 0.10 then the price of the physical to reflect time, quality, and location would suggest a value of USD 62.10. The following example illustrates the principles. It is early February, and a producer has one million unsold barrels of crude oil. An oil refiner is long 1,000 futures (where each future references 1,000 barrels) as they have a wish to protect themselves against rising prices. It is assumed that the future was originally entered into at a price of USD 63.00/bbl. The two parties enter an EFP (probably via a broker) whereby the producer will agree to sell the physical crude oil to the refiner and buy an equivalent futures position. The refiner will take delivery of the crude oil and agrees to sell their existing futures position. Both parties agree to reference the EFP to the shortest-dated futures contract, which is now assumed to be trading at USD 62.00. They agree to a differential of +USD 0.10 to reflect the difference in crude quality, the location where the crude will be delivered to, and the appropriate date. Both parties will then be obliged to register the EFP with the relevant exchange.

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From the producer’s perspective, they will sell their physical crude oil at a price of USD 62.10, but since they now have a long futures position initiated at USD 62.00, the final value of the commodity will only be determined when this position is closed. They are at liberty to close this position whenever they want and may choose to do so over a period. However, for ease of illustration let us suppose it is closed immediately at the same futures price used to settle the EFP. They will make no profit or loss on the futures position since it was opened and closed at the same price, so the final value of their physical sale is USD 62.10. From the refiner’s perspective, they have: ▪ Agreed to purchase physical crude oil at USD 62.10. ▪ Closed out a long futures position established at USD 63.00 at a price of USD 62.00 to realize a USD 1.00/bbl. loss. ▪ Therefore, the cost of their physical purchase was USD 62.10 + USD 1.00 = USD 63.10. Like the producer, the refiner is not obliged to close out the entire futures position when entering the EFP. For example, many of their refined products will be sold on a rateable basis throughout a month and so the price they receive for these may be calculated as some form of average. It would seem logical that the refiner may also wish to price their crude oil expense on a similar basis, and so may decide to unwind their futures hedge on a piecemeal basis over a similar time horizon. 6.8.2.6

Summary

Table 6.7 compares the main features of the three main types of Brent contract.

6.8.3

US crude oil markets

The main type of crude oil traded in the USA is West Texas Intermediate (WTI). This is usually quoted for delivery at Cushing, Oklahoma, although S&P Global Platts does provide quotes for alternative delivery locations such as Midland, Texas. There is a range of other crude oil markets with different delivery locations that include: ▪ ▪ ▪ ▪

West Texas Sour (delivered into Midland Texas). Light Louisiana Sweet (St. James, Louisiana). Mars (Clovelly, Louisiana). Alaska North Slope (Long Beach, California).

Physical WTI price quotations are driven by the pipeline companies’ requirement that all deliveries for a given month be notified by the 25th of the previous month. So, for the period of 26 March–25 April the quoted price on any single day is a representation of crude oil transactions to be delivered during the month of May. On 26 April, the oil price will be reflective of transactions to be delivered during June. Another price index worth mentioning is the ‘American Sour Crude Index’ or (ASCI). This is published daily by the price reporting agency Argus Media and

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TABLE 6.7 Summary of Brent contracts.

Exchange or OTC Underlying asset Pricing point

Exposure period

Loading date

Standard size (bbl.) Settlement

Dated Brent

Brent forward

Brent futures

OTC

OTC

Exchange

Brent, Forties, Oseberg, Ekofisk, Troll FOB – various locations in North West Europe Spot price of crude referencing agreed transactions 10 days – one-month post publication Specific date agreed in contract

Brent, Forties, Oseberg, Ekofisk, Troll FOB – various locations in North West Europe 1st–31st of the quoted calendar month; greatest liquidity in near dated contracts Nominated by seller at least one month prior to delivery

Brent, Forties, Oseberg, Ekofisk, Troll

600,000

600,000

Physical settlement by means of EFP with an option to cash settle against Brent Index 1,000

Physical

Physical/cash

Physical/cash

FOB – various locations in North West Europe Consecutive calendar months out to about 8 years

represents the price of medium sour crude on the US Gulf Coast. This became popular when Saudi Arabia decided to reference their US sales of crude away from WTI to an index that they felt more closely resembled the product they were looking to sell. The index is now also used by Kuwait and Iraq when selling into the USA. The component crude oils are Mars, Poseidon, and Southern Green Canyon. Futures on crude oil and several related petroleum products are offered on the CME Group exchange, with maturities extending to 10 years. Their light, sweet, crude oil contract is physically deliverable by pipeline at Cushing, with each lot consisting of 1,000 barrels (42,000 US gallons). The contracts expire on the third business day prior to the 25th calendar day of the month preceding the delivery date. This allows the expiry of the future to dovetail into the settlement conventions of the physical market noted above. So, if a participant were trading a future with May delivery this contract would expire on 22 April, allowing any short that decides to go to final settlement three days to make the necessary arrangements to schedule the delivery. Despite allowing for physical settlement most futures positions are closed out before contract expiry, which means that buyers sell out of their positions at prevailing market prices whilst sellers do the opposite. Closing out of positions occurs even in situations where market participants wish to buy or sell physical quantities. This is because the standardised terms of futures delivery are usually too restrictive for physical market participants. The CME Group also offers contracts on several refined products, some of which are summarised in Table 6.8.

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TABLE 6.8 Summary of CME contract specifications.

Contract Size Quote Minimum price fluctuation Traded periods Delivery/ Settlement Delivery location

Brent Crude

NY Harbor Ultra Low Sulfur Diesel (ULSD)

RBOB Gasoline

1,000 barrels USD and cents per barrel 0.01 USD per barrel

1,000 barrels USD and cents per barrel 0.01 USD per barrel

42,000 gallons USD and cents per gallon 0.0001 USD per gallon

42,000 gallons USD and cents per gallon 0.0001 USD per gallon

Current year and the next 10 years Physical

Current year and the next seven years Cash

Three years

Three years

Physical

Physical

Cushing, OK

N.A.

New York Harbor

New York Harbor

West Texas Intermediate (WTI)

Source: Based on CME Group

NOTES ▪ At the time of writing, the CME also offered a cash settled WTI contract. ▪ The ULSD contract may be casually referred to as a heating oil (HO) contract. Heating oil is diesel fuel although it may contain a coloured dye to indicate it cannot be used in vehicles for tax reasons. ▪ RBOB stands for Reformulated Gasoline Blendstock for Oxygen Blending. To sell a refined product, it has to meet a series of technical and legal/environmental specifications. Intuitively, RBOB can be thought of as a common building block used in the process of producing gasoline. It is analogous to base metals futures, where the contract specification is an intermediate rather than a final product. 6.8.3.1

Calculating the price of US physical crude oil

Although the reader may feel the inclusion of this topic after a discussion of the futures market is somewhat odd, the pricing of physical crude oil is significantly impacted by futures prices. Suppose a producer is considering selling physical WTI crude oil at Cushing during the month of May. He and the consumer agree to use the conventional pricing method of: NYMEX calendar month average (CMA) plus the NYMEX roll Figure 6.20 helps illustrate the concept and the associated timelines. The CMA component means that for the delivery month of May, part of the agreed payment will consist of the arithmetic average of the front month futures settlement

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NYMEX roll

Calendar month average

Daily calculation over the period:

Arithmetic average of front month futures settlement price for delivery month

((M1 futures price – M2 futures price) x 0.6667) + ((M1 futures price – M3 futures price) x 0.3333) The roll is the arithmetic average of the daily calculations

Individual trading days

25th April

1st May

Individual trading days

31st May

FIGURE 6.20 Calculating the NYMEX roll and the calendar month average.

prices observed over that month. This means that the final price will not be known until after the last trading day of the respective delivery month. However, during the month of May the futures price is initially referencing prices for June delivery before it expires towards the end of the month, when July maturities becomes the front month contract. The NYMEX roll component adjusts this price to make it more representative of prices for May delivery. Refer again to Figure 6.20. The May futures will be the front month contract from the period 26 March–25 April.8 For each day of this earlier period, the following calculation is performed: ((Month One futures price − Month Two futures price) × 0.6667) + ((Month One futures price − Month 3 Three futures price) × 0.3333) By way of illustration suppose that on the 26th March the following settlement prices were observed: May (month 1) June (month 2) July (month 3)

40.28 40.58 40.87

The calculation for that day would be: = ((40.28 − 40.58) × 0.6667) + ((40.58 − 40.87) × 0.3333) = −0.20 + −0.10 = −0.30

8

Assuming the 25th is a good business day, the May contract will expire, and June will become the front month.

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This value would be calculated for each business day over 26 March–25 April period with the NYMEX roll being the average of the results. So if CMA for May is calculated as, say, USD 41.00 and the NYMEX roll was −USD 0.50 then the producer will receive USD 40.50 for each barrel sold, irrespective of when during the agreed month they may have been delivered.

6.8.3.2

Negative WTI prices

As the manuscript for this book was being prepared, a significant number of countries introduced radical social and economic measures to prevent the spread of COVID-19. As a result, the demand for crude oil fell faster and farther than at any point in history (Economist, 2020). Economic activity slowed considerably, and so more crude oil was being placed into storage. Since WTI is a landlocked crude oil with a pricing point at Cushing, Oklahoma, the availability of storage at this location has a significant impact on the reported price. On 20 April 2020 for the first time in its history, WTI crude oil for May 2020 physical delivery closed at a negative price. The market opened at USD 17.73/bbl. and traded as low as USD −40.32 to eventually close at USD −37.63, a daily range of USD 58.05. The May 2020 contract eventually expired the following day at USD 10.01/bbl. Arguably this was because of the structure of the WTI market as the price for Brent crude oil remained positive. Section 12.7 illustrates the concept of a short squeeze whereby participants with short futures positions may end up pushing the price market price higher to avoid having to go to physical delivery. Since the price of crude oil collapsed, then this implies the opposite; there must have been participants who were long the futures and realised if they were unable to close out their positions they would have to take physical delivery. This would mean that they would then be forced to either move the crude oil out of Cushing or place it into a local storage facility. At the time, the EIA reported that stocks in Cushing were approximately 60 million barrels and with the installation’s working capacity estimated at 76 million barrels, so it was about 79% full. According to figures published by the CME Group, the open interest (i.e. outstanding contracts) as at the close of 20 April 2020 was 13,044 contracts, equivalent to 13,044,000 barrels. If all these contracts had gone to final delivery, then storage capacity at Cushing would have been very close to its limit. Indeed, reports (Financial Times, 2020a), suggested that it was highly likely that much of the apparent storage availability had been booked to accommodate future inflows. So it seems likely that rather than be faced with the issue of trying to dispose of oil that could be neither stored or transported out of the area, many ‘longs’ were willing to sell at any price. Of course, in the end, a negative oil price means these longs were paying to sell their oil. There were also suggestions that investor activity may have exacerbated the problem. An investor who uses a future to gain a bullish exposure to crude oil would go long the contract but would need to ‘roll’ this exposure as the maturity approached to avoid physical delivery. The rolling process involves selling out of the existing long position and re-establishing the long position in the next available maturity. If the investor position were relatively large, then the selling pressure to instigate the roll would lead to further downward pressure on the price.

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6.9

MANAGING PRICE RISK ALONG THE SUPPLY CHAIN

Section 6.3 provided an overview of the crude oil supply chain. Based on that analysis, it is possible to identify the different risks that are faced by each of the participants. Producers – exposed to the absolute price of crude as well as an adverse move in quality differentials. The exposure to the level of crude oil prices is sometimes referred to as ‘flat’ price risk. Refiners – on the assumption that they have purchased the oil on an FOB basis, there are several exposures to consider: ▪ ▪ ▪ ▪

The cost of financing the purchase. Freight and insurance costs. Costs of storing the crude oil or refined products. Refinery margins (‘crack spreads’) Consumers – they may be exposed to:

▪ The absolute price of the refined product. ▪ A movement in the price differential between the location used to price the commodity and the end location to which it will be delivered. ▪ The fact that a liquid hedge for their product may not exist and so may be forced to implement a proxy hedge (e.g. hedging jet fuel exposures with crude oil). Some of these risks will be considered below but for space purposes other topics will be considered in separate chapters (e.g. financing and freight costs).

6.9.1

Producer Hedges

In the following examples, structures that are unique to crude oil are emphasised. To avoid repetition, interested readers are referred to the chapter on base metals for generic vanilla and exotic option strategies. Exchange traded futures Although the use of futures would appear to be straightforward, there is the possibility that an element of basis risk may exist. Basis risk is used to describe several different situations, which include: ▪ Using futures in one product to hedge an underlying exposure in another (e.g. using crude oil futures to hedge a jet fuel exposure). ▪ A mismatch between the timing of the exposure and the protection period covered by the future. ▪ Termination of a futures hedge prior to maturity, where there is an underlying physical exposure. Here the basis risk is that the cash and futures prices have not moved in parallel resulting in a hedge that is not 100% efficient.

Crude Oil

213

▪ Physical delivery of the commodity in a location that differs from that used to price the hedging instrument. ▪ Quality differences between the physical exposure and that specified by the hedging instrument (e.g. hedging a Bonny Light exposure with a Brent Future). Consider an example of a US oil producer who in early December is looking to hedge the price risk of his planned production in the first quarter of the following year. He has agreed to sell 50,000 barrels per month to a refiner in each of the first three months. The contract will be settled on a floating rate formula with the final agreed price based on the average of quoted S&P Global Platts prices, published daily in the month preceding the delivery of the crude oil. So, for the 50,000 barrels to be delivered on the first business day of January, the price paid by the refiner will be the average of the S&P Global Platts WTI prices published daily in December. The February delivery will be based on the average of January prices, and a March settlement will be based on the average of February prices. If the producer was concerned about a fall in the price of WTI, then he could sell three lots of 50 futures contracts to mitigate the risk. In a perfect world each futures contract would have a maturity that matches the underlying physical deliveries. However, it is not that simple with the WTI contract. His January delivery will be priced at the average of December’s cash prices and so the final price will not be known January. At that point in time the January WTI future will have expired. (The WTI contract expires three business days prior to the 25th calendar day of the month preceding the delivery day). Hence, he may choose to hedge the December price movements using a February contract, which will mature towards the end of January. Because the price exposure of the physical sale and the futures cover different time periods, the producer runs the risk that the cash and futures prices will not move in tandem; one example of basis risk. Fortunately for the hedger, the chances of futures and cash prices decoupling, i.e. the basis risk, is usually less of a concern than the absolute price risk. The following example illustrates the concepts. On this occasion we have assumed that the physical oil contract was priced at a single point in time. On 1 December a producer enters into a long term contract whereby he agrees to sell forward 50,000 barrels per month of physical WTI crude oil for the first three months of the following year according to a price equal to the S&P Global Platts assessed price for WTI at Cushing on the first good business day of each month. The producer fears that cash prices may decline over the period resulting in lower revenues. To hedge their exposure to the pricing windows at the start of each month, the producer decides to initiate a short hedge by selling a strip of futures contracts. Hence to hedge its January, February, and March sales, it sells February, March, and April CME WTI futures. On the pricing days in question the prompt month futures position is bought back at the prevailing market rate to unwind the hedge. Sometime after each pricing date the producer delivers 50,000 barrels of oil and receives a cash amount based on the S&P Global Platts assessments in return. Table 6.9 shows the outcome of the hedging programme and the effective price realised by the producer. Table 6.9 shows that the producer was able to lock in an average price of 68.28 USD/bbl. for its sale and that this outperformed an un-hedged position which would

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TABLE 6.9 Producer hedge using WTI futures.

Date

Physical

Futures

Dec 1

Sells 50,000 bbl. per month on a forward basis for Jan, Feb, and March delivery S&P Global Platts cash price = 68.37 S&P Global Platts cash price = 67.93 S&P Global Platts cash price = 67.55 S&P Global Platts cash price = 68.79

Sells 50 lots per month of WTI: February = 69.67 March = 70.04 April = 70.63

Jan 1 Feb 1 Mar 1

Buy 50 lots February = 69.32 Buy 50 lots March = 69.29 Buy 50 lots April = 71.15

Futures Gain/Loss (USD/bbl.)

Effective Price (USD/bbl.)

(69.67 − 69.32) = 0.35 (70.04 − 69.29) = 0.75 (70.63 − 71.15) = −0.52

(67.93 + 0.35) = 68.28 (67.55 + 0.75) = 68.30 (68.79 − 0.52) = 68.27

Average S&P Global Platts cash price = (67.93 + 67.55 + 68.79)/3 = 68.09 USD/bbl. Average effective price = (68.28 + 68.30 + 68.27)/3 = 68.28 USD/bbl.

have yielded a lower average price (USD 69.09) over the same period. On the other hand, had prices evolved in a positive direction then they would have locked in its sales revenues at the expense of being able to benefit from a price rise. It is important to note that the effective sale price of 68.28 USD/bbl. was not quite equal to the prevailing cash price at the time the hedge was initiated (68.37 USD/bbl.). This is because cash prices and futures did not always move in tandem during the period in question. The basis can be quantified as the spot price minus the future price and its evolution for this trade is documented in Table 6.10. In all the examples the basis decreased (i.e. became more negative). The basis at the closeout can also be used to determine the effective price paid for the crude oil using the following relationship: Original futures price plus basis at closeout = effective price of crude TABLE 6.10 Evolution of the basis.

Initial value for basis Value of basis at close out of future

February futures

March futures

April futures

68.37 − 69.67 = −1.30

68.37 − 70.04 = −1.67

68.37 − 70.63 = −2.26

67.93 − 69.32 = −1.39

67.55 − 69.29 = −1.74

68.79 − 71.15= −2.36

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Crude Oil

To illustrate, consider the physical consignment to be delivered in January. The original February futures price was 69.67 USD and the basis on close out was −1.39 USD (67.93 − 69.32). This would infer an effective sale price for the crude of 68.28 USD, which indeed was the case: 69.67 − 1.39 = 68.28 In executing this hedge, the producer took on the risk that the cash WTI price would weaken even further relative to the prompt WTI futures contract. The producer was willing to take this risk having determined that the basis between cash WTI and futures was far less volatile than the outright cash price. That is, they would achieve a less favourable sale price if the basis decreased or became more negative. For example, on the close out of the February future, the effective sale price would only have been 67.67 USD if the basis had been −2.00 USD. Hedging crude oil priced over a multi-day loading period In some cases, the physical supply contract would be based on an average of prices over a period to reflect the loading period. In this case the futures position would have to be unwound in equal amounts as the physical contract is priced. So, if the physical contract is priced as the average of prices over five days, then 1/5 of the futures hedge would have to be unwound daily. Suppose it is late May and a producer of crude oil is looking to sell 300,000 barrels of crude oil for delivery in three months’ time (e.g. late August). They agree to a commercial contract with an oil refiner whereby the cost of the physical crude oil will be based on the average of the ‘near month’ future’s closing price over the three days it will take to load the cargo onto the refiner’s vessel. In the market jargon the producer is ‘long’ the market, i.e. they will be adversely impacted by falling prices. As a result, they decide to sell futures to hedge their exposure. So, at the end of May, the refiner decides to buy 300 October contracts, as this will be the ‘near month’ contract on the expected delivery date. The example assumes that each contract is for 1,000 barrels and that the contracted futures price is USD 59.37. Suppose that the closing futures prices for the ‘prompt’ contract for each of the three August delivery dates turn out to be: Date #1 Date #2 Date #3

USD 62.00 USD 63.50 USD 61.25

Under the terms of their physical contract with the refiner, the producer receives the average of these three values multiplied by the number of barrels. The average of these three prices is USD 62.25/bbl. so for the 300,000 barrels this amounts to USD 18,675,000.

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The producer decides to unwind 1/3 of his futures position at these closing prices; that is, he sells 100 futures every day. The resulting profit and loss are as follows: Date #1: USD 62.00 − USD 59.37 = USD 2.63 loss Trader buys 100 futures (i.e.100,000 barrels) On 100,000 barrels this equals a loss of USD 263,000 Date #2: USD 63.50 − USD 59.37 = USD 4.13 loss On 100,000 barrels this equals a loss of USD 413,000 Date #3: USD 61.25 − USD 59.37 = USD 1.88 loss On 100,000 barrels this equals a loss of USD 188,000 Total profit and loss on futures position = USD 263,000 + USD 413,000 + USD 188,000 = USD 864,000 loss The amount received by the producer considering their futures hedge would be: Income received from sale of physical crude minus futures loss = USD 18,675, 000 − USD 864,000 = USD 17,811, 000 On a per barrel basis this is equal to selling crude oil at a price of USD 59.37 – a sum equal to the original futures price. Admittedly, since prices increased then with hindsight, the producer would have been better off doing nothing but the example shows that the futures represents a binding commitment and do not possess the asymmetry of options. The hedge was 100% efficient, but this is unlikely to be the case: ▪ It is assumed that the underlying crude oil and the future are for the same type of crude oil (e.g. Brent). ▪ The pricing of the physical contract references a futures contract rather than another index. This allows the hedge to move in line with the underlying asset price. ▪ The termination of the futures hedge was done at the closing price, which also determined the price of the physical contract. Crude oil swaps A crude oil swap could be used to transform a specific price risk faced by a client. Let us say that a producer has a contract to sell oil on an ongoing basis at a fixed price.

Crude Oil

217

The producer believes that the price of crude will rise and so wishes to benefit accordingly. The refiner enters a crude oil swap where they agree to pay a fixed price per barrel (say USD 50.00) to receive a floating benchmark price such as the average of exchange traded futures prices. Depending on how the swap is structured the fixed cash flows should cancel and the net effect is that the producer ends up selling crude oil on a floating price basis. Although somewhat ambiguous, the market may use the terms ‘buy’ and ‘sell’ in relation to the swap instrument. Here we will define the purchase of a swap as an instance where an entity pays a fixed price and receives the floating or variable index. Selling a swap will be defined as a receipt of fixed against a payment of floating. To avoid ambiguity, it is perhaps preferable to state who is paying or receiving fixed. The swap transaction presented here covers an exact calendar month with the fixed price set at USD 50.00 payable by the producer. The floating index will be based on a straight average of futures prices published daily by the relevant exchange over the period of the contract month. At the end of the calculation period let us assume that the average futures price was USD 49.50 and that the contract was executed on 70,000 bbl. Just like all swap contracts, when cash flows are timed to coincide a single net payment is due. The producer would therefore be a payer of USD 0.50 per barrel under the terms of the swap. When translated into a cash amount (there is no physical delivery of crude oil under the swap) this would equate to USD 35,000 (70,000 barrels x USD 0.50). The producer will sell their physical crude oil at the agreed fixed price but for this month their income will be reduced by the net swap settlement amount. Even though they have incurred a loss the example illustrates that on a net basis they are selling oil on a floating price basis. Table 6.11 summarises the main types of swap and their respective settlement prices. Table 6.11 shows certain swaps, which mirror the underlying physical markets with respect to locations and delivery modes, e.g. Barges FOB Rotterdam. In the case of such a price assessment, the first criteria refers to the type of delivery vessel (Barges), the middle term (FOB – Free on Board) relates to how the delivery will be priced, whilst the third criteria refers to the delivery location (Rotterdam). Table 6.11 shows the main type of fixed for floating swap by product basis; there are several alternative ways in which the cash flows can be calculated: ▪ Fixed price vs. quoted futures price: these ‘futures swaps’ are usually traded against the ‘front’ month and might be applicable for those who have priced their physical deliveries against either basis but wish to transform it to the other. Due to the expiry dates of the futures, which are typically during a month rather than at the end, the price of a swap will consist of futures prices from two different months. ▪ Index price vs. index price: this might be executed as a deal based on two different indices. A possible example might be Dated Brent against Urals. A swap done on these indices would be structured in the traditional fixed vs. floating format but the fixed price will take its value from the differential between the two indices. The floating payment will be based on the actual differential that is observed over the agreed payment period for the swap.

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TABLE 6.11 Frequently traded crude oil and refined product swaps. Underlying Commodity

Settlement price

Brent

Average of daily settlement price of prompt ICE futures contract. Average of daily published S&P Global Platts assessment. Average of daily settlement price of prompt CME futures contract. Average of daily published S&P Global Platts assessment. Average of daily published Asian Petroleum Pricing Index assessment. Average of daily published Argus assessment.

Dated Brent WTI Dubai Tapis Gasoline 10 ppm 95 Ron Barges FOB Rotterdam CME RBOB Gasoline ICE gas oil CME Ultra Low Sulfur Diesel Gas oil 0.1% Sulfur Barges FOB Rotterdam Gas oil 0.25% Sulfur Cargoes FOB Singapore Fuel oil 3.5% Sulfur Barges FOB Rotterdam Fuel oil 2% Sulfur Cargoes FOB Singapore

Average of daily settlement price of prompt CME futures contract. Average of daily settlement price of prompt ICE futures contract. Average of daily settlement price of prompt CME futures contract. Average of daily published S&P Global Platts assessment. Average of daily published S&P Global Platts assessment. Average of daily published S&P Global Platts assessment. Average of daily published S&P Global Platts assessment.

Note: For the gasoline contract 10 ppm indicates there are 10 parts of lead per million.

As to when someone would use this type of swap, a possible scenario would be where a refiner buys a cargo of Urals and decides to hedge it with Brent futures given the absence of a futures market in his particular cargo. To hedge the basis risk that exists between the two cargos, the refiner enters a swap to lock in the differential between Urals and Dated Brent. Although it may seem easier for the hedger to do a fixed/floating based purely on the price of Urals, this would not be executed due to poor liquidity. The hedger is then exposed to a change in the Dated Brent–Brent futures differential. ▪ Index price vs. futures price: this type of swap would be quoted as an index price against a futures price, e.g. Dated Brent vs. ICE Brent futures. ▪ Crude oil vs. products: equally there may be swaps based on different refined products. For example, the swap could involve the exchange of cash flows based on the price of crude oil against one of the refined products such as gasoline. Equally the contract might be structured with cash flows based on the price of fuel oil, against that of electricity.

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Crude Oil

Hedging swaps with futures Dealers who enter into long-dated swaps in an illiquid product may be forced to hedge the exposure using crude oil futures. This will give them what is sometimes referred to as a ‘crack position’ (i.e. an exposure in a refined product against crude oil). For example, suppose that a bank executes a jet fuel swap with an airline such as the one illustrated in Figure 3.1. In simple terms, the bank will lose money on the swap, if the price of jet fuel were to increase above the fixed price. A possible hedge would be to buy crude oil futures. The logic being that if jet fuel prices rise, then (hopefully) crude oil prices will rise to generate a profit on the futures position to offset the loss on the swap. This, however, raises a few questions: How many futures does the trader need to execute? One possible answer to this question would be for the trader to perform some form of regression analysis. This technique describes the relationship between a dependent and independent variable. In this instance the dependent variable would be the price of jet fuel whose value is predicted based on movements in the independent variable, which would be the crude oil future. The first step would be to create a scatter graph of the data and to determine a ‘line of best fit’ whose mathematical form would be: Δy = 𝛼 + βΔx + ε Where: Δy = the change in jet fuel prices (the dependent variable) 𝛼 = a constant; the value of Y even if X has zero value β = the regression co-efficient. This represents the slope of the line of best fit. Δx = the change in crude oil futures prices (the independent variable) ε = the error term.This reflects the fact that other factors may influence the value of Y and are not captured by the specification of the equation. Suppose that the regression equation derived from the data is: Y = 0.001244 + 0.50x If, for ease of illustration, the value of the constant is ignored then the regression result shows that a one-unit change in X (i.e. crude oil prices) is associated with a 0.50-unit change in Y (i.e. jet fuel prices) over the sample period. Admittedly, the values used in the equation were used to illustrate the principles. If jet fuel prices move by USD 1.00 this would be associated with a USD 2.00 move in crude oil prices. Since the crude price is more volatile than jet fuel price the trader would need a smaller futures position to hedge the jet fuel exposure.

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There are problems associated with this technique. What is the reliability of the regression result? The value of the regression co-efficient will also be a function of the sample period. In addition, there is no guarantee that the historical relationship between the two variables will extend into the future. Which maturities should be traded? Broadly speaking, a trader could execute either a ‘stack’ or ‘strip’ hedge. A stack hedge would require the trader to buy all the required futures in a single maturity, which may well be the nearest dated contract. Since the maturity of the swap would be greater than the maturity of the hedge, this position would need to be ‘rolled’ as the future approaches maturity. The rolling procedure requires the trader to close out the existing position and then reopen a new position in the next maturity. In this case, since the trader is long the future, they would need to sell futures to terminate the exposure and then buy futures in the next maturity to maintain the hedge. A ‘strip’ hedge would consist of a series of futures with sequential maturities spread out over the life of the underlying swap. Which strategy is more effective is a debatable issue. Although a strip hedge mirrors the maturity of the underlying swap it may be that there is no liquidity in certain maturities, i.e. although the trader may wish to buy a future, there may not be a willing seller. How effective will the hedge be? Hedging a jet fuel exposure with crude oil is not going to be a perfect hedge. It does assume that the two energy products will be positively correlated by virtue that there is a chemical relationship between the two. Although there is a strong reason to suggest this may be the case, there is no guarantee that this price relationship will hold in all circumstances. How will the hedge impact the price of the swap? There is an old market adage that says the price of a derivative is a function of the underlying hedge. So if the trader offers a jet fuel hedge to a customer, who is hedged somewhat imperfectly with crude oil futures, the trader may decide to make an adjustment to the fixed price receivable on the swap to protect them from an adverse move in the value of the hedge. Two-asset barrier options Two-asset barrier options were introduced in the gold chapter but to show their flexibility, they are illustrated here within a different context. In this section, the scenario is based on a non-US crude oil producer who will receive USD revenues but may wish to convert them to another currency such as EUR. The conventional way of doing this would be using a standard FX option. A stylised term sheet for a EURUSD FX option would have the following terms: Notional:

EUR 50 m

Reference currency pair: Maturity: Current spot rate: Strike: Premium:

EURUSD One month EUR 1.00 = USD 1.1500 EUR 1.00 = USD 1.1524 (ATM forward) USD 0.0106 per EUR of notional (50 m × USD 0.0106 = USD 530,000)

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For readers unfamiliar with FX option market conventions there are a few points to note: ▪ It is not sufficient to refer to an FX option as a EURUSD call in the same way one might with a crude oil call. Conventions vary between FX markets so the term call could refer to the base currency (EUR in this case) while in other markets it may refer to the quoted or counter currency. Since the purchase of one currency requires the sale of another then to avoid confusion it is better to say that in this instance the producer has purchased a EUR call-USD put. ▪ Like all options the premiums are quoted in the same units of the underlying. A EURUSD exchange rate expresses the number of USD to buy or sell a unit of EUR. Therefore, the premium is the number of USD per unit of EUR. In this case it is just over one cent for every EUR. Since there are 50 m units of the base currency then the premium is scaled appropriately to give a value of USD 530,000. ▪ If the client wishes the premium to be expressed in the base currency, then this is converted using the spot rate. In this case it would generate a premium of EUR 460,870. ▪ Some clients may also like the premium to be expressed as a percentage of the notional amount so in EUR terms it would be 0.92% (EUR 460,870/EUR 50 m). One of the ways to reduce the premium cost of this FX hedge would be to structure the option to knock out when commodity prices are high. With high crude oil prices producers are likely to be cash rich and maybe willing to sacrifice some degree of FX protection. Based on the previous figures a two-asset barrier which knocks out with high oil prices may look as follows: Notional:

EUR 50 m

Asset 1: Maturity: Current FX spot: Strike: Asset 2: Asset 2 barrier: Current crude price: Payoff:

EURUSD One month EUR 1.00 = USD 1.1500 EUR 1.00 = USD 1.1524 (ATM forward) Brent Crude Oil USD 65.00/bbl. USD 60.00/bbl. If the FX spot rate at maturity is greater than EUR 1.00 = USD 1.1524 AND the Brent crude price is less than USD 65.00/bbl., then option buyer will receive EUR 50 m in exchange for USD 57,620,000. Otherwise no exchange will take place.

From the producer’s perspective since they are receiving USD, they are at risk that this currency will depreciate relative to the EUR. A USD depreciation (weakening) means that the exchange rate will move in such a way that they will have to give up more USD per EUR.

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The expected correlation between the two assets is a crucial component of this type of option. The following premiums would apply depending on the value of the correlation input: −1 0 +1

USD 0.0106 USD 0.0101 USD 0.0080

There are some interesting features to highlight from this structure: ▪ The correlation input measures the strength of the relationship between the crude oil and the underlying currency, which is EUR not USD. ▪ A negative correlation of −1 means that the option trades at the same premium as the vanilla FX option. This is the correlation between the EUR (not the USD) and the price of crude oil. So, if the EUR strengthens (the USD weakens) this will always be associated with a fall in the price of crude oil. Therefore, the option will never knock out and so will be indistinguishable from the vanilla structure. ▪ A positive correlation of +1 means that if the EUR weakens (USD strengthens) this will be associated with a decrease in the price of crude oil and so the option will not be knocked out. Although the option will not get knocked out, it will not be exercised, as the FX component will be out-of-the-money. In the spot market the FX rate will be less than the strike meaning the producer would be better off walking away from the option because in a spot deal they would give up fewer USD per EUR. ▪ The monitoring of whether the price of crude oil breaches the barrier is mostly done on a continuous basis. If, however, it were a ‘European’ barrier when it was only monitored at maturity then using the zero-correlation premium as an example, the cost of the option would increase. Since the barrier is only monitored once during its life, the chances of crude oil being above the barrier on the expiry date is relatively lower than had it been monitored on an on-going basis. This reduces the likelihood that the option would be knocked out, making a payout more likely and therefore increasing its cost. ▪ The barrier on this structure is relatively close to the current price of crude oil. If the barrier were to be increased, the cost of the option would increase as the chance of it being knocked out reduces. One of the reasons for this is that when pricing the option an implied volatility of 20% p.a. was used. A trader’s rule of thumb would be to convert this value to a monthly equivalent and apply it to the current spot rate to see the range of values that are expected to trade over the life of the option. Since the option has a one-month expiry it is tempting to divide the annual volatility by 12, but the correct approach is to divide by the square root of this value. Since the square root of 12 is approximately 3.46 this would return a monthly equivalent value of 5.78% (20/3.46). Applying this figure to the current crude oil price of USD 60.00

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suggests a range of values of +/− USD 3.47 (USD 56.53 to USD 63.47). So, the closer the barrier is to the spot price the greater the chance the option will knock out and so as a result the premium will be lower. Using the same volatility for a one-month period with a higher barrier of, say, USD 70.00 means that the option is very unlikely to be knocked out and so will trade closer to the value of a vanilla FX option.

6.9.2

Refiner hedges

The demand for crude oil arises mainly from refineries. In theory, the refiner could choose to hedge the cost of their crude oil or their income from selling refined products or both. Hedging the cost of crude oil Suppose a EUR-denominated refiner is looking at different swap structures to manage the cost of their crude oil purchases. One possible solution is an FX-linked swap that has embedded optionality. A term sheet may look as follows: Underlying asset: Current price: FX pair: Maturity: Cash flow frequency: Fixed price: Fixed price payer: Floating price: Floating price payer: Reset condition:

FX barrier: Reset fixed price:

Crude oil USD 70.00 EURUSD Two years Monthly USD 60.00, subject to possible reset Refinery Monthly average of prompt futures price Bank If on any date during the life of the swap, the EURUSD exchange rate is above the FX barrier then the fixed price on the swap is reset from that point until maturity. EUR 1 = USD 1.2500 (current spot EUR 1 = USD 1.1500) USD 85.00

If we assume that the refinery buys its physical crude oil based on an ‘average of month’ basis that references the futures price, then the floating swap cash flow received under the swap could be used to finance this payment. As a result, the fixed rate on the swap would represent their net cost of buying the crude oil. From an FX perspective, a weakening of the USD (strengthening of the EUR) would generally be beneficial, as it would mean they would give up fewer EUR to acquire the USD that they require to buy the physical crude. However, note that in this case, if the FX rate does move in a favourable manner, the fixed price will reset to a level that is considerably higher than the current price of crude oil. The refiner’s cost of buying their physical crude oil will therefore increase.

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▪ The fact that the refiner is able to initially obtain a favourable fixed rate on the swap that is USD 10.00 below the current price suggests that they have sold some form of optionality and rather than receive an explicit premium, their ‘payment’ is in the form of a subsidised fixed rate. ▪ Note that if the rate is reset, this can happen at any time, which suggests a barrier that is monitored on a continuous basis (a so-called ‘American’ barrier). ▪ The activation increases the fixed amount payable for the remaining life of the swap to a single higher rate. This suggests that the embedded optionality has a digital type of payout. ▪ Since the activation of the digital barrier is dependent on an FX rate, it would be classified as a hybrid structure that will require some form of correlation input for valuation purposes. Hedging the crack spread using exchange traded futures Refiners will be buyers of crude oil and sellers of refined products. Given the nature of their different inputs and outputs they are exposed to a change in the differential between the two prices. This is sometimes referred to as the crack spread, which derives it name from the refining process where the crude oil is ‘cracked’ into a variety of different outputs. The crack spread measures the income earned from the sale of refined products to the cost of crude oil. Figure 6.5 shows generic refinery margins in different geographical locations. They are based on a single crude oil appropriate for that region and optimised refined product yields based on a generic refinery configuration, also appropriate for each region. The margins are expressed as a semi-variable basis in that all variable costs (e.g. energy costs incurred in the production of the products) are included. A positive margin is one where the income received from the sale of the refined products is greater than the cost of buying the crude oil. Refinery margins in the USA tend to be higher as they are more constrained in terms of capacity than Europe or Asia. The refiner can hedge against a fall in this margin by fixing the spread using a future, OTC forward or an option. One of the most popular strategies in this area is the 3:2:1 futures crack spread. This is a single transaction that is composed of three crude oil futures, two gasoline futures, and one heating oil contract. This reflects the fact that broadly speaking a typical refinery configuration will be such that a barrel of crude will yield twice as much gasoline than heating oil. As a result, every three barrels of crude will yield two of gasoline and one of heating oil. Although refineries will also produce fuel oil and naphtha, there is no futures market for these products and so the exposures cannot be easily hedged. To hedge a decline in the margin, the refiner would sell the crack spread, which would involve a purchase of the requisite number of crude oil contracts and the sale of refined product contracts (gasoline and heating oil). Note that the action of selling or buying the spread refers to the nature of the refined product transaction. The spread will usually have a time dimension to reflect the speed with which the crude oil is refined. Hence the refiner may sell longer-dated refined product futures than the purchased crude oil future.

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Although the futures hedge will fix the refining spread, it is by no means a perfect hedge, as the refinery runs two secondary basis risks. The first relates to differences in the delivery location between the physical transaction and derivative hedge. This will be reflected in the price of the different contracts and there is no guarantee that they will move in tandem. For example, assume that a US refiner decides to buy crude oil for delivery on the US Gulf Coast (USGC) with a similar quality as that of the WTI future (e.g. Bonny Light). He is likely to sell his gasoline output also for delivery at the same location (USGC). If futures are used to hedge the refining margin, the crude oil contract will be priced for delivery at Cushing while the gasoline contract is based on delivery at New York Harbor (NYH). This means they have exposure to the Cushing/USGC price differential on the crude oil exposure and NYH/USGC price differential on the gasoline contract. The second source of basis risk lies in the quality of the underlying physical products and that specified in the futures contract. Hedging the crack spread using OTC swaps It is assumed that a refiner is proposing to hedge its production revenues for a future fourth quarter. In the physical market they agree to purchase 480,000 barrels of Brent crude oil according to a uniform pricing schedule based on the daily S&P Global Platts Dated Brent assessment in October, November, and December. In addition to this, the refiner agrees to sell 480,000 barrels of its refined products according to several other published assessments over an identical time frame. The details of the refiner’s production profile are given in Table 6.12. For the sake of simplicity, it has been assumed that there are no waste products in this refining process although in practice this would not be the case. We will also assume the refiner is unwilling to execute a futures-based transaction, as it does not want to be exposed to the basis risks. Furthermore, the refiner wishes to hedge its entire slate of products rather than those where a traded market exists. It is possible to execute an OTC swap on the margin between the weighted basket of products in Table 6.12 and Dated Brent. Liquid swap markets exist for each of the production constituents, which means that the price of this ‘margin swap’ can be derived as follows: Refinery Margin = (0.03 ∗ Naphtha + 0.41 ∗ Gasoline + 0.35 ∗ gas oil + 0.21 ∗ Fuel oil) − Dated Brent TABLE 6.12 Hypothetical refiner’s production profile. Product

% of total output

Naphtha Gasoline Gas oil Fuel oil

3 41 35 21

Pricing quote S&P Platts Cargoes CIF North West Europe Argus 10 ppm 95 Ron Barges FOB Rotterdam S&P Platts 0.1% Sulfur Barges FOB Rotterdam S&P Platts 1% Sulfur Barges FOB Rotterdam

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The fixed price on the swap is in essence a weighted average of the component swap prices, less the price of a Dated Brent swap. The weights applied to the refined products represent the refiner’s relative production percentages. In the European markets, refined product prices are quoted in USD per metric tonne whilst crude oil is quoted in USD per barrel. Refinery margins are quoted in USD per barrel, which means that the refined product swap prices must be expressed on the same basis. In the derivatives markets it is standard practice to use the conversion factors detailed in table 6.13. The refiner fears that margins will fall by the time fourth quarter arrives and so enters a margin swap based on a notional of 160,000 barrels per month for the quarter in question. We will assume that the fixed rate has been set at USD 7.24. The refiner sells the swap receiving a fixed price of USD 7.24, while paying a floating rate. Five good business days after each month in the fourth quarter, the refiner pays or receives a cash amount depending on the difference between the fixed price of the swap and the average monthly refining margin implied by the various published prices. Accordingly, whatever it gains or loses in the physical market is offset under the swap. The result is a hedged position and secured revenues. Table 6.14 shows how this is achieved and that the net margin achieved is equal to the fixed rate on the swap. Hedging the crack spread using options Basket options were introduced in the chapter on base metals. As a brief recap, a basket option is a single option that references the value of several underlying assets. One of the features of the basket option is that they offer a premium saving relative to buying individual options on each of the underlying assets. This is since the valuation of these products is a function of the correlation between assets. The refinery is exposed to a fall in their margins and so two simple option strategies would be to either buy a put or sell a call on this spread. If they were to buy a put option, then they would receive a payment if the spread declined but would have to pay a premium. The sale of a call on the spread would mean that if the spread declined, the option would not be exercised and the refinery would retain the premium, which could TABLE 6.13 Energy conversion factors. Product

USD per bbl. to USD per metric tonne

Naphtha Gasoline Jet Gas oil Fuel oil

8.90 8.33 7.88 7.45 6.35

Note: To convert a quantity expressed in USD per barrel to USD per metric tonne one would multiply by the appropriate conversion factor.

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TABLE 6.14 Refinery margin hedge using OTC swaps. Date

Physical

Swap

15 Sep

Agrees to sell 160,000 barrels per month in Q4 at average of daily, published assessments. Delivery/settlement on fifth business day after month end. Average margin according to October published prices = USD 6.82/bbl. Cash received = (160,000*6.82) = USD 1,091,200 Average margin according to November published prices = USD 6.03/bbl. Cash received = (160,000*6.03) = USD 964,800 Average margin according to December published prices = 8.11 USD/bbl. Cash received = (160,000*8.11) = USD 1,297,600

Sells (i.e. receives fixed) 160,000 bbl. per month Q4 refinery margin Swap = USD USD 7.24/bbl. Swap settlement: = 160,000*(7.24 − 6.82) = USD 67,200

5 Nov

5 Dec

5 Jan

Swap settlement: = 160,000*(7.24 − 6.03) = USD 193,600 Swap settlement: = 160,000*(7.24 − 8.11) = USD −139,200

Effective sale price = (1,091,200 + 964,800 + 1,297,600 + 67,200 + 193,600 − 139,200) / 480,000 barrels = USD 7.24/bbl.

be used to offset any decline in revenues. If the spread were to increase, then they would be required to make a payment on the option although their underlying margins would improve. A refining margin option is a spread option between a basket of energy products and crude oil. Instead of trading a series of spread options between each individual refined product and crude oil, the refiner can trade a single refining margin option, which would include all its oil products. Given the fact that every refinery will have a different configuration then these products will usually be bespoke. This section focuses on the use of calendar spread options for managing storage capacity. Owning storage gives the owner the choice between selling the commodity now or in the future. Owning storage capacity can be thought of as a form of ‘real’ optionality. Suppose the market is in contango with forward prices rising with respect to maturity. There may be an incentive to store the asset now and sell it later at a higher price. This would be profitable if the costs associated with storing the asset are less than the difference between the spot and forward prices. If the market is in backwardation then short-term prices are higher than long-term prices, and the owner should logically sell the asset immediately as there is no benefit to leaving it in storage. This difference between two maturities on a forward price curve is known as the calendar spread. The maturities could be spreads for either adjacent or non-adjacent months. It follows that a calendar spread option is an option on the price differential

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between two delivery dates of the same commodity. So, for example, a spread option could be referenced to the price difference between the June and December ICE Brent futures contract. By convention, the calendar spread is defined as: Near-dated futures price minus the long-dated futures price Sometimes reference may be made to buying or selling the spread. In this instance, buying the spread means buying the near-dated contract and selling the long-dated contract. The opposite is true when describing the sale of the spread. One implication of defining the spread in such a manner is that in a contango market, the spread is negative, while in a backwardated market the spread is positive. Representing this diagrammatically shows that the availability of storage can be thought of as a put option on the calendar spread. Increasing contango

10

Increasing backwardation

Storage benefit

8 6 4 2 0

-10

-8

-6

-4

-2

0

2

4

6

8

10

FIGURE 6.21 Payoff from a calendar spread option.

So, calendar spread options can be used to protect clients against adverse changes in the forward curve. Monetising storage capacity The forward curve for gas oil typically displays an element of seasonality. That is, they display a succession of contango and backwardation periods, with the fuel being more expensive in winter and cheaper in the summer. Suppose it is currently August and a company has 100,000 cubic meters of excess capacity for the period between January and June in the following year. The current futures price for January is USD 903.00/MT, while the June futures price is USD 889.00 indicating that the market is in backwardation. The company decides to sell a put option on the spread between these futures prices. A put option on the spread would allow the holder to sell or deliver the underlying which in this case is the spread between two futures prices. From an operational perspective it is often easier to cash-settle such contracts. Calendar spread options can

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TABLE 6.15 Monetising storage capacity using options.

January price June price Spread (Jan – Jun) Option strike Option payout Gas oil purchased? Profit and loss on purchase and sale of gas oil Storage cost incurred Option premium Total return

Scenario #1

Scenario #2

Scenario #3

Scenario #4

USD 860.00 USD 890.00 − USD 30.00 − USD 10.00 − USD 20.00 Yes USD 30.00

USD 860.00 USD 868.00 − USD 8.00 − USD 10.00 USD 0.00 Yes USD 8.00

USD 860.00 USD 866.00 − USD 6.00 − USD 10.00 USD 0.00 No USD 0.00

USD 860.00 USD 850.00 USD 10.00 − USD 10.00 USD 0.00 No USD 0.00

− USD 7.00 USD 0.50 USD 3.50

− USD 7.00 USD 0.50 USD 1.50

USD 0.00 USD 0.50 USD 0.50

USD 0.00 USD 0.50 USD 0.50

be structured to be European or Asian in style and generally the option is set to expire prior to the maturity of the first futures contract9 . The ‘ATM spread’ would be USD 14.00 (USD 903.00 − USD 889.00). The company decides to set a strike of −USD 10.00, which means that they will only have to pay out on the option if the spread declines beyond −USD 10.00, i.e. if the market moves into contango. Table 6.15 shows the profit or loss to the company at maturity under a variety of different scenarios. The following points are relevant to the table. ▪ The expiry payoff on the option is MAX (Strike − (January price − June price), 0) ▪ If the client takes delivery of the gas oil for the six-month period it is assumed that the total cost of storage is USD 7.00/MT. ▪ It is also possible that the client may still decide to buy the gas oil for January and sell the gas oil for June even if the option is not exercised against them. They would do this if the difference between the buy and sell price is less than the cost of storage. ▪ For ease of illustration the example has ignored any transportation and financing costs. ▪ The total return to the client is: Payout on the option + storage cost + profit and loss from the purchase and sale of gas oil + the option premium. The fact that the strike is negative makes the payoff on this type of option somewhat counterintuitive. 9

At the time of writing, the ICE gas oil contract matures two days before the 14th calendar day of the delivery month, with physical settlement taking place between the 16th and the last calendar day of the delivery month.

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▪ Scenario #1 – here the market moves into contango, which pushes the spread of the two futures prices beyond the strike; recall that a put option will pay off as the underlying decreases. Since the storage owner is short the option, they will be required to pay out USD 20.00 to cash-settle the obligation. However, since the market is in contango then as an unrelated separate transaction the storage owner could now ‘buy the futures spread’ by buying the January contract and selling the June contract. If they were to hold both futures to maturity they would take delivery of the gas oil in January for USD 860.00, pay USD 7.00 for the cost of storing it until June, when they could deliver it to fulfill their short June futures position resulting in an income of USD 890.00. There overall return would be: Payout on the option + profit or loss on the futures position − cost of storage + option premium − USD 20.00 + USD 30.00 − USD 7.00 + USD 0.52 = USD 3.50 ▪ Scenario #2 – again the market is in contango by USD 8.00. The option expires out of the money but since the size of the contango is greater than their storage cost there is still sufficient reason to buy the futures spread as per the first scenario. Using the same equation as in scenario #1, their overall return would be USD 1.50. ▪ Scenario #3 – the market is in contango, but the option expires out of the money. However, the amount of contango does not cover the cost of storage and so the physical commodity is not bought and sold. However, since the option is not exercised the storage owner retains the premium. ▪ Scenario #4 – this is where the market remains in backwardation, the option is not exercised, there is no incentive to buy and store the physical commodity, and so similar to the third scenario, the owner earns just the option premium. In the third and fourth scenarios where the storage has not been used, the owner has been able to generate some income from the sale of the option, which has not been exercised.

6.9.3

Refined product hedges

Consumers of crude oil are largely refineries as most end users are more interested in the final refined product. As a recap, Table 6.16 shows the main refined products, their uses and applicable industry sectors: Consider an example of an airline company based in Europe offering flights to a variety of different global locations. At the start of the year the airline asks several of the companies to tender for the delivery of jet fuel to different airports from which they operate (e.g. London Heathrow). The airline has an ongoing need for jet fuel and so is seeking a fixed number of barrels per month to be delivered. The tender price will be based on a floating formula and will settle against prices published by S&P Platts. A normal method of pricing the jet fuel will be based on an ‘average of month’ basis. This means that at the end of each month, the price paid will be an arithmetic average of the jet fuel price quoted daily in S&P Platts. However, there are several different quoted jet

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TABLE 6.16 Refined products and their main applications. Refined product

Major uses

Industry sectors

Jet fuel Road diesel or heating oil Naphtha Gasoline/petrol Heavy fuel oil

Air travel, military Road haulage, farming, space heating Petrochemical feedstock Road transport Seaborne transport, power generation, asphalt

Logistics Airlines Couriers Utilities Railways Shipping Chemicals Heavy industry

fuel prices depending on the delivery location. These may include the US Gulf Coast, North West Europe (NWE), the Mediterranean, and Singapore. The tender will require the selling company to include the cost of delivery to the airport. The additional cost of transportation to the airport will be expressed as a premium to the conventional delivery location. So, the quote may come back from the seller as ‘Average of month based on a reference price of S&P Platts CIF NWE plus a premium of USD X per barrel to cover transport costs’. Using swaps to transform a floating exposure into fixed If during the year the airline is concerned about a rise in the price of jet fuel, it could enter a commodity swap to cover part of the exposure. In April, the company executes the following cash settled jet fuel swap with an investment bank. Commodity: Payer of fixed: Payer of floating index: Period of swap: Fixed price. Notional amount. Settlement. Price source. Floating reference price. Reference price calculation.

Jet Cargoes CIF NWE9 (Cost, Insurance Freight, North West Europe) Airline Investment bank Three months commencing 1 October USD 650.00/tonne 10,000 tonnes per month Monthly S&P Platts European Spot price for Jet Cargoes CIF NWE, published daily Arithmetic average of the floating reference price over each month

At the end of each month the average of all of the daily spot prices is calculated and compared to the fixed price. 10

Another popular index is Jet Barges FOB Rotterdam.

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▪ If the average price is greater than the agreed fixed price of USD 650.00/tonne, the airline will receive a cash payment based on this amount multiplied by the agreed number of tonnes. ▪ If the average price is the same as the fixed price, then no settlement takes place. ▪ If the price of jet fuel is on average lower than the fixed rate then the airline will make a payment for the difference to the bank based on the differential. Settlement under the swap is normally five good business days after the last day of the traded month. The payment or receipt under the swap combined with the purchase of the physical commodity will result in a fixed price of USD 650.00/tonne. It is important to note that in this example, the terms of the swap’s floating reference price, matched exactly the terms of the airline’s physical purchases. Hedging jet fuel exposure using gas oil futures Owing to chemical similarities it is market practice to price physical jet fuel contract as a differential to gas oil. Jet fuel normally trades at a premium to gas oil as it must meet higher quality specifications. However, this relationship can break down in certain cases where supply and demand fundamentals are such that gas oil is more sought after than jet fuel. The pricing relationship between the products can be expressed as: jet fuel = gas oil + jet differential If gas oil is trading at USD 72.00/bbl., it can be converted to a tonnage equivalent by using an industry convention value of USD 7.45, which returns a figure of USD 536.40. If the quoted price of jet fuel is say USD 586.40 per tonne, the ‘jet diff’ is USD 50.00. Gas oil normally trades at a premium to crude oil and this differential is sometimes referred to as the ‘Gas Oil’ crack. It is possible to hedge a jet fuel exposure using gas oil futures due to the existence of a liquid futures market. Traditionally, there have been very high correlations (i.e. > 90%) between: ▪ Brent crude oil and gas oil ▪ Brent crude oil and jet fuel ▪ Gas oil and jet fuel In the gas oil-jet relationship, gas oil has traditionally been the main price driver and although the relationship can be very volatile, if one were to hedge in gas oil, it is likely that you would capture most of any jet price movement. A possible way of pricing a physical delivery of jet fuel could be: Physical jet fuel = Prompt gas oil futures price at delivery + fixed Jet diff + transport costs to delivery location

Crude Oil

233

There could be several ways in which an airline could hedge this exposure: ▪ Transfer the risk to their suppliers by agreeing a fixed price supply contract. ▪ Transfer the risk to customers by including some provision such as a ‘fuel levy’ clause that would require a supplemental payment in the event of an increase in prices. ▪ Since the physical purchase references a futures price, the airline can buy the requisite number of gas oil futures and with the other two elements of the physical contract fixed, they will be able to lock in a known future cost. Another strategy sometimes used by airlines involves a combination of different derivatives depending on the time horizon. ▪ Long-dated crude oil trades of a three- to four-year maturity to manage the overall macro picture. ▪ As these contracts shorten in maturity, they may then roll into gas oil futures with maturities of about two years. ▪ With one year to go they may seek out jet fuel solutions (e.g. swaps) and then with six months remaining look to hedge deliveries to specific locations. Hedging jet fuel exposures using crude oil futures In the previous section, it was argued that airlines might decide to hedge their jet fuel exposures using crude oil futures if there is no liquid instrument that directly matches their exposure. Banks that offer risk management solutions to clients may be faced with a similar problem. For example, suppose that a bank enters a fixed-floating jet fuel swap with an airline, where they receive fixed and pay floating. Since the bank is now faced with an exposure to rising jet fuel prices, they need to hedge this exposure, which could be done using crude oil futures. An example of this type of swap was illustrated in Chapter 3 (see Figure 3.1) in relation to the collapse of Japan Airlines. Regression analysis could be used to determine the appropriate size of the hedge. Regression analysis describes the relationship between a dependent and independent variable. In this example, the dependent variable would be jet fuel and the independent variable would be crude oil futures. The form of the regression equation would be: Change in the price of jet fuel = Alpha + Beta Change in crude oil futures price + e Where: Alpha = a constant; the value of Y even if X has zero value. Beta = the regression coefficient. This is the slope of the line of best fit. e = error term. This reflects the fact that other factors may influence the value of the dependent variable and are not captured by the specification of the equation.

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Very often in financial price regressions the value of alpha can be small and is often ignored. It is the value of beta that is used to calculate the appropriate hedge ratio. To calculate the equation a few assumptions need to be made: ▪ ▪ ▪ ▪ ▪ ▪

Which index value of jet fuel should be used? How far back should the data sample extend? What is the frequency of the sample? (Daily, weekly, monthly) At what time of day are the futures prices sampled? Which maturity of futures should be used? What conversion factor do we need to convert jet fuel (traded in metric tonnes) to crude oil (traded in barrels)?

With respect to the final point a common factor used in the energy markets is that one metric tonne is equivalent to 7.45 barrels. If jet fuel is trading at USD 650.00/MT, then this is equivalent to USD 87.24/bbl. Suppose that the results of the regression analysis suggest a beta value of 0.8. This would tell us that a one-unit change in the price of a crude oil future is associated with a 0.8-unit price change in jet fuel. The bank decides to hedge 1,000 metric tonnes (MT) of jet fuel using crude oil futures with a contract size of 1,000 barrels. The correct hedge ratio would be: = Beta ∗ (jet fuel amount to be hedged∕contract size of crude oil futures) = 0.8 ∗ (7, 450 barrels of jet fuel∕1, 000 barrels of crude) = 6 crude oil futures (rounded to the nearest contract) If crude oil futures were to increase by USD 1.00 then the futures hedge would change in value by USD 6,000. Based on the regression analysis, this dollar change in the value of crude would be associated with a USD 0.80 change in the price of jet fuel resulting in a change in value of USD 5,960. The hedge is not 100% perfect because an element of rounding was used to determine the correct number of futures. Although the calculation may appear to be somewhat straightforward, the trader is then faced with some tricky issues. If hedging a multi-period swap, which maturity of futures do they pick? They could trade a strip of futures (i.e. a series of consecutive futures contracts) or a stack of futures (hedge the entire maturity of the swap by using one single futures maturity). A strip of futures may closely match the underlying exposure but may not be liquid. The second approach offers the greater liquidity but does not match the maturity of the swap. Another problem is that the beta value will likely evolve over time and so any hedge will need to be rebalanced to reflect any change. Hedging jet fuel exposures using gas oil futures and a basis swap There is an active OTC market for basis swaps that allow an end user to transform exposure in one product to that of another, i.e. an underlying exposure to gas oil can be transformed into a jet fuel exposure. These swaps are quoted on a bid-offer basis and are quoted as a fixed against floating differential, in the same manner as a Brent CFD. The fixed price is calculated as the difference between gas oil and jet fuel.

235

Crude Oil

In this example, we will assume that the airline buys their jet fuel requirements in the spot market on a variable price basis (e.g. an average of quoted S&P Platts prices plus a premium for delivery to a particular location). To hedge the exposure, they decide to use a combination of gas oil futures and a basis swap. They buy the gas oil future with the same maturity as the underlying exposure at the equivalent of USD 536.40/tonne. At the same time, they enter a jet diff swap at a quoted level of +USD 45.00. The swap is bought in the sense that the agreement is requiring them to pay a USD 45.00 fixed amount per tonne at expiry in return for receiving the average difference between the actual gas oil price and jet fuel price over the agreed period of the swap. The combination of the two deals (buy the gas oil future, buy the jet diff swap) hedges the two components to which they were exposed under the terms of the physical. Under this pricing agreement the buyer is exposed to a change in the price of gas oil and the jet differential since jet fuel is priced from gas oil. The net effect of the transaction is that the airline locks in the price of their jet fuel purchase at USD 581.40. Assume that at maturity the following market conditions exist. The gas oil future is trading at USD 550.00/tonne and the jet differential has narrowed to USD 40.00. From the relationship presented earlier that links gas oil and jet fuel, we can infer that jet fuel is now trading at USD 590.00/tonne. The airline will make a USD 13.60 profit on the close out of the future but will have to make a net payment of USD 5.00 under the swap. The airline buys jet fuel at USD 590.00/tonne to which they add the USD 5.00 loss on the swap but subtract the USD 13.60 profit under the future. The net cost is USD 581.40, equal to the locked in value established at the point of executing the gas oil future and buying the swap. Hedging jet fuel using options Suppose an airline consumes 1,000 MT of jet fuel each month but which varies by 100 MT over or under this amount. The base amount of their demand could be hedged using a series of call options (a ‘strip’ of options), which could be structured in a variety of ways highlighted previously in the text (e.g. Asian-style, premium reduction techniques). The variable demand could be hedged using a compound option. A compound option is an option on an option so in this instance the airline could buy a call on a call. They would pay a premium to acquire a call option, which if exercised would allow them to buy a second call option. On the exercise of the second option, the airline would be obliged to pay a second premium. The terms of a plain vanilla European call option would be: Underlying price: Strike: Time to maturity: Implied volatility: Premium:

USD 600.00 USD 600.00 One month 30% USD 21.00 (rounded)

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A compound option would allow the airline to buy the above option based on these terms. So, the call on a call would have the strike rate equal to the premium on the second, plain vanilla call. The terms of the compound option would be: Underlying price: Strike on underlying option: Strike on compound option: Compound option maturity: Vanilla option maturity: Implied volatility: Premium:

USD 600.00 USD 600.00 USD 21.00 One month One month 30% USD 10.00 (rounded)

In this example, the compound option has a one-month maturity which if exercised grants the holder a one-month call option. For the purposes of this example, both dates were chosen somewhat arbitrarily and can be negotiated between the counterparties. When the compound option matures, the airline would need to make a judgment as to their likely consumption in one month’s time. If they anticipate consuming the extra jet fuel, they may decide to exercise the compound option and enter the vanilla call option. This would only be worthwhile if the additional premium now represents a saving over the current vanilla equivalent. So, if implied volatility had increased over the month (all other things unchanged) a one-month plain vanilla call option would now cost more, say, USD 24.00. In this scenario the compound option would be exercised, as it is ITM. However, note that the total premium incurred by using the compound option (USD 31.00) is greater than the now more expensive call option (USD 24.00), which in hindsight would make this approach a relatively expensive one.

CHAPTER

7

Natural Gas

7.1

FORMATION OF NATURAL GAS

Natural gas is a fossil fuel, the main constituent of which is methane (CH4 ). Oil and natural gas, which are frequently found together in the same deposits, are formed from the decay of vegetation and animals. Over time, geological processes turned these remains into reservoirs of hydrocarbons trapped by overlying impermeable rock strata. Natural gas that is discovered with crude oil is often referred to as ‘associated gas’ but is classified as ‘non-associated gas’ when found separately. Although the actual composition of natural gas varies between reservoirs, a distinction can be made between ‘wet’ and ‘dry’ gas. Wet gas has a high proportion of other gaseous substances such as pentane, ethane, propane, and butane referred to collectively as natural gas liquids or NGLs. Dry gas is natural gas without these associated substances. After natural gas has been extracted from the ground the NGLs are removed and can be sold separately. For example, ethane is a key input in the production of plastics. The processing of natural gas also removes any water and hydrogen sulfide and adds a smell for safety purposes, as methane in its naturally occurring form is odourless. A major development in the industry is the significant technological advancements made with respect to the recovery of natural gas trapped in shale rock formations. These formations will sometimes have fractures that contain natural gas, but since the surrounding rocks are not particularly permeable, the extraction process was not commercially viable for many years. This type of gas is sometimes referred to as an ‘unconventional’ source. Shale gas extraction is not a new concept and the author recalls a discussion with an experienced energy professional who witnessed shale operations in the US in the late 1970s/early 1980s. Two relatively recent developments that have increased the viability of such projects are: ▪ Horizontal drilling – this allows the pipeline to the wellhead to bend, which not only allows access to difficult-to-reach areas, but also increases the surface area that can be drilled. ▪ Hydraulic fracturing (‘fracking’) – this involves pumping liquids into the shale rock formation to create wider fractures in the rock. The liquids may contain a more permeable solid such as sand, which would then allow the trapped gas to flow to the wellhead.

237

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MEASURING NATURAL GAS

The most common measure of the volume of natural gas is a cubic metre, which is normally expressed as m3 or cm. In the USA, the convention is to use imperial measures such as cubic feet (ft3 ). These measures are quite small and so are often multiplied by sizing factors such as a thousand (m), million (mm; 106 ), billion (b; 109 ) and a trillion (t; 1012 ). These measurements are taken assuming normal temperatures and pressures. The energy content of natural gas is measured in a variety of ways. The calorific value of natural gas measures the amount of energy produced when a fuel is burnt. One calorie measures the amount of energy required to raise one gram of water by one degree Celsius. A joule is an alternative measure, and one calorie equals four joules. A kilowatt is equal to 3,600,000 joules and is often expressed as a rate. For example, a kilowatt-hour (kWh) is equal to one kilowatt of power expended for one hour. Larger businesses and institutions sometimes use the megawatt hour (MWh), where 1 MWh = 1,000 kWh. The energy outputs of power plants over long periods of time or the energy consumption of states or nations can be expressed in gigawatt hours (GWh; equal to 1,000 MWh). In the USA, the most common measure of energy content is the British Thermal Unit (BTU). It is defined as the amount of heat that is required to raise the temperature of one pound of water by one degree Fahrenheit. Another common measure in the UK market is the therm, which is equivalent to 100,000 BTU or about 97 cubic feet. In the European natural gas markets a variety of different measures can be used. These include therms, megawatt hours, or gigajoules. One MWh is equal to 34.12 therms and 1 million BTUs equal about 10 therms.

7.3

THE PHYSICAL SUPPLY CHAIN

One of the effects of natural gas deregulation has been to increase the degree of competition along the physical supply chain. The traditional monopolistic supply chain has been restructured so that different functions can now be performed by different entities. While some companies may be vertically integrated performing a number of functions along the supply chain, others may just operate ‘upstream’ in exploration and production or ‘downstream’ in the trading and supplying of gas.

7.3.1

Production

The first part of the physical supply chain is the exploration and production of natural gas from either an offshore or onshore location. If the natural gas is produced offshore it has to be gathered from various rigs and piped ashore. The point at which the natural gas reaches the shore is sometimes referred to as the beach terminal. A significant number of producers will be oil majors, but there may also be several smaller independent companies in operation. In some locations there will also be onshore production facilities, but the process will essentially be the same. Before onward transportation this ‘wet’ natural gas will have to be processed to separate the natural gas element (i.e. methane) from the other naturally occurring natural gas liquids. The resultant ‘dry’ gas is then delivered into the pipeline system.

Natural Gas

7.3.2

239

Shippers

The advent of deregulation and subsequent re-regulation has allowed third party access (sometimes called ‘open access’ in the USA) to the National Transmission System (NTS) and also saw the emergence of a new role within the supply chain; that of the shipper (sometimes referred to as marketers). Shippers are licensed wholesalers who buy natural gas from the producers at the shore terminals for onward delivery along the main pipeline to end consumers. The ownership of designated shippers is diverse. They may be affiliated to natural gas producers, electricity companies, banks, or commodity traders. The shipper/marketer will perform a variety of different roles: ▪ ▪ ▪ ▪

Buy natural gas from producers and then find sellers. Sell natural gas to customers and then source the supply. Arrange transportation of natural gas along the network pipeline. Inform the owner of the NTS (e.g. National Grid Gas in the UK) where the natural gas will enter the pipeline and where it will exit. This is done using a nomination system. A shipper can nominate gas to be delivered into the system, out of the system, or to simply change the title of gas held within the system. ▪ For natural gas to be shipped along the main high-pressure NTS, the shipper has to acquire sufficient entry capacity to permit the flow and then nominate the amount they wish to deliver. Equally to remove natural gas, exit capacity needs to be booked. Entry and exit capacity can be booked directly with the system operator, via an auction or by secondary market trading. ▪ Natural gas can enter the NTS from offshore or onshore production facilities or storage. It exits the NTS into local distribution networks, storage facilities, or is delivered to large industrial users. As part of their responsibilities the shippers must ensure that their daily operations balance. That happens when the amount of natural gas injected into the system equals the amount withdrawn. Shippers who fail to balance their demand and supply incur financial penalties.

7.3.3

Transmission

Once onshore, natural gas is principally moved along a high-pressure pipeline to either a natural gas retail supplier or directly to a wholesale consumer. By transporting it under pressure a greater volume of natural gas can be moved. In order to keep the natural gas moving along the pipelines there will be a number of compressor stations that ensure that the natural gas remains pressurised. A natural gas retail supplier will arrange for the natural gas to be delivered to the end user along lower pressure pipes that join the high-pressure pipeline. These pipelines are usually made from carbon steel and can vary in size from 2–60 inches in diameter. One of the consequences of re-regulation was the realisation that new entrants to the market would not be willing to build competing large-scale national transportation infrastructure. For example, in the USA the EIA estimate there are about three million miles of natural gas pipelines. Most natural gas users receive their supplies from an entity that is often referred to generically as a local distribution company (LDC).

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Depending on the degree of deregulation in the market, the LDC may operate in a specific geographical area or may be free to offer services throughout a specific marketplace. In the USA, the delivery points to LDCs are sometimes referred to as ‘citygates’ and are often used as pricing points for buyers and sellers. In the UK, National Grid Gas is the company that manages 4,200 miles of the main high-pressure pipeline; sometimes referred to as the National Transmission System (NTS). It is a private company (also sometimes referred to generically as the Transmission System Operator or TSO), but operates under a licence granted by the UK regulator. Its role is to deliver natural gas and it can only buy or sell natural gas for purposes of managing the integrity of the pipeline. It is obliged to follow the terms of the ‘Network Code’, which is a framework that dictates how it will operate and the nature of the relationship it has with the users of the network such as shippers. The Network Code enshrines a principle that is common to re-regulated markets which is ‘third party access’. Third party access allows certain companies (shippers) to have access to the pipeline network in order to facilitate the movement of natural gas on behalf of producers or consumers. There are also a number of independent natural gas transporters who have built extensions to the NTS to supply certain customers not served by the main network. Natural gas leaves the NTS on a continual basis either directly to large industrial users (such as power stations), storage facilities, or into one of a number of Gas Distribution Networks into which the UK is grouped. Once within the regional network, the natural gas can be routed towards the final consumer. One of the key responsibilities of the transmission system operator is to ensure that the system is balanced. This is done as a three-stage process. Firstly, there is the nomination process, where the shippers are required to inform the TSO as to how much natural gas will be delivered, over what period and the entry and exit points. The TSO will then confirm the nomination after they are sure that sufficient capacity exists within the network. The final stage in the process is the scheduling by the TSO of all the confirmed nominations based on defined priorities. Although the act of balancing the network will be performed by the TSO, the shippers will be incentivised through monetary penalties to ensure that the amount of natural gas entering the system matches the amount of natural gas exiting. The transmission system operator has a number of options available to them in order to ensure that the volume of natural gas within the pipeline is kept within acceptable limits. For example, they could utilise production contracts to supply natural gas that include a clause that allows for the contracted amount to be increased above the stated amount. This additional amount is referred to as the ‘swing’. The existence of adequate storage facilities is also important so that natural gas could be withdrawn at short notice. A third tool that could be used is interruptible supply contracts with large industrial consumers. Here the customer is willing to accept that his supply of natural gas may be curtailed in periods where demand is high. In exchange, the consumer will receive some form of financial compensation.

7.3.4

Interconnectors

Gas interconnectors connect gas transmission systems from other countries (e.g. Belgium, Netherlands) to the National Transmission System (NTS) in England, Scotland,

Natural Gas

241

and Wales. As production in the North Sea declines, the importance of the interconnectors will increase, as the UK will be forced to import more natural gas.

7.3.5

Storage

Storage plays an important role on the supply side of the market by allowing participants to meet peak demand and may also help ‘smooth’ out demand either during certain times of the year (e.g. winter) or perhaps during the day (e.g. meeting residential demand). Excess natural gas can be stored in large underground caverns, above ground facilities or within the pipes on the transportation network (a process referred to as ‘line packing’). By raising and lowering the pressure on any pipeline segment, a pipeline company can use the segment to store gas during periods when there is less demand at the end of the pipeline. Using line packing in this way allows pipeline operators to handle short-term fluctuations in demand. There are different types of storage facilities. A depleted gas field is a very common and cost-effective way of storing gas, as it will already have a significant amount of existing infrastructure. Underground cavities are created by drilling down into salt layers, adding seawater to dissolve the salt and then pumping in natural gas to force out the water. Depleted oil or natural gas reservoirs are also used for this purpose. Natural gas can also be stored in a liquefied form (LNG), which reduces the amount of space occupied. Storage is sometimes classified as either base or peak load in nature. Base load storage is more strategic in nature and although the facilities may be large in size, the rate at which the gas can be extracted is low. Natural gas reservoirs that have been depleted are a popular choice for this sort of facility. Peak load facilities are more tactical in nature and are designed to allow smaller amounts of gas at a faster rate. Salt caverns are commonly used for peak storage needs. In a re-regulated market, storage facilities are run on a commercial basis with capacity being sold off to third parties. The availability of storage capacity relative to demand will have an important impact on the price of natural gas. If capacity is scarce relative to demand, a cold spell of weather could cause natural gas prices to rise steeply. In general terms, excess natural gas is injected into storage during warmer periods and withdrawn in colder times.

7.3.6

Supply

Under monopoly-style structure the final consumer would have virtually no choice as to who provided their natural gas supply. In the natural gas markets that have been re-regulated, a consumer should be free to choose who provides their natural gas supplies. This freedom of choice also extends to the suppliers who can choose the source of their natural gas and arrange with a shipper to ensure it is delivered.

7.3.7

Customers

Distinction is usually made between two different types of customer. Retail consumers would typically include households, shops, and offices whereas very large industrial

242

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

customers would cover power stations that may buy directly from either shippers or producers. In some cases, the large industrial users may have separate arrangements to receive their supplies by a specific ‘offtake’ from the national pipeline system. However, within the industrial capacity there will be larger customers who have an arrangement whereby their supply can be interrupted or where the agreement to supply gas is ‘firm’.

7.3.8

Non-physical participants (NPPs)

The re-regulation of physical markets and growth of financial risk management products has seen the emergence of participants who do not have a need for the physical commodity. Typically, this would include commodity trading houses, hedge funds, and some banks. There are a variety of roles that NPPs can fulfill: ▪ Traditional lending banks that have lent to upstream producers take on an element of commodity risk. If they cannot offset that risk, they may seek out an institution with natural gas trading capability to manage the associated price risk. ▪ Most of the oil producers (e.g. BP, Shell) will have very sophisticated natural gas trading and risk management operations and will act as trading counterparties to other NPPs. ▪ Utilities will have large demand and uncertain consumption forecasts and so will have significant volume and price risk. As a result, they require structured natural gas risk management contracts that provide them with flexibility. ▪ Major industrial natural gas consumers are chemical companies, building products, glass, steel manufacturers, and fertiliser manufacturers. Where an entity has a multisite operation, it may also be possible to aggregate smaller loads and manage the natural gas price risk centrally. ▪ Commodity traders and hedge funds will use the natural gas market to implement view driven strategies using the suite of physical and derivative products.

7.4

DEREGULATION AND RE-REGULATION

The emergence of natural gas as a tradable commodity has come about because of deregulation in some countries. This, however, does not mean that the various markets are now unregulated, rather a new set of regulations have subsequently emerged. Prior to deregulation, gas markets were characterised as monopolies where one entity would purchase virtually all of the domestic production, transport it to its end destination, and then sell it to a final consumer. Agreements to buy and sell were primarily based on long-term, fixed-price contracts, often linked to the price of oil. In the US, prior to deregulation, natural gas producers would sell to pipeline companies who then transported and sold the commodity either to large industrial users or to local distribution companies for onward sale to the general public. The prices charged by producers to the transportation companies and the amounts paid by the local distribution companies were regulated at the federal level. The retail consumer was protected against monopolistic practices by state regulation.

Natural Gas

7.4.1

243

The US experience

The first country to introduce competition into their domestic natural gas market was the USA. In the very early days of the industry it was regulated at a local level, but as intrastate pipelines started to develop there was no effective method of overseeing the industry. The origins of formal federal regulation were set out in the Natural Gas Act of 19381 , which recognised that while the movement of natural gas along major interstate pipelines was a natural monopoly, it required an element of regulation. The act concerned itself with the setting of rates for the transportation of natural gas along interstate pipelines, but did not specify any particular regulation of producer prices. Wellhead price regulation came about in 1954 as a result of a legal case (Phillips Petroleum Co. vs. Wisconsin). As a result of this lawsuit the Federal Power Commission (who regulated interstate natural gas sales at the time) imposed price ceilings on the amount that producers could charge, which remained in place until 1978. There were three effects of the Phillips decision: ▪ Since the sale price for which natural gas could be sold was regulated, there was little incentive for the producer to devote extra capital to expand exploration. ▪ The price of intrastate gas was not subject to the same regulation and so created a bias, which encouraged producing states to sell the commodity locally rather than nationally. This created natural gas shortages in the mid-1970s in some states. ▪ As a result of the Middle East Oil embargos in the 1970s, natural gas became a more attractive energy substitute. Combined with the relatively low price ceilings imposed by the regulator, the demand for natural gas increased substantially. The next significant act was the Natural Gas Policy Act of 1978, which aimed to create a single market that did not favour intrastate over interstate sales and would allow market forces to determine the price of natural gas. The act also saw the Federal Power Commission replaced by FERC (Federal Energy Regulatory Commission). FERC is responsible for the regulation of interstate natural gas pipelines and storage facilities. It is also responsible for approving natural gas and liquefied natural gas (LNG) import and export facilities. The complete unbundling of natural gas services continued via a series of orders issued by FERC and federal legislators. In 1985, FERC Order 436 (sometimes referred to as the ‘open access order’) required that natural gas pipelines provide open access to transportation services, albeit on a voluntary basis. However, it was the Natural Gas Wellhead Decontrol Act of 1989, which effectively led to the restructuring of the natural gas industry and encouraged market determined gas prices. This meant the large-scale consumers of natural gas were able to negotiate prices directly with producers and then contract separately for its transportation. FERC order 636 issued in 1992 made the voluntary unbundling of services outlined in order 436 compulsory. This order stated that the pipeline companies had to separate their transportation and sales functions to give the customer greater choice as to the sale, transportation, and storage of natural gas.

1

Subsequently amended by the 2005 Energy Policy Act.

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The overall impact for the USA was that producer prices were no longer subject to regulation and were driven by the fundamentals of supply and demand. Producers and consumers could contract directly with the pipeline companies no longer taking possession of the natural gas. They would now only offer transportation as a service to another company. It also gave rise to a range of new services such as shipping and trading.

7.4.2

The UK experience

In the UK, the natural gas market was subject to major deregulation and re-regulation from the mid-1980s (e.g. the Gas Acts of 1986 and 1995). Prior to this time the market had been dominated by a single monopoly – British Gas. The company was initially privatised and by the late 1990s had demerged with a series of separate companies performing different roles (e.g. BG focusing on extraction, National Grid Gas maintaining the transportation network, and Centrica supplying natural gas to retail customers under the British Gas brand). The Department for Business, Energy, and Industrial Strategy (BEIS) is responsible for setting energy and climate change policy and establishes the framework for achieving different policy goals. The industry’s upstream activities (e.g. exploration and production) are regulated by the Oil and Gas Authority (OGA), while the downstream activities (e.g. consumer supply) are currently regulated by OFGEM (Office of Gas and Electricity Markets).

7.4.3

Continental European deregulation

The European market is mainly regulated by a series of directives2 that should eventually be incorporated into domestic law within each member state. The second Gas Directive of 2003 (which repealed the first Gas Directive of 1998) had the objective of creating a single unified market for natural gas. This was complemented by the Gas Regulation of 2005, which expanded on many of the issues outlined in the 2003 Directive. The third European Gas Directive was agreed in 2007 and entered into force in 2009. The directives require each country within the EU to restructure their industry in order to allow consumers greater choice as to who will supply their natural gas. The Gas Directives covered a variety of issues such as: ▪ ▪ ▪ ▪

Unbundling of services provided by integrated companies. Security of supply. Infrastructure. Designation of the transmission system operator to run the high-pressure pipeline network. ▪ Fair access to transmission networks. ▪ Access to storage. 2

An EU regulation is binding in its entirety across all member states. A directive is a legislative act that sets out a goal that all EU countries must achieve. However, it is up to the individual countries to devise their own laws on how to reach these goals.

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▪ Distribution of natural gas to customers. ▪ National regulation. Inevitably any market will evolve according to local conditions and at different speeds. However, a number of common features have evolved for countries that have introduced an element of competition: ▪ Prices are determined more by conditions of demand and supply rather than being set by long-term contracts. ▪ Monopolistic structures have been replaced by the unbundling of functions allowing new companies to enter the market and offer greater competition. ▪ New functions have evolved to meet the demands of the new structures (e.g. shippers). ▪ A new set of regulations has evolved for different elements of the physical supply chain. For example in the UK the Network Code outlines the relationship between the owners of the National Transmission System (NTS) and the gas shipping companies who, in a deregulated market, are now able to administratively arrange for natural gas to be moved along the pipeline. ▪ New traded markets allow the management of natural gas market price risk (both over-the-counter and on an exchange traded basis). ▪ Greater movement of natural gas across international borders in both gaseous and liquefied forms.

7.5

THE DEMAND FOR AND SUPPLY OF NATURAL GAS

7.5.1

Relative importance of natural gas

The annual BP statistical review of world energy provides data in relation to the consumption of energy by fuel type. It defines primary energy sources as: ▪ ▪ ▪ ▪ ▪ ▪

Crude oil Natural gas Coal Nuclear energy Hydro electric Renewables

Figure 6.1 showed the relative importance of natural gas indicating that it comprised 24% of overall energy consumption. The trade in natural gas is characterised by several different features: ▪ Domestic markets where natural gas is moved by pipeline. ▪ The exporting and importing of natural gas internationally by pipeline. ▪ A global seaborne liquefied natural gas (LNG) market.

246

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS S. & Cent. America 4.0%

Europe 1.7%

North America 7.6%

Africa 7.5%

Middle East 38.0%

Asia Pacific 8.9%

CIS 32.3%

FIGURE 7.1 Proportion of proven natural gas reserves. Source: BP Statistical Review of World Energy 2020. BP PLC.

7.5.2

Reserves of natural gas

Figure 7.1 shows the global distribution of proved reserves. In percentage terms the three regions with the largest reserves are: Middle East CIS Asia Pacific

38.0% 32.3% 8.9%

The evolution of each region’s proved reserves over the period 1980–2019 is shown in Figure 7.2. The two countries with the largest proven reserves are the Russian Federation with 38 trillion cubic metres (Tcm) and Iran with 32 Tcm.

7.5.3

Production of natural gas

The evolution of natural gas production on a regional basis is shown in Figure 7.3. Overall production of natural gas has been rising steadily since 1970 from 975 billion cubic metres (Bcm) to 3,989 Bcm in 2019. The highest individual producers of natural gas are the USA (1,128 Bcm) and the Russian Federation (679 Bcm).

247

Natural Gas

Europe S & C America N America Africa Asia Pacific

200 180 160 140 120 100 80 60 40 20 0

CIS

Middle East

18 20 16 20 14 20 12 20 10 20 08 20 06 20 04 20 02 20 00 20 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 19 80 19

FIGURE 7.2 Evolution of proven natural gas reserves; trillion cubic metres 1980–2019 Source: BP Statistical Review of World Energy 2020. BP PLC.

4,500 3,500

S & C America Africa Europe

3,000

Asia Pacific

2,500

Middle East

4,000

2,000 1,500

CIS

1,000 N America

500 0

18

16

20

20

14 12

20

10

20

08

20

06

20

04

20

02

20

00

20

98

20

19

96 94

19

92

19

90

19

88

19

86

19

84

19

82

19

80

19

78

19

76

19

74

19

72

19

70

19

19

FIGURE 7.3 Natural gas production 1970–2019, billion cubic metres. Source: BP Statistical Review of World Energy 2020. BP PLC.

7.5.4

Shale gas

One of the key developments since the publication of the first edition of this text has been the rapid technological advancements made in recovering natural gas trapped in deposits deep in shale rock formations. These shale rocks will often have fractures that contain natural gas and although fracking has existed for many decades, until recently, it has not been commercially viable. This unconventional source of natural gas has had a major impact on the supply side of the market. The two main techniques that have been used are horizontal drilling and hydraulic fracturing (fracking). As the name suggests, horizontal drilling allows the pipeline to the wellhead to bend, which allows the producer to access sources that are considered more difficult to reach. Fracking involves pumping liquids and permeable solids such as sand into the shale formation to widen the fractures, which will then allow the natural gas to flow to the wellhead.

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109

Middle East 76

CIS Africa

63

S & Cent America

46

Asia Pacific

26

Europe

14

USA

13 0

20

40

60

80

100

120

FIGURE 7.4 Reserves to production ratio. Source: BP Statistical Review of World Energy 2020. BP PLC.

7.5.5

Reserve to production ratio

One key concern often expressed in relation to energy is that given that fossil fuels are finite in nature, how long will it be until the resource runs out? The reserve to production ratio (R/P ratio) divides the level of proven reserves at the end of the year by the production in that particular year. The result is the number of years that the reserves would last if production were to continue at that level. At the end of 2019, the global figure was approximately 50 years. The regional distribution is shown in Figure 7.4.

7.5.6

Consumption of natural gas

The evolution of natural gas consumption on a regional basis is shown in Figure 7.5. The USA consumes the largest amount of natural gas (846 Bcm), followed by the Russian Federation (444 Bcm), and then China (307 Bcm). Typically, the largest users of natural gas are: ▪ The electricity sector. ▪ The energy sector (excluding electricity) including entities such as oil refineries. ▪ The residential sector, which significantly impacts the seasonal price patterns of natural gas.

7.5.7

Exporting natural gas

The largest pipeline exporters of gas in 2019 were:

249

Natural Gas 4,500 3,500

Africa S & C America Europe

3,000

Middle East

4,000

2,500

CIS

2,000

Asia Pacific

1,500 1,000

N America

500 0

19 20 17 20 5 1 20 3 1 20 1 1 20 09 20 7 0 20 05 20 3 0 20 1 0 20 9 9 19 97 19 5 9 19 3 9 19 91 19 9 8 19 7 8 19 5 8 19 3 8 19 1 8 19 9 7 19 7 7 19 5 7 19 73 19 1 7 19 69 19 7 6 19 5 6 19

FIGURE 7.5 Natural gas consumption 1965–2019. Source: BP Statistical Review of World Energy 2020. BP PLC. ▪ The Russian Federation exported 217 Bcm mainly to Germany, Italy, and Turkey. ▪ Canada exported 73 Bcm exclusively to the USA. ▪ Norway exported 109 Bcm to several European locations; principally France, Germany, and the UK. ▪ The Netherlands exported 38 Bcm principally to Germany. ▪ Algeria exported 21 Bcm under the Mediterranean to Italy and Spain. From this, it is unsurprising to see that the largest four importers of gas via pipelines were: ▪ ▪ ▪ ▪ ▪

Germany USA Italy China Netherlands

109 Bcm 73 Bcm 54 Bcm 48 Bcm 41 Bcm

These main flows are shown graphically on Figure 7.6.

7.5.8

Liquefied natural gas (LNG)

Countries dependent on natural gas that (for geographical reasons) cannot receive it via a pipeline must resort to receiving the commodity on a seaborne basis in the form of LNG. This is not a competing product to natural gas, but merely an alternative method of distribution. In liquefied form natural gas occupies 1/600 of the space it would in gaseous form making it more viable to transport over longer distances. To create LNG, it is cooled below its freezing point of −161 ∘ C(−260∘ F), and other constituents such as oxygen and carbon dioxide are removed to leave a gas that is virtually pure methane. Once converted it can be transported in specially adapted ships to LNG terminals in any

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

FIGURE 7.6 Movements of natural gas by pipeline. Billions of cubic metres. Source: BP Statistical Review of World Energy 2020. BP PLC. geographical location, where the conversion process is then reversed. However, converting natural gas to LNG is an expensive and complex process that requires a substantial infrastructure, which is expensive and may take many years to construct. Annual production of gas in LNG form is expected to increase from its current levels particularly for countries with high consumption rates relative to their own domestic supplies. The biggest importers of LNG are shown in Figure 7.7. The largest exporters of LNG are shown in Figure 7.8. These main flows are shown graphically on Figure 7.9. Although not immediately obvious from the figures, there are certain countries (e.g. USA, Trinidad and Tobago, Nigeria) that export small amounts of LNG to many countries.

7.6 7.6.1

NATURAL GAS PRICES Natural gas price definitions

Before considering the factors that influence the price of natural gas, it is perhaps useful to consider what is meant by the term ‘price’. From a retail perspective, the price of natural gas may vary (due to price changes at the wholesale level), but may be influenced by regulatory considerations. However, the price of natural gas at the wholesale level will be influenced by a very different set of factors. In a highly monopolistic natural gas

251

Natural Gas

Japan

105

China

85

South Korea

56

India

33

France

23

Taiwan

23

Spain

22 18

United Kingdom 0

20

40

60

80

100

120

FIGURE 7.7 Major LNG importers. Billion cubic metres. Source: BP Statistical Review of World Energy 2020. BP PLC.

Qatar

107

Australia

105

USA

48

Russian Federation

39

Malaysia

35

Nigeria

29

Indonesia

22

Algeria

17

Trinidad & Tobago

17 0

20

40

60

80

100

120

FIGURE 7.8 Major LNG exporters. Billion cubic metres. Source: BP Statistical Review of World Energy 2020. BP PLC.

industry, contracts to buy or sell natural gas may well be long-term, bilateral, and fixed price in nature. ‘Take or pay’ contracts might exist if a buyer doesn’t take delivery of the agreed volume, they would have to pay a fee. Although aspects of these types of pricing structures may persist in a re-regulated market, there is now a greater possibility that the price will be based on fundamental demand and supply considerations. As a result, a term structure of prices would gradually evolve along with the use of risk management products. As with any commodity there will be different prices for delivery of natural gas for different maturities and for different locations. However, although there may be a common set of delivery maturities, there will be different sources for reporting prices of deals executed. To ensure the efficient settlement of a variety of contracts (e.g. physical supply contracts or derivatives) the emergence of a single, credible, and accepted benchmark reference is key. For the energy markets there are a variety of different possible

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FIGURE 7.9 Movements of LNG. Billion cubic metres. Source: BP Statistical Review of World Energy 2020. BP PLC. sources. For example, this index should be representative of market conditions at a particular time and that the market is liquid (defined as the ability to execute a transaction without significantly moving the price). Some contracts may be settled against a price quoted on a futures exchange such as ICE or NYMEX (which is part of the CME Group). Examples of natural gas prices in different countries (UK, Holland, and the USA) are shown in Figure 7.10. Other popular price sources are privately owned, price reporting publications such as the Heren European Spot Gas Markets (HESGM) published by ICIS and ‘Inside FERC’ published by S&P Global Platts for the US market. The HESGM reports a variety of different prices, which include: ▪ Monthly and daily price indices for a variety of locations (e.g. UK NBP, and continental hubs such as Zeebrugge), ▪ Quoted prices that cover natural gas for delivery day-ahead, weekend, working days next week, the balance of the month, monthly, quarterly, and annually, Inside FERC reports: ▪ Spot prices of natural gas delivered to a variety of pipelines. ▪ Spot prices for different market centres.

253

Natural Gas 12.00 10.00 8.00 6.00 4.00 2.00 0.00

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

UK NBP

NL TTF

US Henry Hub

FIGURE 7.10 Natural gas prices. USD per million Btu. NBP = National Balancing Point, TTF = Title Transfer Facility. These are virtual pricing points through which all gas in that country is deemed to flow. Source: BP Statistical Review of World Energy 2020. BP PLC.

7.6.2

Oil indexation in the natural gas market

Where the price of natural gas is determined by the interaction of fundamental demand and supply, this is referred to as ‘gas-on-gas’ pricing. The linkage between the price of natural gas and crude oil (‘gas to oil pricing’) stems from a number of reasons and affects both regulated and re-regulated markets. The linkage exists for a number of reasons: ▪ Both energy sources are often found together. By linking the price of natural gas to oil energy, companies would not be incentivised to produce one source over another. ▪ The early natural gas finds in Europe were valued based on alternative fuels, which commercial and domestic consumers had used prior to this time. As a result, natural gas contracts for industrial consumers tended to be linked to the price of fuel oil, power generation contracts to the price of fuel oil or coal, and domestic supply contracts to the price of gas oil. In some cases, contracts could also be linked directly to the price of a particular crude oil (e.g. Brent). ▪ When natural gas became more of a substitute for oil, natural gas price rises became indexed to the changes in the oil price to ensure that it remained attractively priced and retained its market share. ▪ For some end users there is an element of substitutability between different fuel sources, so relative pricing becomes important. ▪ Since oil-based products are mature liquid markets, they provide an attractive relative pricing source in geographical locations where natural gas markets are considered illiquid. This was particularly relevant when banks were lending to large exploration and production projects. To ensure there were sufficient cash flows to service the debt, this led to the development of long-term natural gas sales contracts that were indexed to oil-based products.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

One interesting illustration on the role of oil prices within a deregulated market is the situation faced by the UK. Many large industrial consumers and power stations can operate using either natural gas or oil-based products. As a result, the gas-oil price link will have an indirect impact on the price of natural gas. Additionally, as the UK becomes more reliant on overseas European imports, its main source of supply will be from a variety of different countries within Europe. Since a significant proportion of natural gas contracts in Europe are indexed to the price of crude oil, and if natural gas is imported via the Interconnector, the price charged to the purchaser will be influenced by the price of oil. A report published by the European Commission in 2006 about competition in the European Gas markets highlighted more detail about the nature of oil indexation in the region. It noted that supply agreements were characterised by long-term contracts of between 15–20 years in duration and generally included a pricing formula that was indexed to a variety of different fuels. There is no single indexation formula that applies across all markets but there may be common elements to the supply contracts in which they are embedded: ▪ A predefined maturity, say, 10 or 20 years. ▪ A ‘take or pay’ clause that requires the buyer to take delivery of an agreed quantity of gas or to pay for it even if it is not required. These contracts are also sometimes termed ‘take and pay’ or ‘swing options’. ▪ The price of natural gas in these contracts is usually recalculated every one to three months. A hypothetical indexation formula might have the following characteristics. Let us assume that a gas supplier was fixing their prices with a large industrial consumer as of 1 September of a particular year. There will be a base price for the natural gas, which may be adjusted by the average price of the chosen oil-based product (e.g. fuel oil) that prevailed over a three-month period with a one-month lag. So, in this example, the pricing window would extend from 1 May–1 August. The contract price would then be valid for, say, a three-month period to 1 December. The effect is to link the price of natural gas to the price of oil, but with the effect being both lagged and damped by the averaging process. This indexation formula would be referred to as a ‘3-1-3’. The end formula will normally include adjustments to ensure that the final price takes account of the fact that the prices of the different oil products are expressed in units of volume rather than units of energy, and may be traded in a different currency, and may have different thermal properties. The EC report suggested that about 75% of all contracts were indexed and the most popular oil-based products were light fuel oil, gas oil, and heavy fuel oil. This figure varied according to the region of natural gas production. In the UK, the figure was closer to 20% with the main pricing basis being either market determined or one that was linked to the rate of inflation. In the Netherlands, Norway, and Russia, the indexation patterns were revealed that about 80% of production was indexed to heavy and light fuel oils. As a result, it would be reasonable to say that regulated markets are characterised by longer-term contracts, with take or pay clauses and prices indexed to oil-based

Natural Gas

255

products. Deregulated markets would have a wider range of contract maturity from within day contracts to longer-term contracts (but not as long as those seen in regulated markets). Prices are more likely to be indexed to the fundamental demand and supply factors for natural gas. It would seem likely that the influence of crude oil and the refined products will continue to exert an influence over EU pricing structures since Netherlands, Norway, and Russia supply about 60% of Europe’s natural gas needs. The advent of a re-regulated market will not necessarily signal the immediate end of the influence of oil on natural gas prices given that contracts indexed to oil tend to be very long term in nature.

7.6.3 7.6.3.1

Liquefied natural gas (LNG) prices Overview of LNG contracts

LNG contracts are sometimes referred to as ‘sales and purchase agreements’ (SPA). They represent a binding contract between buyer and seller for the purchase or sale of an agreed amount of LNG for delivery over a specific period at an agreed price. The terms of the contract would typically include: ▪ Duration – traditionally SPA contracts were very long term in nature (e.g. 20 years) as the sellers needed to ensure sufficient cash flow to repay their capital investment. Although this term of contract still exists, there has been a gradual move to shorter-term transactions combined with an increase in spot trading. Buyers may also have infrastructure investments to finance and so may also be happy with long-term contracts as they offer cash flow certainty. ▪ Volumes – although the contract may state an annual volume, there may be some flexibility for the buyer. For example, it may allow them to take an increased amount or to elect not to take part of their contracted delivery without activating any ‘take or pay’ clause. ▪ Take or pay clause – this requires the buyer to pay for a minimum amount of LNG whether they take delivery or not. Sometimes this clause may stipulate that a certain percentage of their annual contract quantity must be taken; this might range from 85–100%. ▪ Destination clauses – in some LNG contracts there may be a clause that limits the buyer’s ability to transfer the cargoes to another entity or that restricts the buyer from nominating an alternative delivery terminal. From a buyer’s perspective this clause could be restrictive, as having some degree of flexibility over the end destination would help them manage any ‘take or pay’ risks, particularly if the original destination is oversupplied. Sellers were also concerned that buyers may be tempted to arbitrage market prices by selling on a cargo to another buyer, which would then mean it would become another source of supply. These destination clauses are gradually becoming less common as certain jurisdictions may view them as being anti-competitive. ▪ Payment terms – this will state whether the price is ‘free on board’ (FOB) in which the buyer is responsible for the shipping costs or ‘cost, insurance, freight’ (CIF) in which the seller is responsible for shipping costs.

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▪ Pricing basis – Since there is no overarching global price for natural gas, this clause describes how prices would be determined. It may be formula-based, referencing crude oil, or based on an agreed gas index price such as the Henry Hub natural gas future. The contract may also include some provision to renegotiate the pricing terms during the life of the contract. 7.6.3.2

Asian LNG physical pricing

Asian LNG contracts are an interesting case study on how the pricing process has evolved over time. In the very early days of the LNG market, contracts were often simple fixed-price transactions. However, after the oil crises of the early 1970s, there was a move towards using an index, which would capture the economics of higher crude oil prices. Arguably, the most popular crude oil index formula is the Japan Customs-cleared Crude (JCC), sometimes nicknamed the ‘Japanese Crude Cocktail’. The typical structure of an LNG pricing contract that references the JCC formula is: Price of LNG = A × (Price of crude oil) + B The price of LNG would be expressed in USD per MMBtu. ‘A’ was the degree of indexation to oil prices, which could range from 11–15%. The magnitude of this co-efficient was designed to reflect the degree of ‘oil/natural gas parity’. This is the LNG price that would be equal to that of crude oil on a barrel equivalent basis. A co-efficient of 0.1724 is full oil parity. If the agreed co-efficient was, say, 0.1485 this would suggest that the contract had an 85% crude oil linkage (0.1485/0.172). So, a 1% increase in the price of crude oil would mean that, all other things being equal, the price of LNG would increase by 0.85%. The price of crude in the formula was the price of JCC, which is based on the average price of crude oil imported into Japan. This could be based on an average price over several previous months with an agreed time lag. ‘B’ was a constant term that represented non-oil factors (e.g. shipping costs) and ensured that LNG prices did not fall below a certain level. Although this example illustrated how a link to the price of crude oil could be established, since these LNG contracts are all individually negotiated, it is possible to reference the price to other competing sources of energy such as a fuel oil, gas oil, and coal. Another pricing concept worthy of mention is the ‘S’ curve, a stylised example of which is shown in Figure 7.11. The basic idea is that there are different values for A and B, which depend on the range of prices taken by the price of crude oil. In low crude oil price scenarios, there is price support for LNG sellers, while the formula has a dampening effect on the value of LNG at higher crude oil prices, which protects LNG buyers. In more recent times, the market has gravitated towards using natural gas benchmarks with contracts referencing non-Asia indexes such as US Henry Hub or UK National Balancing Point (NBP), given that there was no Asian natural gas pricing point. As the market continues to grow there has been a move toward specific Asian price indexes such as the S&P Global Platts Japan Korea Marker (JKM). The marker

257

Natural Gas LNG contracted price

Price support for buyers LNG = A3 x JCC + B3

Price support for sellers LNG = A1 x JCC + B1 LNG = A2 x JCC

Oil price

FIGURE 7.11 LNG ‘S’ curve.

reflects the spot market value of LNG cargoes delivered ‘ex-ship’ (DES3 ) into Japan, South Korea, China, and Taiwan. Figure 7.12 illustrates the movements in price between four natural gas price indices from 2009 to 2019. The price correlation over this period between the JKM and the various indices are: 0.97 − UK NBP 0.96 − NL TTF 0.36 − US HH

7.7 7.7.1

NATURAL GAS PRICE DRIVERS Supply side price drivers

On the supply side of the price equation there are several key issues: ▪ Current levels of domestic production and proven reserves – for some countries, the balance between the levels of domestic production and imports will have a big impact on price. For example, the UK became a net importer of natural gas from continental Europe in 2005, which introduced a new set of price dynamics such

3

DES means that the seller fulfills his obligation to deliver when the goods have been made available to the buyer on board the ship uncleared for import at the named port of destination. The seller must bear all costs and risks involved in bringing the goods to the named port of destination.

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18.00 16.00 14.00 12.00 10.00 8.00 6.00 4.00 2.00 0.00

2010

2011

2012

UK NBP

2013

2014

NL TTF

2015

2016

US Henry Hub

2017

2018

2019

JKM

FIGURE 7.12 Natural gas benchmark prices 2009–2019. USD per million BTU. Source: BP Statistical Review of World Energy 2020. BP PLC. as increased sensitivity to changes in the price of crude oil. If the amount of natural gas to be extracted falls below initial expectations, this may exert upward price pressure. ▪ Production outages due to accidents or weather – for example, US natural gas production, which is very concentrated in the Gulf of Mexico, can be susceptible to weather disruption (e.g. Hurricanes Katrina in 2005 and Harvey in 2017). Within this category, it would be appropriate to include the closing of fields for maintenance during certain times of the year when demand is expected to be low. ▪ Available infrastructure – like many commodities there is a limit to the flexibility of supply because infrastructure projects will require a long time to complete. Interconnectors are large international pipelines used to transport natural gas. If the price of continental natural gas is higher than that in the UK there is an incentive to deliver natural gas into Europe, while the opposite will hold true if the price of UK natural gas is higher than that seen on the continent. The size and timing of planned infrastructure projects such as storage facilities, new interconnectors, and LNG terminals may influence prices for delivery of natural gas in the future. One particular day, shortly after the opening of the Langeled Norwegian pipeline to the UK, a combination of factors (warm weather, a major incoming shipment of LNG, a shortage of storage capacity, and a large delivery to test the interconnector) caused a surplus of supply. National Grid Gas reported that 344 million cubic metres were available compared with estimated demand of 234 million cubic metres. This led to suppliers paying buyers to take up the excess with the price of gas reportedly falling to minus five pence per therm. ▪ Storage capacity – it is common for natural gas to be stored under and above ground to absorb any change in the demand and supply balance. A lack of storage capacity may cause prices to increase sharply if, for example, there is an unexpected spell of cold weather.

Natural Gas

259

▪ Security of natural gas supplies – traditionally Western Europe has been able to source its natural gas supplies from four key areas: ▪ The North Sea (from UK, Norwegian, and Dutch owned fields). ▪ Onshore European natural gas fields. ▪ Russia. ▪ Algeria. Security of supply can be interpreted as either the availability or reliability of natural gas supplies and is a key factor for countries that are reliant on imports of natural gas, particularly where there is no diversification of supply. Security of supply is enhanced by the existence of a diversified source of supply, adequate transmission infrastructure, and sufficient storage facilities. Arguably, the converse could also apply, i.e. the security of demand; that is one country becomes over-reliant on a single buyer and could suffer economically if that relationship were to deteriorate. ▪ Proportion of natural gas that is exported – one characteristic of the natural gas market has been the increase in the trading of LNG. The more that is exported – perhaps driven by higher prices in other regions – the lower the domestic supplies and, all other things being equal, the higher the price. For example, at the time of the first edition of this text, BP estimated that the US was a net importer of 109 billion cubic metres (Bcm) of natural gas, but by 2019 they were net exporter of 123 Bcm, largely due to the impact of shale gas. ▪ Concentration of suppliers – The Economist (2012) argues that liberalised markets tend to hand power to big suppliers. A large supplier could manage its production in such a way that spot prices could be influenced in a particular direction.

7.7.2

Demand side price drivers

The demand side of the market is driven by: ▪ Seasonal demand or weather – The main component of natural gas demand is domestic for heating and cooking requirements and so a change in the weather may lead to a change in demand. ▪ Degree of domestic competition between suppliers – As the choice of suppliers increases the price of natural gas should fall. ▪ Electricity generation – Natural gas is seen as a more environmentally attractive fuel to run electricity power stations compared to coal. The deregulation of the electricity market has further spurred the growth of natural gas. However, as technology improves, the importance of renewable energy is likely to increase. ▪ Exports – Since the UK is now linked to the rest of Europe via a series of pipelines; it is possible to export gas to other countries if there is an increase in demand. ▪ Storage injections – Typically natural gas is injected into storage in the summer when demand is relatively lower. ▪ Relative prices of competing fuels – As the price of alternative fuels increase relative to natural gas, there is greater incentive to produce and consume natural gas.

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7.7.3

LNG price drivers

There are several more specific factors that influence the pricing of LNG contracts: ▪ ▪ ▪ ▪ ▪ ▪ ▪

The number of competing supply projects, Demand for LNG from other potential customers, Buyer’s willingness to take an equity stake in the project, Buyer’s flexibility around the destination of the shipment, The required volumes, Availability of LNG vessels, The level of reserves.

7.8

TRADING NATURAL GAS

One of the impacts of moving from a monopolistic structure characterised by long-term fixed pricing agreements, is the move to shorter-term trading arrangements. The motivations for trading natural gas can be explained within the context of the risks faced by different elements of the physical supply chain.

7.8.1

Motivations for trading natural gas

Producers will be concerned with maximising their revenues and meeting contractual supply commitments. If they are unable to produce natural gas to meet their requirements, they may be forced to enter the market to purchase the amount they need from a third party in order fulfill the delivery to their end client. Additionally, if they have flexibility to increase their production they may be tempted to produce more if they believe they will be able to sell it at a higher price. They may be faced with a number of different supply contracts with different maturities that they may or may not be able to meet from their existing production. Additionally, the contracts may be priced in a variety of different ways (e.g. fixed, floating, oil indexation). This may motivate them to enter into derivative contracts to mitigate the associated risk. The flip side of this are the consumers of natural gas who will be looking to ensure that they can supply sufficient gas at the most cost-efficient price. Like the producers, they will be faced with a variety of market risks that they may wish to mitigate. Since shippers are responsible for ensuring that their demand and supply commitments are in balance, they may be forced into the market to buy and sell natural gas. The TSO will be responsible for ensuring that overall, the system is in balance and so may need to buy and sell natural gas to achieve this. With respect to storage, one of the popular strategies that are used by traders and consuming utilities is to buy natural gas when it is cheap (e.g. in the summer months), in anticipation that the revenues generated at its eventual point of sale will exceed all associated costs. Financial institutions (e.g. banks and trading houses) will offer risk management solutions to those entities along the physical supply chain. As such they will take on a particular risk that they will then seek to offset at a profit by trading with similar institutions. For example, they may identify an opportunity to arbitrage the price of natural in two different locations (e.g. UK NBP vs. Zeebrugge).

Natural Gas

7.8.2

261

Contract types

Natural gas contracts (physical or financial) can be traded either on an exchange or over the counter basis. For example, within the UK there are two main organised exchanges: the Intercontinental Exchange (ICE) and the On-the-Day Commodity Market (OCM), both of which will result in physical delivery if the contracts are held to maturity. The OCM market is designed to allow market participants to balance their short-term demand and supply commitments. The OCM market also allows the system operator to buy and sell natural gas for operational and safety reasons. Physical contracts can be executed with a variety of different maturities: ▪ ▪ ▪ ▪

Same day (sometimes referred to as ‘within day’). Next day (variously called ‘prompt’ or ‘day ahead’). Future months (buying/selling of gas every day of the specified month). Future quarters (buying/selling of gas every day for the three months of a specific quarter). ▪ Seasons – this could be the summer period (April–September) or winter (October–March). ▪ Annual contracts – Either the calendar year (buying/selling gas every day for the 12 months covering January–December) or the gas year (October–September); buying/selling gas every day for a 12-month period covering October to the following September.

7.8.3

Delivery points

Within any natural gas market, agreement must be reached as to where the transfer of natural gas ownership will occur. As a result, several popular delivery locations have evolved, that are either physical or virtual in nature. There are many natural gas market hubs in the USA of which the most cited delivery point is the Henry Hub in Louisiana, which is the physical meeting point for 12 intraand interstate pipelines. Traditionally, a significant proportion of natural gas would be taken from various production points in the Gulf of Mexico and then fed to a number of states through the East Coast, Midwest, and up to the Canadian border. However, the advent of shale gas continues to reshape these flows. Although it is possible to buy and sell gas in any location, the price may be quoted as a spread (referred to as the location differential) to the Henry Hub figure. In a similar vein, the Zeebrugge hub is a common delivery location in continental Europe as it represents the physical junction of several international pipelines. If the hub is physical in nature, then it is likely that there will be a range of other facilities available to the market participants such as storage and treatment facilities. In some markets there may be a notional or virtual settlement point, which covers an entire network. In the UK there is a virtual delivery point referred to as the National Balancing Point (NBP), which is a notional point within the national transmission system through which all natural gas is deemed to flow and about which all natural gas is required to balance. The Dutch national transmission company has created something like the UK, which is referred to as the Title Transfer Facility (TTF).

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7.8.4

Trading natural gas in the UK

Over-the-counter (OTC) trades broadly encompass four different types of transaction. NBP spot and forward transactions, beach contracts, and interconnector trades. These trades can vary in their maturity; for example, NBP trades are quoted from ‘within day’ out to three years. Each counterparty will undertake to make trade nominations to the system operator as to the quantity of natural gas and the period of the performance to which it relates. An NBP transaction could also be executed such that the buyer and seller will trade the right of ownership of natural gas within the NTS. Since the natural gas is already within the NTS, the system operator will simply have to make an adjustment to the accounts of the two shippers as to the quantity traded. Beach trades are bilateral contracts where the purchase or sale will take place at a specified natural gas terminal where it is brought ashore from a production facility. These deals are executed for natural gas transactions outside of the NTS and can be useful for a shipper who is looking to resolve an anticipated system imbalance. Interconnector trades for delivery at, say, Zeebrugge will operate in a similar fashion. One of the key requirements of the Network Code is that shippers are required to balance their daily injections with daily deliveries at the NBP. If actual natural gas usage is not equal to the amount nominated, the shipper will be out of balance. The system will be long natural gas if too much is delivered, or the withdrawals (‘offtake’) are less than expected. The system will be short natural gas if the shipper did not deliver enough or the offtake was more than expected. This imbalance can be anticipated by the TSO by matching nominations made by different shippers to buy and sell natural gas. There are several ways in which the system can be brought back into balance: ▪ Shippers can obtain or dispose of natural gas in the On-the-Day Commodity Market (OCM). ▪ Shippers trade with producers outside of the national transmission system using beach contracts. ▪ The system operator can buy or sell natural gas on the OCM if they believe an imbalance will occur and settle retrospectively with a particular shipper. ▪ The system operator or shippers use contracts to extract natural gas from storage. ▪ Certain clients have agreements whereby their supply can be interrupted.

7.8.5

On-the-Day Commodity Market (OCM)

The OCM was set up as part of the re-regulation process of the UK Natural gas industry to help manage system imbalances. Access to this 24-hour electronic market is restricted to the system operator and licensed shippers. Transactions can be executed between these counterparties for either balancing purposes or for pure trading motives. This regulated market currently has two different segments, the day-ahead market and the OCM within-day market. The day-ahead market offers four different types of contract: ▪ ▪ ▪ ▪

Individual days Balance of the week Weekend strip Working days next week

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263

The OCM within day market offers three types of transactions. A locational trade allows for the purchase or sale of natural gas at specific points on the NTS. A physical trade allows for the purchase or sale of physical natural gas at the NBP. Title trades represent a change of ownership of natural gas already at the NBP. If National Grid Gas is required to buy extra natural gas to make the system balance, an imbalance charge is subsequently made to the offending shipper at what is referred to as the System Marginal Price (SMP). On the OCM the ‘SMP buy’ is the highest price at which the system operator bought natural gas for the system, while ‘SMP sell’ is the lowest price at which natural gas was sold out of the system. A related concept is the System Average Price, which is a volume-weighted average of all buy and sells.

7.9 7.9.1

NATURAL GAS DERIVATIVES Exchange traded futures contracts

A natural gas futures contract for the UK was first listed in January 1997. It can be used for a variety of reasons: ▪ To help manage a market participant’s natural gas price exposure. ▪ As a means of taking exposure to the gas market without necessarily having an underlying exposure. To avoid taking physical delivery, the investor would close out the futures position prior to expiry. ▪ The futures market can also be used to obtain or dispose of supplies to the natural gas market, as all the contracts will result in physical delivery at the NBP if held to maturity. 7.9.1.1

Futures contract specification

Table 7.1 highlights the main features of the UK natural gas future traded on the ICE and the Henry Hub natural gas futures traded on the NYMEX exchange, which is part of the CME Group. It should be noted that each exchange trades several different types of contract and the following table is designed to convey the main contract characteristics. For the contracts traded on the ICE, if the contract is not closed out prior to its expiry the counterparties will be expected to go to full delivery in equal measure on each individual day that the contract covers. Month contracts are strips made up of individual and consecutive calendar days, the total number of which is dependent on the number of days in the month. These contracts will be listed up to 83 months in the future. Quarter contracts are strips of three individual and consecutive calendar months. However, the contracts are standardised to given time periods (e.g. January–March) rather than being a negotiable set of consecutive months. Season contracts are strips of six individual and consecutive contract months. Season contracts are specified as either April–September or October–March. Annual contracts are strips of 12 individual and consecutive contract months comprising January–December. On NYMEX the most popular contract is for monthly settlement with physical delivery at Henry Hub (HH). However, NYMEX (as well as the ICE) have recognised

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TABLE 7.1 Contract specifications for UK and US natural gas futures. ICE

NYMEX

Contract size Unit of trading

Five lots One lot equals 1,000 therms of natural gas per day

Quotation

The contract price is in sterling and in pence per therm 0.01 pence per therm

One lot One lot equals 10,000 million British thermal units (MMBtu) US dollars and cents per MMBtu UDS 0.001 (0.1c) per MMBtu (USD 10.00 per contract) Monthly contracts listed for the current year and the next 12 calendar years

Minimum price fluctuation Contract description

Last trading day

Delivery

▪ ▪ ▪ ▪

Annual contracts Season contracts Quarter contracts Month contracts

Trading will cease at the close of business, two business days prior to the first calendar day of the delivery month, quarter, season, or calendar year. Contracts are for physical delivery through the transfer of rights at the UK National Balancing Point. Delivery is made equally throughout the delivery period.

Three business days prior to the first calendar day of the delivery month

Physical delivery at the Sabine Line company Henry Hub in Erath, Louisiana

Source: ICE, www.theice.com; CME Group, www.cmegroup.com

that there are a number of other natural gas pricing points in the USA and Canada and therefore offer a number of ‘basis’ contracts that are quoted as price differentials between various pricing points and Henry Hub. For example, if a natural gas consumer wanted to hedge the cost of natural gas for delivery at a different location than Henry Hub, then the use of a HH future would leave them exposed to basis risk. That is, the price they would pay for the delivery of their physical natural gas could be different than that received under a Henry Hub delivered future. The issue of basis risk is considered below in Section 7.9.2.2. 7.9.1.2

Applications of exchange traded futures

Hedging the purchase cost of natural gas Let us assume that a UK industrial consumer has a commercial agreement with a producer to receive physical natural gas on a regular basis. The price agreement is based on the prevailing ‘spot’ price at the time of delivery, as the producer is not prepared to enter into a fixed price contract. The consumer decides to buy a single month natural gas future on the ICE for delivery in three months’ time. The price quoted for this

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future is 44 pence per therm. The consumer decides to close out the futures position at the last possible moment to avoid physical delivery (the ICE future expires two business day prior to the start of the contract delivery period). We will assume that on the close out date the price achieved for selling the future is 48p/therm. If we assume that the futures and spot price have converged, the consumer takes delivery of the natural gas at the same price from his supplier, his cost will be 48p/therm minus the profit on the future of 4p/therm. This gives a cost of 44p/therm, a sum equal to the original futures price. Futures calendar spreads for natural gas storage operators For those companies who run storage facilities, they will either be storing natural gas on behalf of another entity within the supply chain or will hold it for their own account. If there is excess storage capacity, it may be possible to generate an arbitrage profit. Recall from Chapter 2 on valuation that one approach to analysing the forward price of an asset is the spot price plus the cost of carrying an underlying position for the duration of the transaction. This cost of carry would be driven by such elements as the cost of financing the purchase of the commodity and the cost of its storage. If the cost of storage in a facility is less than the value embedded within an observed forward price it may be possible for the storage operator to execute an arbitrage trade. For example, let us assume that the storage operator has identified that they will have excess capacity in one month’s time for a period of one month. Let us assume that the price of natural gas for one- and two-month delivery is 50p/therm and 53p/therm respectively. If they were to buy the natural gas for forward delivery in one month and simultaneously sell it forward for delivery in two months, they would make a profit if the associated costs of taking physical delivery in one month’s time and storing it are less than the price differential earned from the futures trades. So, if the cost of storing the gas for one month is, say, 1p/therm, their profit would be 2p/therm (53-50-1). This strategy is referred to as ‘going long the calendar spread’. That is, the trade is the simultaneous purchase of a short-dated futures contract with the sale of a longer dated futures contract. The use of exchange traded futures by the various entities along the supply chain for natural gas is summarised in Table 7.2. Exchange for Physicals (EFPs) An EFP represents a mechanism that will allow two entities to use the futures exchange as means of fixing the price for a physical supply contract without using the exchange to fulfill delivery. An example based on crude oil is covered in Section 6.8.2.5. Let us take an example of a producer of natural gas who has agreed to supply 50,000 therms per day to an end user for the month of August. We will assume that both sides are unable to agree on the price terms and so agree to use the EFP mechanism. EFPs need to be registered with the relevant exchange prior to the maturity of the particular futures contract to which they relate. They agree to register this trade 15 business days prior to the contract maturity. We will assume that five business days later the producer enters

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TABLE 7.2 Potential applications of exchange traded futures. Participant

Nature of price exposure

Action

Producer Shipper/Marketer

Exposed to falling prices If long natural gas, exposed to falling prices If short natural gas, exposed to rising prices Similar to shippers If long natural gas, exposed to falling prices If holding excess storage capacity held Exposed to rising prices

Sell futures Sell futures

Traders Storage

Consumer

Buy futures Buy/sell futures Sell futures Buy short-dated futures, sell long dated futures Buy futures

the ICE futures market and sells 50 lots (1 lot = 1,000 therms) at the prevailing price of 44p/therm. The consumer will do the opposite trade (i.e. sell 50 lots) but can choose the timing of the trade to any point after the registration of the EFP but prior to maturity of the future. There is no requirement for the two parties to execute the futures trades at the same time. We will assume that the consumer executes the purchase leg the following day when the futures price has risen to 46p/therm. Since neither party wants to use the exchange as a mechanism for delivery of the natural gas, they agree to a nominal price to close out their futures positions, which will also be used to settle the physical contract. We will assume that they agree the futures close out price to be 45p/therm. From the producer’s perspective they have: ▪ Sold the future at 44p/therm. ▪ Closed out futures position at 45p/therm. ▪ Delivered the natural gas to consumer at 45p/therm. As a result, their net income on the transaction is 44p/therm. This is calculated as the money received from the consumer for the physical natural gas (45p/therm) less the 1p/therm loss on the futures transaction. From the perspective of the consumer they will have bought the futures at 46p/therm and will close out at the agreed price of 45p/therm to make a 1p loss. They take delivery of the natural gas at the agreed close out price of 45p/therm resulting in a net cost of 46p/therm. In both instances the price paid or received for the natural gas was determined by the price at which the initial futures position was executed.

7.9.2

Over-the-counter natural gas transactions

OTC contracts can be separated out into two main types, physical or financial. Physical natural gas transactions will involve the delivery of natural gas whereas financial contracts will be cash-settled.

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7.9.2.1

Physically settled forward contracts

Fixed price forward contract The following term sheet indicates the typical terms for a physical contract that is executed at a fixed price: Seller: Buyer: Trade date: Supply period: Daily quantity: Total quantity: Price:

Bank/trading house Client November 06:00, 1 March to 06:00, 1 September (184 days) 25,000 therms 4,600,000 therms Forty-five spot five five (45.55) pence per therm

In this contract the seller is responsible for delivering 4.6 million therms over a six-month period in equal amounts per day (i.e. 25,000 therms per day). This type of contract includes a clause that outlines the compensation that either party will have to pay if they fail to perform as part of the contract. The market has adopted a common set of terms and conditions to manage such a situation. Say that the client is unable to receive the contracted amount. The seller would then have to dispose of the natural gas in the marketplace. The compensation that either side of the contract would face for a breach of contract is based on the system marginal price (SMP) traded on the OCM.

Floating price forward contract Here the price is not fixed but will be based on an agreed index. A typical term sheet, linked to the day-ahead price quoted by ICIS Heren, might look as follows: Seller: Buyer: Transaction date: Supply period: Supply quantity: Price: Index price:

Bank/trading house Client November 06:00, 30 November to 06:00, 1 December 400,000 therms A price expressed as a price per therm equal to the Index Price. For delivery on a Business Day, that day’s price as stated in pence per therm of natural gas for the ‘Day Ahead’. For delivery on a day which is not a Business Day, that day’s price as stated in pence per therm of natural gas for the ‘Weekend’; each as published in the column NBP under the heading ‘NBP Price Assessment’ in the issue of ICIS Heren European Spot Gas Markets, published on the Business Day immediately preceding that day of delivery.

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A US floating contract might contain the following terms: Seller: Buyer: Transaction date: Delivery period:

Contract quantity: Price: Index price:

Bank/trading house Client December Each calendar day from and including 09:00 Central Standard Time (CST) 1 January to and including 09:00 hours CST 31 January in the same calendar year. 6,000 MMBtu per calendar day in the delivery period. A price expressed as a price per MMBtu equal to the Index Price. “NATURAL GAS LOUISIANA / SOUTHEAST HENRY HUB” meaning the contract price will be a price stated in USD per MMBtu of natural gas, calculated on the first business day of the calendar month following each month in the delivery period, published under the heading ‘Final daily price survey - Platts locations (USD / MMBTU)’: in the issue of ‘Gas Daily’ for such calendar month.

Another variation of this type of structure is to link the price to an exchange traded future. A hypothetical UK transaction linked to the price of the ICE future would have the following terms: Seller: Buyer: Transaction date: Supply period: Daily quantity: Total supply quantity: Contract price:

Bank/trading house Client March 06:00, 1 July to 06:00, 1 August (31 days) 20,000 therms 620,000 therms ‘Natural gas – ICE – Monthly index’ meaning the contract price will be a price stated in pence per therm of natural gas, calculated as the average of prices per therm of natural gas published on the ICE on each day of the calendar month preceding the prompt calendar for delivery in the prompt calendar month.

In this contract a single price will apply for each daily delivery, but this will not be agreed at the time of the trade. In this example, the price applied will be based on the daily average of the July futures price, in the month prior to delivery.

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Option on physically settled fixed price forward It is also possible to execute an option for physical delivery. For example, a client may decide to buy a put option, which would give them the right to sell natural gas for delivery at the NBP. Indicative terms might look as follows: Transaction date: Seller: Buyer: Option style: Option type: Expiration: Strike price: Premium: Total premium:

September Bank/trading house Client European Put 23 December 35p/therm GBP 0.00675/therm GBP 27,202.50

If the client exercises the put then bank/trading house will buy natural gas from the client under a pre-agreed set of terms, an example of which is given below: NBP trade Buyer: Seller: Supply period: Daily quantity: Price per therm:

Bank/trading house Client 06:00, 1 January to 06:00, 1 February 130,000 therms 35p

If the option is not exercised, then the seller simply collects the premium. The premium cost is calculated as 130,000 therms a day for 31 days at £0.00675 per therm. Options on UK gas can trade with implied volatilities that range from 40–90% and are often structured with Asian-style (i.e. averaging) payoffs. 7.9.2.2

Natural gas swaps

Cash settled transactions are attractive to either producers or consumers where they wish to separate the physical delivery or receipt of the natural gas from the associated price risk. Additionally, there may be traders and hedge funds that have no physical capabilities but wish to take price exposure to the market without the need to trade in the underlying instrument.

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Natural gas swaps can be used for a variety of purposes: ▪ To manage the basis risk of delivering natural gas at different physical locations. This could be achieved by entering a swap where the cash flows are linked to prices in different delivery locations. ▪ To transform the price risk of a physical purchase or sale (e.g. from a fixed to floating exposure). ▪ As a means of exploiting a potential view on a rise in a natural gas price. Vanilla natural gas swap Take for example a hedge fund that decides to take exposure to the underlying price of UK natural gas. It enters a natural gas swap, with a maturity of six months, starting one year after it has been traded. The swap will involve an exchange of cash flows, where one will be fixed, say, 70 pence/therm and the other will be based on an index price taken from ICIS Heren. The floating index might be the daily, unweighted average of day-ahead prices quoted by the same source. The floating side of the swap can also be based on the arithmetical average of a futures price, such as the price of the front month ICE UK natural gas futures. The cash flows will be exchanged monthly and will be based on a notional quantity of 30,000 therms per day and so with a 182-day period this would give a total quantity of 5,460,000 therms. Settlement of cash flows would take place five business days after the end of the monthly calculation period. By way of example let us assume that at the end of one of the settlement months that the daily average of prices quoted by ICIS Heren was 66.56785 pence (the accuracy of the calculations would be stated in the deal confirmation and may extend to five decimal places). We will say that the hedge fund is the payer of the fixed rate and receiver of floating and there are 31 days in the month. The cash flows to be exchanged are therefore: Fixed cash flows 35,000 therms × 70p × 31 = GBP 759,500 Floating cash flows 35,000 therms × 66.56785p × 31 = GBP 722, 261.17 Net payment by the hedge fund is the difference between the two cash flows: GBP 37,238.83. By paying fixed on this transaction, the hedge fund is effectively taking the view that the price of UK natural gas will, on average, be greater than 70 pence per therm. Basis swaps Swaps can also be used to transform the price risk of buying or selling natural gas at a particular location. Take the following US locational basis swap:

Natural Gas

Trade Date: Effective date: Termination date: Notional quantity: Calculation period: Payment date: Floating Amount A: Floating Amount A: Reference price: Specified price: Source: Pricing date: Floating amount B: Floating Amount B: Reference price: Spread: Specified price: Source: Pricing date:

271 16 January 1 October 31 March the following year 4,000 MMBtu per calendar day in each calculation period Each consecutive calendar month, from and including the effective date, to and including the termination date In respect of each calculation period, the fifth business day following the last pricing date in such calculation period Payable by the client NATURAL GAS – Houston Ship Channel (HSC) The index price for spot delivery S&P Global Platts ‘Gas Daily’ The first commodity business day during the calculation period Payable by bank NATURAL GAS – HENRY HUB – CME plus spread Minus USD 0.1500 per MMBtu Settlement price for the calendar month and year corresponding to the calculation period NYMEX The last commodity business day on which the relevant futures contract is scheduled to trade on the exchange

There could be several motivations as to why this transaction could be executed. Basis risk with respect to the natural gas market is where the price in one location moves by a different amount to that elsewhere. This basis risk is often expressed as a spread differential to the NYMEX future, which settles at Henry Hub. Say that natural gas to be delivered for a certain date at the Houston Ship Channel is USD 2.85 MMBtu while the CME futures contract for the same delivery is USD 3.00 MMBtu. The basis differential for HSC would be minus USD 0.15 to the NYMEX futures contract. Since the bank will be less interested in owning the underlying, they may wish to take a view based on how the locational spread may evolve over time. Looking at the direction of the cash flows above, the bank will make a profit if the basis differential falls (‘tightens’). Imagine that the differential moves to NYMEX minus USD 0.10. The bank could take an offsetting position where it receives NYMEX less the USD 0.10 and pays HSC. The net result is that the HSC cash flows cancel out and the bank receives more on the incoming CME cash flow than it has to pay out. If the client has an underlying exposure to natural gas priced at HSC, the swap will allow it to transform the exposure to that of Henry Hub. If the client is selling natural gas, the price it receives will be paid away under the swap and it will be a net receiver of Henry Hub minus USD 0.15.

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Index swaps Another variation of the basis swap is an index swap. Here both swap cash flows are floating but reference different maturities. One cash flow may reference a daily price index, while the other could reference, say, a monthly index. So if a gas market consumer has a physical contract to buy natural gas based on a monthly index, they could enter such a swap where they agree to receive from the counterparty a cash flow based on the monthly index and pay a daily index in return. Their exposure to movements in the monthly index is neutralised and is replaced with a daily index price risk. Swing swaps In physical natural gas supply contracts, it may be possible for the two parties to agree to a ‘swing option’, which is a right to take more or less of some agreed contractual amount. Although these clauses may be somewhat involved in nature, in essence, the ability to take delivery of an increased amount is effectively a call option on natural gas, while the ability to reduce the amount delivered represents a put option. A swing swap will be structured as a fixed-float transaction, but arguably the defining characteristic is the price index to which the floating side of the transaction is referenced. In some natural gas swaps, the floating price may reference a single monthly index, but with a swing option it may reference the average of a series of daily prices. To illustrate the concept, consider the following example, which is based on an idea in Sturm (1997). Suppose that at the start of a particular month, a US natural gas producer agrees to sell all of their production to a consumer in particular region on a fixed price basis of USD 2.00/MMBtu. Several days later market conditions change and prices for this region start to rise. The producer can benefit from this price rise by means of a swing swap. The transaction would work as follows: Physical transaction ▪ Producer delivers the natural gas and receives a fixed price of USD 2.00/MMBtu as per the terms of their commercial contract. Swap transaction ▪ Producer pays a fixed price. Ideally, they would like to pay a fixed price equal to USD 2.00/MMBtu such that it matches the cash flow received from the physical transaction. However, they will pay the prevailing market price, which could be different than this value. ▪ Producer receives a floating cash flow, which is based on an average of daily prices from an agreed source. ▪ If it is assumed that the fixed price on the swap is traded at USD 2.00/MMBtu, then the producer will profit from rising prices via the floating leg.

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Gas formula swap In Section 7.6 it was noted that some natural gas participants paid for their natural gas based on a formula indexed to crude oil. A gas formula swap would involve an exchange of cash flows that would transform the formula into a single fixed price equivalent. Consider the following stylised example, from the perspective of a EUR-denominated natural gas consumer. It is assumed that the consumer is buying their supplies on a gas formula basis. Maturity: Fixed leg payer: Fixed leg: Floating leg payer: Floating leg:

One year Client Fixed price in EUR per kW-h Bank In EUR, [0.5057 + 0.0302 * Brent (6,0,3)] / EURUSD exchange rate (1, −1,1)

The oil linkage is a constant, plus a proportion of the oil price, which is converted into EUR. The value for Brent is the arithmetic average of, say, Dated Brent over the previous six months (the 0 indicates there is no lag) and is applicable for the next three months. The exchange rate is the prior month daily average of the EURUSD exchange rate. The net result is that the cash flow received from the bank finances the purchase of their physical natural gas and on a net basis they end up paying a fixed price in EUR. It may also be possible to increase the complexity of the swap by including additional energy products such as gas oil. Chooser swap Another structure would be for a client to enter into a transaction where they receive, under a swap, a cash flow linked to the price of natural gas less a ‘discount’ (e.g. the NBP price minus 3 pence/therm). In return they would pay one of, say, three different prices: ▪ The ‘day ahead’ NBP price. ▪ NYMEX HH futures price (converted into p/therm). ▪ ICE Brent crude oil price (converted into p/therm). The choice of which energy price paid by the client is made by the structuring entity. This example assumes that the client is buying physical natural gas on an NBP basis and the fixed discounted cash flow receivable under the swap is used to finance this purchase. However, this swap cash flow is reduced by a fixed amount, so it is not a perfect offset to their physical cost. It would imply therefore that the floating swap cash flow they must pay would offer them some benefit, i.e. whatever they are required to pay it will offset the 3 pence discount on the fixed leg. As such, it suggests that the client

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Market price

Market price Client

Purchase of natural gas

Bank Fixed price

FIGURE 7.13 Illustration of cash flow direction for a ‘double down’ swap.

is taking a view on the relative energy prices. The reason the client is able to receive a discount to the NBP price is due to the fact that they have sold optionality to the structuring entity. Rather than receive an explicit cash flow, the fixed price is adjusted downward. Double down swap This type of swap is more aggressive in nature than the previous examples. It allows the client to benefit from an improved swap rate but with an element of conditionality attached. If the monthly price for natural gas is less than or equal to the agreed swap rate the notional for that month doubles. An example term sheet for a consumer of natural gas may look as follows: Fixed rate payer: Floating rate payer: Maturity: Settlement frequency: Fixed price: Floating price: Double down feature:

Client Bank One year Monthly Expressed in natural gas units (e.g. USD/MMBtu or GBP/therm) Daily average of prevailing front month futures contract If the floating price is less than or equal to the fixed price, the notional for that month doubles

The basic outline of the transaction is shown in Figure 7.13. In this example, the fixed rate on the swap would be lower than an equivalent ‘vanilla’ swap. This would reflect that the client has in effect sold a series of monthly options to the bank. If the floating rate declines, the bank would exercise the embedded option for that month in order to receive the fixed amount on twice the notional. This should result in a net cash inflow, as the amount payable on the floating leg will have decreased due to the fall in the price for natural gas.

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7.9.2.3

Option strategies

In terms of option-based strategies, the various vanilla option strategies presented elsewhere could be applied within the natural gas market (i.e. see the chapter on base metals). The following transactions represent ideas that are perhaps more specific to the natural gas market. Swaptions One product that links the swap market to the option market is an option on a swap (a swaption). Some of the terminology for this product can be confusing, but it is common to describe them in terms of either being ‘payer’ or ‘receiver’ transactions. A buyer of a receiver swaption has purchased the right to pay a fixed price (and therefore receive a variable cash flow) in a swap. If the counterparties to the transaction do not wish to enter into the swap at the point of exercise, it is possible to cash settle the transaction at the point of expiry. In this case the terms of the swap agreed under the option are marked to market at the swap rates that prevail at the time of exercise. The resulting net present value of the cash flows is then paid to the counterparty for which the deal has value. The following hypothetical term sheet illustrates a ‘receiver’ swaption: Option contract Option buyer: Option seller: Option style: Option type: Option maturity: Settlement: Premium: Swap contract Swap maturity: Payment frequency: Total Notional amount: Notional per month: Fixed price payer: Fixed price: Floating price payer: Floating reference price: Floating price:

Client Bank European Swaption One month Physical delivery into a swap USD 5 mm One year Monthly for both fixed and floating 4,800,000 MMBtu 400,000 MMBtu Bank USD 2.50 per MMBtu Client Natural gas – Henry Hub – NYMEX Final settlement price on last trading date for NYMEX Henry Hub futures contract corresponding to the calendar month of the swap settlement

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Another popular strategy not yet considered is a corridor, which is comprised of a combination of options. Assume that there is a consumer of natural gas that wishes to buy insurance against a steep rise in price. He can buy a call option with the strike placed out-of-the money and then finance this by the sale of another option. In previous examples such as the ‘min-max’ structure analysed in Chapter 5, the sold option had been of the opposite type (i.e. an OTM put with a strike set to achieve zero premium; Figure 5.8), but in a corridor the sold option is the same type but with a higher strike. Let us assume that the consumer is faced with the following market conditions: Trade date: Effective date: Maturity: Notional amount: Reference price: Current futures price: Pricing date: Premium payment date: Settlement date: Settlement method:

1 March 1 April 30 April 1,750,000 MMBtu Near month NYMEX future (i.e. April) USD 6.74/MMBtu The penultimate business day on which the futures contract is scheduled to trade on the exchange Five business days from trade date Five business days after maturity date Cash settled

Options on North American natural gas can trade with implied volatilities that could range from 40–120%. An OTM European-style call option to cover the period 1–30 April priced with an implied volatility of 50% and a strike of USD 7.00 would cost USD 0.35 per MMBtu. Since the option has been written on a notional of 1,750,000 MMBtu, this would give a premium cost USD 612,500. This could be partly financed with the sale of a call option with a higher strike. The higher strike option will not completely recoup the premium on the purchased option as this could only be achieved if both options had exactly the same strike (a somewhat pointless exercise). Let us assume that the consumer decides to sell an OTM call with the strike set at USD 7.50 – a level he does not believe will trade. For simplicity we will assume that it has been priced at the same level of implied volatility. The premium on the option would be USD 0.20 per MMBtu, to give a total income of USD 350,000. The net cost to the trader is therefore USD 0.15 per MMBtu or USD 262,500 on the entire position. Settlement on the purchased call option will be: Max (0, Underlying price at expiry − strike price) Settlement on the sold call option will follow the same logic except that the seller will face increasing losses as the expiry price rises above the strike price. The effect of the strategy will be that if the underlying price is below the strike of the purchased call the consumer will buy the natural gas at the prevailing market price plus the net premium cost. Between the two strikes the consumer will pay a fixed price equal to the strike of the purchased call plus the net premium cost. Above the strike of the sold call the net purchase price will increase, but still be less than the prevailing

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TABLE 7.3 At expiry payoff of consumer corridor strategy. Underlying price (USD/ MMBtu)

Cost of purchasing the natural gas

Settlement on purchased call option (USD 7.00 strike)

Settlement on sold call option (USD 7.50 strike)

Net premium cost

Net purchase cost of natural gas

5.00 5.50 6.00 6.50 7.00 7.50 8.00 8.50

(5.00) (5.50) (6.00) (6.50) (7.00) (7.50) (8.00) (8.50)

0.00 0.00 0.00 0.00 0.00 0.50 1.00 1.50

0.00 0.00 0.00 0.00 0.00 0.00 (0.50) (1.00)

(0.15) (0.15) (0.15) (0.15) (0.15) (0.15) (0.15) (0.15)

(5.15) (5.65) (6.15) (6.65) (7.15) (7.15) (7.65) (8.15)

underlying price. This is shown in Table 7.3, which analyses the ‘at expiry’ situation for the consumer, assuming both options are cash settled. We will assume that the consumer has agreed to buy the natural gas based on the same price at which the option will be settled. Bermudan option A Bermudan-style option allows the buyer to exercise on a pre-agreed number of dates. Consider the following example: an industrial consumer of natural gas buys a fixed volume every month except for one month where they must close the plant for routine maintenance. However, at the start of the year the exact date of the closure is unknown. Under the terms of their normal commercial supply contract, they will buy natural gas every month based on a daily averaging process. To hedge this price exposure, they have been using cash-settled swaps, structured such that an offsetting floating payment is received by the client who, in return, pays a fixed amount. During the closure of the plant they will not have any underlying commitment to buy the physical natural gas but will still be required to settle the swap. If the underlying price of natural gas has fallen, they will have a net settlement liability on the swap. On the other hand, a rise in natural gas prices will result in a net cash inflow. To hedge against a potential fall in prices, the consumer buys a Bermudan put option. Once the closure dates are known, the option can be exercised if needed. The payout on the Bermuda put option can be structured to be Asian-style to match the swap and the underlying commercial contract: Max (Strike − Average of Spot, 0) The option strike could be set equal to the fixed rate on the swap and the cost of the option could be built into the swap’s fixed price so the client is not faced with an upfront premium cash flow. Since they are buying the option, the fixed rate payable on the underlying swap will be higher than a vanilla equivalent. If the price of natural gas

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falls then they will pay on the swap but will exercise the option and receive a compensating payout. If the price of natural gas increases, then they will receive on the swap and allow the option to lapse. Spread options A spread option is an option that pays off based on the difference between the prices of two underlying assets, relative to a pre-agreed strike. A call option will pay off if the spread is greater than the strike, while a put option will pay off if the spread is lower than the strike. Call payoff = Max (Price of asset 1 − price of asset 2 − strike, 0) Put payoff = Max (Strike − price of asset 1 + price of asset 2, 0) There are several possible ways in which spread options could be applied within natural gas markets: ▪ Some LNG contracts may reference traded natural gas prices with the possibility that a particular cargo could be linked to the higher of the US Henry Hub future or UK NBP price. Suppose a producer has negotiated such a clause into an LNG agreement. This is a form of optionality, which could be ‘monetised’ by trading an offsetting financial contract. The producer could sell a call on the spread between the two gas prices structured as MAX (NBP – HH – strike, 0), priced in equivalent terms (e.g. pence per therm). If the price of NBP rose relative to HH resulting in an ITM option at maturity, they would be required to make payment to the call buyer. However, under the terms of the physical contract they would receive the higher NBP price, which could offset the losses. In addition, their income will have increased, as they will have received the option premium. ▪ Suppose a producer of a commodity such as chlorine operates a gas-fired power plant. If they faced competition from other producers in another location, their competitive position may be harmed if the price of gas in their domestic location increases relative to the overseas price. An option on the spread between the two prices would help manage this risk. ▪ A producer of natural gas may have gas stored at different geographical locations (e.g. UK and Holland). If they are concerned about an adverse change in the relative prices of the natural gas, then it may be possible to structure a spread option between the two. ▪ Spread options could also be used to express views on transport and storage. Different locations will have different gas prices; therefore a spread option between the prices at two different locations could be a view on transportation costs given that the underlying commodity is homogeneous. ▪ Options on gas oil storage were examined in Chapter 6. Storage costs could be thought of, therefore, as an option on gas prices at two different points in time.

Natural Gas

7.9.2.4

279

LNG derivatives

The pricing of physical LNG contracts was considered in Section 7.6.3.2. In some respects, derivatives for this segment of the market will be similar in nature to those of ‘regular’ natural gas. Where the physical LNG contract is referenced to oil prices then some form of oil-linked derivative could be used to hedge the resultant exposure. With the US now a major exporter of natural gas, pricing physical contracts referencing the Henry Hub futures price has grown in popularity, which therefore provides producers and consumers with a benchmark index that can be used to hedge the resultant price exposure. A trader who buys LNG in the US referencing Henry Hub prices may then decide to sell it in either Europe (at NBP or TTF prices) or Asia (referencing JKM prices) and so will have an exposure to the spread between the two prices. They will be able to make a profit as long as the cost of transporting the gas between the two locations is less than the differential between the prices. This is another example of spread exposure considered earlier in this section. Another popular ‘view driven’ transaction is to trade the spread between JKM and TTF (or HH) using either futures or options.

CHAPTER

8

Electricity

‘One of the biggest surges in the electricity in the UK occurred at the end of an international soccer match in 1990 when England lost to Germany. Demand soared by 2,800 megawatts, which was equivalent to more than a million kettles being switched on as the English drowned their sorrows with the answer to all the world’s problems – a cup of tea’. —UK National Grid

8.1

WHAT IS ELECTRICITY?

All matter is made up of atoms, the core of which is called a nucleus. This nucleus is made up of protons and neutrons and is surrounded by electrons. If electrons move from one atom to another, a current of electricity is created. In its raw form, electricity is useless to our daily needs. It is nearly always converted into a different kind of energy at its end point of consumption. It is converted into heat to cook food or boil water or into light and sound energy in order to watch TV or listen to the radio. Electricity is made by converting different forms of energy. Not much electricity exists naturally in the environment and it is nigh on impossible to capture or store. On Earth, there are many forms of stored energy, mainly in the form of plants and fossil fuels, which can be converted into electrical energy. It is also possible to convert movement energy from wind and waves and light energy into electrical energy. Changing one form of energy into another is termed ‘transformation’, while moving energy from one location to another is called energy transfer. The following flow diagram (Figure 8.1) summarises the path of energy from source to useful form.

280

281

Electricity

Energy source (fuel, wind, waves, solar)

Transfer

Power station

Transformation

Electrical energy

Transfer

Homes, factories, hospitals

Transformation

Heat, light, sound, movement

FIGURE 8.1 Energy transfer and transformation: the path or energy from source to useful form.

8.1.1

Conversion of energy sources to electricity

Fuels Inputs such as fossil fuels or nuclear fuel are used to boil water. The resulting steam is used to drive a turbine, which in turn drives a generator, which produces the electricity. The generator works by ‘electromagnetic induction’. This is the rotation of a wire within a magnetic field, which induces an electric current. An old-fashioned bicycle dynamo works in much the same way as it transforms movement energy into electrical energy, which is then transferred to the bulb and transformed into light energy. Solar energy Heat energy is absorbed by solar panels and then used to heat water into steam. The steam is then used to drive a turbine which produces electricity in a similar way to above. Wind, wave, hydro electric, and tidal energy Movement energy is used directly to drive a generator. In this case there is no need to boil water to turn a turbine.

8.1.2

Primary sources of energy

Electricity is sometimes referred to as a secondary source of energy as it must be created from some primary source. The primary fuel sources used in electricity generation include: ▪ ▪ ▪ ▪ ▪ ▪ ▪

Natural gas and liquefied natural gas. Nuclear power. Coal. Oil. Water. Wind. Solar.

The choice of fuel will be dependent on how efficiently it generates electricity, the cost of the fuel itself, and any waste products that may result from the process. The main fuels used in electricity generation in the USA and UK are shown in Table 8.1, with the figures used in the first edition of this text by way of comparison.

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TABLE 8.1 Fuels used in electricity generation. Fuel source Natural gas Coal Nuclear Petroleum Renewables Other fuel sources

USA (2003)

USA (2018)

UK (2004)

UK (2016)

16% 51% 20% 3% 7% 2%

35% 27% 19% 1% 17% 1%

40% 33% 19% 1% 1% 3.5%

42% 9% 21% 1% 25% 3%

Source: EIA, Digest of UK Energy statistics; figures may not add up to 100% due to rounding differences.

The UK remains heavily reliant on natural gas as the primary source of fuel while coal’s contribution to the energy mix has declined. The use of renewable energy has increased significantly. US production is no longer dominated by coal and this could be explained by the increased availability and relative cost effectiveness of ‘shale gas’. One of the reasons why natural gas is a popular primary fuel is that it has a relatively high thermal efficiency. Thermal efficiency relates the electrical energy produced to the energy content of the input as in every step of electricity generation some energy is lost. Burning fuel to boil water is particularly inefficient since a lot of energy is lost in the form of heat. Take for example a fossil fuel fired power station, where a common sight is the enormous clouds emerging from their towers. This is mainly steam taking energy in the form of heat being released into the atmosphere. For example, in a combined-cycle natural gas power station, the thermal efficiency reaches about 47%. This means for every 100 units of natural gas used as a fuel source, only 47 units are converted to usable electrical energy. The least thermally efficient energy sources are coal (about 36%) and then nuclear power (about 38%). There are some significant regional differences in the selection of the primary fuel source. In Norway production of electricity is nearly 100% hydropower-based. In years where there is excess rainfall the country can supply its surrounding neighbours (Sweden, Denmark, and Finland) with a cheap source of electricity. However, when the reservoirs are low, Norway will import electricity from its neighbours who are more reliant on conventional primary fuel sources.

8.1.3

Commercial production of electricity

Although the general principles of electricity generation are universal, the actual design of power stations varies. Three possible generation methods are: ▪ Combined Heat and Power (CHP), ▪ Combined Cycle Gas Turbine (CCGT), ▪ Open Cycle Gas Turbine (OCGT). A CHP power station is one that typically uses natural gas to produce electricity but also allows the steam and hot water that is produced at the same time to be captured for other uses. A CCGT is an energy efficient gas turbine system where initially one turbine

Electricity

283

generates electricity from the gas produced during the combustion of the primary fuel source. The hot gases are then passed through a boiler and the steam that is produced drives a second turbine that generates electricity. An OCGT generates electricity from gas produced during fuel combustion. This method of generation is not regarded as being particularly efficient but OCGT plants can increase their load very quickly and, hence, tend to be used as a reserve to respond to sharp increases in demand.

8.1.4

Measuring electricity

Consumption of electricity is measured in two ways. When reference is made to electrical power, the unit of measurement is a watt. Since a watt is a relatively small amount of power it is more common to express it as a kilowatt (1,000 watts) or a megawatt (1 million watts). The higher the watt or kilowatt rating of a particular electrical device the more electricity it requires. If an electric light bulb is rated at 100 watts, it is describing an instantaneous quantity; it is consuming at any split second 100 watts. However, a consumer of electricity will not want to use electricity over a split second but over a period, which means the quantity has to be expressed as a rate. The amount of electricity generated or used over a period of time is measured in watt-hours (Wh). This is determined by multiplying the number of watts used or generated by the number of hours. For example, ten 100-watt light bulbs burning for one hour would consume 1,000 Wh. When divided by 1,000 this is equal to one kilowatt hour (1 kWh) of electric energy. To put this in some context the EIA estimates that the US residential sector used a total of 1,462 billion kWh in 2018, with space cooling and heating accounting for the most significant amounts (214 and 217 billion kWh respectively). If someone wanted to have access to a generation resource, they might decide to buy a power station with a capacity of 100 MW. However, if they wanted to use this amount of electricity for one hour, they would buy 100 MWh. Other measurements of electrical energy in ascending order are: ▪ Megawatt hours (MWh – a thousand kWh), ▪ Gigawatt hours (GWh – a thousand MWh), ▪ Terrawatt hours (TWh – a thousand GWh). Another unit of measurement is the volt, which measures the force being used to push electrons around a circuit. Technically this force is called potential, which is measured using the volt. Potential can be thought of as the steepness of a hill that electrons run down. The steeper the hill (i.e. the higher the current), the faster they roll.

8.2

THE PHYSICAL SUPPLY CHAIN

Just like natural gas, regulation has played a major role in shaping markets in each geographical location. A number of electricity markets have undergone substantial deregulation followed by re-regulation. Issues of competition largely drove the original restructuring of the electricity industry; however, since the first edition of this text the consequences of climate change are now having a greater impact on the structure

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of the industry. A common theme in the original process of deregulation was the unbundling of the different functions that exist along the supply chain that were traditionally performed by a single fully integrated utility. In the UK, which is regarded as one of the most deregulated markets in the world, the result is that there is significant competition in the generation and supply of electricity, but not in its transmission and distribution. The physical supply chain for electricity can be broken down into a number of different components: ▪ ▪ ▪ ▪ ▪

The production of electricity (generation), The transport of electricity on high voltage lines (transmission), Transportation on low voltage lines (distribution), The marketing of electricity to final consumers (supply), The buying and selling of electricity on wholesale markets.

The following descriptions outline the key functions of the main participants in the physical supply chain of electricity. Electricity generators – these will be the companies who build and run power stations that produce electricity. There may be a mixture of producers of different size and varying degrees of integration. Some producers may operate a portfolio of different plants in different locations using different fuels and technology. At the other end of the spectrum there may be independent power producers who do not have any transmission capabilities and do not sell on to the retail market. They may operate within a defined area supplying electricity to wholesale buyers. The transmission system operator (TSO) – having produced the electricity, it has to be transmitted to the end user, usually by means of high voltage wires mounted on overhead pylons. Transmission lines link the generators to the distributors. The network of transmission lines is referred to collectively as the ‘grid’ with the TSO usually being responsible for ensuring its efficient and reliable operation. Typically, the TSO will: ▪ Coordinate and schedule transmission transactions. ▪ Ensure that the demand for and the supply of electricity are balanced on an ongoing basis. Since electricity cannot be stored, demand and supply must balance instantaneously, or the lights will go out. ▪ Manage generation in system emergencies. ▪ Manage generation reserves. ▪ Ensure that new transmission facilities are built when and where they are required. ▪ Coordinate transmission payments. It is worth noting that TSO responsibilities vary by jurisdiction. In the UK, National Grid owns the physical transmission network, but National Grid Electricity System Operator (a separate legal entity) ensures that demand and supply are balanced in real time. Electricity distribution businesses – electricity cannot be delivered into a home directly from the high voltage network so a series of substations transfer the electricity

Electricity

285

onto a lower voltage local network before its final delivery. These businesses may sometimes be referred to as Distribution System Operators (DSO). Suppliers – these are the companies that sell and bill customers for the electricity that they use. They will make use of the distribution networks to supply energy to the end consumer. In some cases, wholesale customers who have a significant demand may agree on a supply contract directly with the producer. End customers – they can be either domestic users or large and small business customers. Each of the participants in the supply chain will want to be compensated for the service they provide and for the UK, the final price paid by the domestic consumer is made up of: ▪ ▪ ▪ ▪ ▪ ▪ ▪

Wholesale costs (buying the energy in the wholesale market) – 32.32%, Network costs (costs of delivering the energy to a home) – 23.15%, Operating costs (billing, customer services, IT systems) – 17.34%, Government environmental and social obligation costs – 20.44%, Value added tax – 4.76%, Supplier pre-tax margin – 0.73%, Other direct costs – 1.25%.

Although this description of the supply chain is still valid, changes in technology and climate change have impacted this structure. It is not the purpose of this book to speculate on how the industry may evolve, but it is important to appreciate that the structure is changing all of the time. For example, the production of electricity is now impacted by the increased use of renewable sources such as solar and wind power. Improved battery storage technology, homes fitted with ‘smart’ technology, the increased use of domestic solar panels, and electric vehicles are reshaping the way the industry will supply an end consumer.

8.3

MARKET STRUCTURE AND REGULATION

At a very high level two main electricity market structures have evolved: electricity pools and bilateral markets. However, this is a simplified way of catergorising the different structures and some markets may well not be fully described using these terms. Electricity pools Pools are sometimes characterised as being a centralised market, where competition between generators is encouraged to achieve a fair price for buyers. In a compulsory pool all of the generators will sell their output at a single price. In an auction-like process, typically overseen by a system operator, the generators submit how much they are willing to generate and at what cost. The system operator will then ‘dispatch’ the required energy either based on forecasted or actual demand. In the auction-based process, prices are set for a single generation period and the price from period to period may differ significantly. For example, if generating capacity

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is suddenly lost, there could be a substantial increase in price until sufficient reserve capacity can be brought online. Those entities supplying end customers indicate how much energy they require and how much they are willing to pay; generators indicate what they are willing to supply and the price they will charge. The auction process sets the price for any period as the highest generating price submitted, such that all demand is satisfied. The following is a simplified example of how such a system operates. Assume that in one single period of generation the demand to receive electricity is 1,000 MW, and there are four generators (I to IV). Each of the generators has the capacity to provide 250 MW but the prices at which they are willing to supply differ due to the type of fuel used in the generation process. The prices offered by the generators are: ▪ ▪ ▪ ▪

Generator I: USD 60.00 Generator II: USD 65.00 Generator III: USD 70.00 Generator IV:USD 75.00

In this case, supply and demand is matched in terms of volume, and the clearing price (sometimes referred to as the system marginal price) for this period is USD 75.00. This is the highest accepted price from all available generators such that demand is equal to supply. All of the generators are paid this amount irrespective of how much they bid in the auction process; this single price is also paid by those demanding the electricity. In this example, all of the producers are ‘in merit’ as they will all generate electricity. Had the demand for electricity been only 750 MW then generator IV would not produce and would be deemed ‘out of merit’. The clearing price in that case would be USD 70.00 set by generator III. Bilateral markets This structure requires both sellers and buyers to enter bilateral contracts for the sale of electricity. This is the dominant model in the United Kingdom and a simplified illustration of this structure is shown in Figure 8.2. It is also possible for bilateral supply contracts to exist between generators (see Figure 8.2) where one of the participants is unable to supply a contracted amount of electricity. Once the transaction has been agreed, the participants must notify the system operator by a specified time as to the net amount that will be bought or sold for a given generation period. Unlike the pool system, it is now the seller of electricity who will have to dispatch (i.e. generate) the agreed electricity based on the details outlined in the bilateral contract. The system operator will then be required to ensure that the system is always in balance and will have available specific tools that will allow them to adjust the system accordingly. Figure 8.2 also highlights the existence of organised exchanges. These will allow participants to: ▪ Buy and sell physical electricity to balance demand and supply. ▪ Trade derivatives to manage the associated price risk. Exchanges are considered in more detail in Section 8.5.

287

Electricity

PRODUCERS

Energy Source

PRODUCERS

TRANSMISSION

DISTRIBUTION

RETAIL CONSUMERS INDUSTRIAL CONSUMERS

BANKS, TRADING HOUSES, BROKERS, HEDGE FUNDS

SUPPLIERS

EXCHANGES Flow of energy Commercial supply contracts Ad hoc physical supplies and / or risk management

FIGURE 8.2 Structure of bilateral electricity market. Source: Author

8.3.1

The European Experience

Within the European Union it is important to distinguish between a regulation and a directive. A regulation must be applied in its entirety within domestic law across the European Union. A directive outlines a goal that all EU countries must achieve but it is up to the individual countries to devise their own laws to achieve the objectives. Within Europe, deregulation of the market began with the First Electricity Directive of 1996, which removed legal monopolies by allowing large electricity customers the ability to choose their source of supply. It also set out the principles, whereby vertically integrated companies were required to allow third parties access to their transmission and distribution networks. It also started the process of unbundling (i.e. legal separation) of the activities performed by these vertically integrated companies. In effect, it introduced a distinction between the regulated part of the market (i.e. the network operations) and the competitive elements (generation and supply). Subsequent Electricity Directives and Regulations (2003 and 2009) developed many of the themes of the earlier legislation. The overarching goal of EU legislation is based on a ‘target design model’ aimed at creating interconnected European markets with convergent prices. At the time of writing, the aims of EU electricity regulation are to: ▪ Allow free movement of electricity throughout the EU market by means of cross border trade. ▪ Increase competition and cooperation. ▪ Encourage the use of renewable energy to decarbonise the EU energy system. ▪ Improve consumer protection, information, and empowerment. ▪ Enhance the role of ACER (Agency for the Cooperation of Energy Regulators). ACER was officially launched in 2011 because of the Third EU Energy Directive, and its remit extends to both electricity and natural gas.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Although it would be possible to fill an entire textbook on this subject, another European trading regulation worthy of note is REMIT (Regulation of Energy Market Integrity and Transparency). The regulation: ▪ Defines market abuse (e.g. market manipulation or insider trading). ▪ Prohibits market abuse. ▪ Requires effective and timely public disclosure of inside information by market participants. ▪ Obliges participants to report suspicious transactions.

8.3.2

Overview of UK regulation

In March 2001, the New Electricity Trading Arrangements (NETA but pronounced as ‘neeta’) were introduced. NETA was designed to ensure that those entities wishing to buy or sell electricity should be able to freely negotiate bi- or multilateral contracts either on an OTC basis or on a recognised exchange. NETA included provisions for: ▪ A mechanism that allows for the balancing of demand and supply by the transmission system operator. ▪ Delivery of electricity to a single notional point avoiding the need for a multitude of different delivery locations (the National Balancing Point). ▪ The development of short-term power exchanges that will allow market participants to fine tune their demand and supply requirements. For example, EPEX Spot allows members to manage their within-day balancing requirements. ▪ OTC derivative markets that allow participants to hedge the exposures of varying maturities. ▪ A settlement process to charge those entities that have not delivered or received their contracted power. In 2005, NETA was expanded to include Scotland and was renamed BETTA (British Electricity Trading and Transmission Arrangements).

8.3.3

The American Experience

Although it is possible to generalise about the structure of an electricity supply chain, the USA power industry has fragmented into several different markets with no single overarching structure. In some areas of the USA, there are open, competitive, wholesale, and retail markets while in others, a more regulated framework exists. The supply of electricity in the USA has traditionally come from one of three sources: ▪ Utility companies that may be owned by shareholders or the local municipality. The utilities have responsibility for a specific geographical area and would typically operate along all parts of the physical supply chain. Historically they may also have supplied other household services such as natural gas, water, and telecommunications. If the entity is a municipal utility, one or more local governments may run it depending on the area that it serves. Although utilities still exist in a deregulated market, it is more likely that they will only be involved in one particular element, such as retail distribution.

Electricity

289

▪ Rural co-ops set up to provide electricity to remote locations. This type of company is owned by the customers it serves. ▪ Federally owned power agencies that may have been established to sell power that is generated from infrastructure projects paid for by the government (e.g. hydro-related). One example is the Tennessee Valley Authority, which was set-up in 1933 to help the region develop during the Great Depression. One of its original responsibilities was to provide electricity to homes and businesses in the region. The overall direction for the electricity industry is determined by the passage of federal law. The Federal Energy Regulatory Commission (FERC) regulates the industry at the wholesale level. Regulation at the state level encompasses areas such as vertically integrated utilities and competition in the retail sector. Municipal utilities will either be regulated at state or local government level, while electricity co-ops are regulated by their own elected boards. FERC’s main areas of responsibility include the activities of Independent System Operators (ISOs) and Regional Transmission Organisations (RTOs), some aspects of generation, and the wholesale trading of power. ISOs and RTOs are responsible for controlling, managing, and operating the bulk electric transmission grid. At the time of writing there are seven ISOs/RTOs: ▪ ▪ ▪ ▪ ▪ ▪ ▪

California. ERCOT (Electric Reliability Council of Texas). Midcontinent. New England. New York. PJM. South West Power Pool.

North American Electric Reliability Corporation (NERC) The Energy Policy Act of 2005 called for the establishment of an Electric Reliability Organisation and a year later the designation was awarded to NERC, which was originally established in 1968 as a response to a serious blackout a few years earlier. NERC is responsible for ensuring the reliability, security, and adequacy of the bulk power system in the USA, Canada, and parts of Mexico. Their coverage includes the high voltage transmission system but does not extend to the distribution system that delivers electricity into the home. NERC defines reliability in terms of: ▪ Adequacy – the ability of the system to always supply the aggregate demand requirements of the end users. ▪ Reliability – the ability of the system to withstand sudden disturbances. In recent times this has expanded to include the security of the system from physical or cyber attacks.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

NERC is responsible for designing reliability standards for all the US markets but delegates some of its compliance activities to a series of partners known as regional reliability councils, which are in turn made up of members from each segment of the electricity industry. The regional reliability councils are: ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪

Western Electricity Coordinating Council (WECC). Midwest Reliability Organization (MRO). Southwest Power Pool (SPP). Electricity Reliability Council of Texas Inc. (ERCOT). Northeast Power Coordinating Council (NPCC). Reliability First Corporation (RFC). Southeastern Electric Reliability Council (SERC). Florida Reliability Coordinating Council (FRCC).

One of the consequences of having several different regulatory bodies is that it creates a complex set of rules and regulations.

8.3.4

Wholesale markets in the USA

Perhaps due to the way that the US market was deregulated and re-regulated a patch work of different markets has subsequently evolved. The US federal government has the power to oversee interstate markets, but individual states oversee the utilities that serve retail customers. So, because federal regulators did not dictate the structure for all power markets, they preferred instead to provide broad guidelines, so each region was free to structure its own market. Although the US markets have evolved at different rates throughout the country, once the traditional model of a single entity operating along the entire supply chain is subject to deregulation, the development of independently owned generation emerges to provide the incumbent utility, which at this stage of reform is the single buyer of power, with more competition. Typically, the next stage of development in the market allows large consumers to choose their source of supply. This gives rise to an Independent System Operator (ISO) that manages the transmission of power over a given area. As competition increases, electric marketers emerge, buying and selling electricity between wholesale participants. The final stage of development occurs when the retail buyer is free to choose their supply of electricity. As an illustration of how deregulation has impacted the US market, according to the EIA’s website, in 2017 electricity sales were made by four major types of entity: ▪ Investor-owned utilities: 51%. ▪ Power marketers: 22% (e.g. entities that may not own generating facilities such as financial intermediaries but can buy and sell electricity). ▪ Federal, state, and local utilities: 14%. ▪ Electric cooperatives: 11%. ▪ Other: 2%.

Electricity

8.4

291

PRICE DRIVERS OF ELECTRICITY

Introduction Electricity must be produced when it is demanded. As a result, the spot price for electricity is very dependent on its physical infrastructure. If there are problems with physical delivery such as transmission constraints this could lead to volatile prices. However, since it is impossible to store electricity, a high price today does not mean a high price tomorrow. If demand exceeds supply of electricity, then the lights will go out (a blackout). However, there may be instances where they may be a momentary excess of demand over supply, which may cause the lights to dim or flicker. This is referred to as a brownout. The four main users of electricity are: ▪ ▪ ▪ ▪

Domestic (e.g. lighting and appliances), Industrial (e.g. manufacturing), Commercial (e.g. office buildings), Transportation (e.g. railways).

Electricity markets are essentially local markets given the fact that generation and supply is generally limited to a certain geographical location. However, the markets are subject to global influences as the primary fuel sources may need to be imported and the cost of carbon emissions needs to be considered. Load Demand for electricity is related to the concept of load, which is defined as the amount of power carried by a system or the amount of power consumed by an electrical device at a specified time. This demand will vary considerably according to the time of day, the day of the week, the season of the year and the climate. Generators will therefore create a load profile or load shape that describes the pattern of electricity demand over a given period. Generating companies may operate different types of power stations according to different types of demand or load. A baseload-generating unit is used to generate power at a flat rate around the clock. Baseload is the minimum amount of electric power delivered or required over a period at a steady state. A peak load generating unit is used to meet the requirement during periods of greatest demand on the system. Intermediate load generating units meet systems requirements that are greater than baseloads but less than peak loads. When constructing load curves, (a representation of demand in a particular generation period) account must be taken of: ▪ The type of end user (e.g. residential, commercial, and industrial) and how they use electricity. ▪ The time of day.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

▪ Time of year. ▪ Geographic region. For example, in the USA, the demand for electricity peaks in the summer except for the northern states and Florida. Demand and supply – an overview Figure 8.3 shows the global generation of electricity over the period 1985–2019. Perhaps somewhat unsurprisingly, overall generation has more than doubled in the period. Although generation in regions such as the USA and Europe has continued to increase, the most noticeable change is the Asia Pacific region, dominated by the growth in generation in China. In 1985, the country generated 411 TWh and by 2019 this had risen to 7,503 TWh. Even between the publication of the first and second editions of this book (about 11 years) Chinese electricity generation has increased by about 300%. Since electricity is a secondary source of power, it is instructive to look at the different sources of primary fuel used to generate electricity. Figure 8.4 analyses the main geographical regions and looks at their reliance on primary fuels in relative percentage terms. Some key themes emerge: ▪ Coal still plays an important role in power generation, especially in Asia Pacific. ▪ A relatively large proportion of electricity in Central and South America is generated by hydro. ▪ Regions with large supplies of natural gas such as North America, the CIS, and the Middle East use this commodity as their primary fuel input. ▪ Despite the current development of renewable technology, the application within the power markets is still limited, with Europe being a leader in relative terms.

30,000

25,000

Africa Middle East S & C America CIS

20,000 Europe 15,000

N America

10,000 Asia Pacific 5,000

19 8 19 5 8 19 6 8 19 7 8 19 8 8 19 9 9 19 0 9 19 1 9 19 2 9 19 3 9 19 4 9 19 5 9 19 6 9 19 7 9 19 8 9 20 9 00 20 0 20 1 0 20 2 03 20 0 20 4 0 20 5 0 20 6 0 20 7 0 20 8 09 20 1 20 0 1 20 1 1 20 2 1 20 3 1 20 4 1 20 5 16 20 17

0

FIGURE 8.3 Global electricity generation (Terawatt-hours) 1985–2019. Source: BP Statistical Review of World Energy 2020. BP PLC.

293

Electricity 100% 90% 80% 70%

Other Renewables Hydro electric Nuclear energy Coal Natural Gas Oil

60% 50% 40% 30% 20% 10% 0% North America

S. & Cent. America

Europe

CIS

Middle East

Africa

Asia Pacific

FIGURE 8.4 Global electricity generation by fuel type (2019). Source: BP Statistical Review of World Energy 2020. BP PLC.

100% Imports, 4.30%

90%

Imports, 7.22% Gas, 26%

80%

Gas, 42.05%

70% 60% 50%

Coal, 43%

Hydro, 1.31% Solar, 4.08%

40%

Wind, 17.08%

30% 20% 10% 0%

Coal, 2.18%

Hydro, 1% Solar, 0.40% Wind, 3.90% Biomass, 0.70% Nuclear, 20.70%

2012

Biomass, 6.63% Nuclear, 19.44%

2019

FIGURE 8.5 Fuels used in the production of electricity in the UK. 2012 vs. 2019. Source: http://www.mygridgb.co.uk/historicaldata/

Figure 8.5 looks at how the mix of fuels used in the production of electricity in the UK has evolved over the period 2012–2019. Some of the key points are: ▪ The reliance on coal has decreased dramatically. ▪ The use of natural gas has increased. ▪ There is a greater reliance on ‘renewable’ energy sources such as biomass, wind, and solar.

294 8.4.1

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Demand for electricity

Economic activity Like crude oil, an increase in economic activity will tend to lead to an increase in the use of electricity. Weather Using the USA as an example, seasonal demand for electricity will increase during the summer as more households switch on their air conditioning units. Elements of weather that affect the demand for electricity will include the absolute temperature, the level of humidity, the amount of cloud cover, and expected rainfall. Some analysts will refer to Heating or Cooling Degree Days. Heating Degree Days (HDD) are defined relative to the outdoor temperature and what is a comfortable room temperature (e.g. 21∘ C or 70∘ F). The colder the weather, the higher is the number of HDDs as it suggests a greater energy demand to heat a building. Cooling Degree Days (CDD) work in the opposite direction; when the weather is warmer (i.e. above 21∘ C/70∘ F) then the number of CDDs is positive. Human activity The time of day will determine if the demand for power is heavy or light. Normal working hours are typically defined as peak time while off peak covers evenings, nights, and early mornings. In the same vein, the day of the week will also impact demand. When buying or selling power, weekends can be traded separately and may be classified as a lower usage period. Extending the argument further, power can be traded in ‘blocks’ of months to represent the different seasons, which in the electricity market are broadly defined as winter (October–March) and summer (April–September). End user Suppliers will also differentiate between retail and industrial customers. Typically, retail customers will be greater users of electricity at the weekend while industrial users will represent the greatest source of demand during the week. Special Events There may also be odd events that will cause a sudden surge. For example, in the UK the system operator must deal with what they refer to as ‘TV pick up’. This a short but sometimes dramatic increase in demand that occurs at the end of certain TV programmes such as soap operas and sporting events. In their preparation for major sporting events, the demand forecasters will collect a lot of information to develop an accurate picture of demand. This included the timing of the match and whether it would coincide with sunset, if extra time were a possibility, and what alternative TV options would be scheduled for after the match.

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Efficiency improvements As technology improves, several household appliances have improved in terms of their efficiency of consumption, leading to a decrease in their use of electricity. Electric Vehicles At the time of writing, the impact on the electricity market of an increase in demand for electric vehicles (EV) is not clear. One argument is that demand for EVs will significantly increase when the economics of owning the vehicle are superior to the traditional internal combustion engine. One part of this issue is the creation of the appropriate recharging infrastructure, which represents a significant investment. One useful model of assessing the impact of EVs on the electricity system is suggested by Massey (2018). Number of EVs × EV usage (e.g. kilometres driven) × EV efficiency (kWh∕km) = electricity used (kWh) + grid losses of 7–8% (getting the energy from production to consumption) = required electricity generation in kWh The use of EV poses a number of questions and challenges to the system such as whether the system would be able to cope with a large number of people returning home from work and immediately charging their cars during traditional peak load periods. It may require the introduction of ‘managed’ charging where EV owners may have to charge their vehicle during the night when demand is normally lower.

8.4.2

Supply of electricity

Physical capacity There are several different factors that could be included in this category: ▪ The type of available generation (i.e. coal or natural gas), which will determine the cost of generation and have an influence on the price paid for electricity in any period. ▪ The operating ‘health’ of available generation, which might be reflected in the amount of required maintenance on plants or outright mechanical failure. ▪ Limits on the physical capacity of electricity transmission that could restrict the amount of power imported into or exported from a particular geographic region.

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One relationship that many traders will monitor is the way in which the reserve margin of a particular market changes. This is defined as the actual amount of available generation capacity relative to peak demand and is normally expressed as a percentage. For example, in the USA, FERC (Federal Energy Regulatory Commission) suggests that capacity margins should on average be in the region of 15–17%. There is an inverse relationship between the reserve margin and the wholesale price of electricity. Interconnections The term can be used to refer to individual transmission lines that link different markets in one geographical location (e.g. the USA) or more commonly to the overall capacity provided by the various lines (sometimes undersea cables) that run between two countries. The UK has interconnectors with France, Netherlands, Northern Ireland, and the Republic of Ireland. In theory a difference in price between the two countries should result in power being directed to the highest price location. The UK-France interconnector is approximately 70 km in length with 45 km of cable underwater. The capacity of such interconnectors affects the ability of the country or region to import and export electricity. Fuel prices Like all traded products, the balance between supply and demand will determine the market price. However, it could be argued that in the short-term, demand for electricity is somewhat inelastic in its response to changes in price. For example, a domestic user will switch on a light without much consideration for the actual cost. So if the short-term price were to increase significantly for one generating period, it is unlikely that this would have a material effect on the end user as most domestic and a significant proportion of industrial and commercial consumption is based on tariffs that do not change rapidly. As a result, it is the activities of the generating companies that determine the short-term price for electricity. Suppliers seeking to buy electricity will seek out the lowest cost source of generation such as wind and hydro. Once generation capacity in this sector is reached, buyers will then purchase their supplies from the next cheapest source, which will typically be nuclear powered. After this, electricity will be provided by installations using either coal or natural gas as their primary fuel input. Consequently, the price of electricity will be driven by the price of the fuel used at the point where demand equals supply; the so-called ‘marginal fuel’. Typically coal and gas generators are the marginal sources of electricity generation, therefore the demand and supply dynamics of these markets will have a significant impact on the market price for electricity. In addition, and depending on which market is being analysed, the cost of emitting carbon may also influence the price of electricity. ▪ Electricity and natural gas – An increase in the price of electricity should lead to an increase in the price of natural gas. However, the same relationship may not hold the other way around. At any point in time, generation capacity that uses the

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cheapest marginal fuel will be running near capacity. However, demand is unlikely to be met by generation powered by a single fuel source, and so the more efficient plants that use the alternate marginal fuel will be switched on. It will be the price of the fuel input used by these generators that will determine the market price of electricity. If natural gas prices are low relative to coal, installations using this fuel input will always be on. To supply the marginal demand, coal-fired installations will be used. If the price of gas rises but is still below coal, the increase is unlikely to have an impact on the price of electricity. Conversely if gas is more expensive than coal, a rise in its price will have a greater impact on the price of electricity. ▪ Electricity and coal – The effect of coal on the price of electricity may be country specific. For a country that imports coal from overseas, a rise in the price of electricity is unlikely to have a significant impact on its price since it is being purchased in a global market subject to a multitude of different price drivers. Like natural gas, the impact of an increase in the price of coal will depend on whether it is the marginal fuel. If it is the marginal fuel, then an increase in the price of coal will lead to an increase in the price of electricity. However, if coal is comparatively cheap compared to natural gas then an increase in the price of coal will have a weaker effect on the price of electricity. There is also a positive correlation between coal and natural gas in that a rise in coal prices will cause generators to demand more natural gas, pushing up its price. Electricity and renewable sources of energy Typically, natural gas is the main source of energy used to produce electricity. One of the UK regulators, Ofgem reported that in 2018 that although 32.8% of generation used natural gas, wind power and solar made up 17.5% (2019). Participants’ bidding behaviour In markets where electricity is priced using an auction process, the bidding behaviour of the participants may influence the clearing price.

8.4.3

Factors influencing spot and forward prices

The previous list of price drivers was presented without any context of time. Like many commodity markets, participants will be buying and selling electricity for a variety of different maturities resulting in a forward curve. Like any forward curve, it represents the clearing price where demand equals supply for different future maturities. Like many commodity markets it will likely display backwardation, albeit on a seasonal basis. Power prices in the UK and Europe will be higher for winter delivery than those for summer. However, traditional forward pricing relationships cannot be applied to electricity markets due to the inability to borrow, lend, or store electricity. Hence the idea of

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a forward price being the expected future price less a risk premium would be perhaps a more valid model (see Chapter 2 for more details). In their report on the energy sector, the EU Commission (2006) noted that market participants rated the following factors as being key price determinants for different maturities: Shorter-dated maturities ▪ ▪ ▪ ▪ ▪ ▪ ▪

Plant availability Input fuel prices Precipitation Wind speed Interconnector availability Temperature Price of carbon emissions

Longer-dated maturities ▪ ▪ ▪ ▪ ▪ ▪ ▪

Forward fuel prices New generation capacity or retirement of existing capacity Water reservoir levels Weather trends Interconnector capacity Price of carbon emissions Economic growth

The report also argued that a risk premium would be embedded within the forward price to reflect the value to participants of the certainty of cash flow that a forward contract would offer over an unknown future spot price. This component could be either a premium or a discount, but the report argues that, in practice, it is more likely to be a premium. This is consistent with one of the pricing frameworks outlined in Chapter 2.

8.4.4

Negative prices

One aspect seen in some energy (and agricultural) markets is the concept of negative prices. One example in the UK natural gas market was cited in Chapter 7. With respect to electricity, intraday prices in Germany fell to −EUR 500/MWh on one day in 2012 (Risk, 2016). One explanation for negative prices was given by the European Commission (2019): ‘Negative hourly prices usually appear when demand for electricity is lower than expected and when variable renewable generation is abundant, combined with ongoing relatively non-flexible large baseload power generation (e.g. nuclear and coal-fired plants). In such cases, conventional power plants begin to offer their output for a negative price in an effort to avoid switching the unit off and having to go through the costly and high maintenance operation of restarting the facility when they are required again.’

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Other reasons cited for negative prices include: ▪ Transmission constraints that would restrict the movement of the excess power to other parts of the grid. ▪ Government subsidies to renewable generators. This means that the price of electricity can be negative but with a subsidy payment from the government the generator could still possibly make a profit. Specific examples of negative prices in the US include: (Risk, 2016) ▪ Hydroelectric plants in the North Western States when heavy spring rains force the plants to keep running to avoid flooding. ▪ Solar and wind power combined with transmission outages in California. ▪ Negative prices in the PJM region, particularly North Illinois because of strong winds in the Midwest. This would typically occur at night when demand would be low, and the winds would be at their most powerful. ▪ Excess wind power in west Texas, prior to the development of new transmission capability. Negative prices were also seen in the United Kingdom electricity markets in 2019 (Watt Logic, 2020). ▪ In March of that year the temperature was unseasonably warm and so demand fell. However, solar generation increased significantly leading to negative prices which fell as low as −GBP 70.24/MWh for about six hours. ▪ Stormy weather in December saw high wind output that triggered negative prices. By midnight on the 7th, wind generation accounted for just under 48% of generation. Prices were negative from around 10:45 pm on 7 December to 12:45pm on 8 December.

8.4.5

Spark and dark spreads

Since the main sources of fuel input to produce electricity are traditionally natural gas and coal, a producer of electricity is caught between two markets. They run the risk that the price of their input exceeds the price of their output. This is captured in two key price relationships. The spark spread is measured as the price of electricity minus the price of natural gas. This effectively measures the relationship between what is produced (electricity) and the main fuel input (natural gas). It is also possible to measure the ‘dark spread’, which relates the price received for electricity to the cost of producing it by burning coal. Although it would appear to be a simple calculation, the different energy sources will be measured in different units. The convention is to express the spread in currency units per MWh, which means that in calculating the spark spread, natural gas, which will be expressed in therms (for the UK market) or British thermal units (for the US market), will need to be converted into an equivalent MWh value. In addition, the thermal efficiency of the input needs to be considered. Recall from an earlier section that thermal efficiency relates the electrical energy produced to the energy content of the

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input. When calculating the spark spread, the market convention is to use a thermal efficiency of 49.13%. That means that for every 100 units of natural gas that are used in production, only 49.13 units are converted into usable electricity. To calculate the dark spread, a thermal efficiency of 36% is applied. In simple terms, the spark spread can be calculated as: Raw spark spread = Price of power − (price of input fuel∕thermal efficiency) However, with the advent of the emissions trading the raw spark spread is adjusted to include the cost of emitting carbon into the atmosphere as represented by the cost of a carbon credit. Adjusted spark spread = raw spark spread − (CO2 adjustment ∗ CO2 price) This adjusted spark spread is sometimes referred to as the ‘clean spark spread’. The dark spread adjusted for the cost of emitting CO2 is referred to as the ‘clean dark spread’. The CO2 adjustment is the number of metric tonnes of carbon dioxide emitted into the atmosphere to produce one MWh of electricity. A figure of 0.42 would be typical for natural gas while the figure applied to coal is 0.85. The following is a full worked example of how the numbers are derived. Let us assume that the cost of day-ahead electricity in the UK is quoted at GBP 34.50/MWh and that day-ahead gas for delivery at the UK National Balancing Point is 36p per therm. The first step is to divide the price of gas by 100 to express it in GBP/therm; the value is therefore GBP 0.36. To convert therms into MWh, the market uses a value of 0.0293071/therm so dividing by this value returns a figure of GBP 12.28/MWh. This is the cost of the input fuel in the electricity generation process. The next step is to take account of the fuel efficiency which involves dividing the fuel cost in GBP/MWh by 0.49131. This returns a value of GBP 25.00 rounded to two decimal places. The unadjusted or raw spark spread is therefore GBP 34.50 – GBP 25.00 = GBP 9.50. Let us assume the cost of emitting one tonne of CO2 was quoted at GBP 10.75. Since the CO2 adjustment is 0.42 this equates to a cost of GBP 4.52/tonne of electricity produced. The spark spread adjusted for the cost of emitting carbon would therefore be GBP 9.50 – GBP 4.52 = GBP 4.98. A similar exercise can be performed for the dark spread. Here the assumption is that steam coal is assumed to have a heat content of 12,000 Btu per pound weight, which equates to 7 MWh per tonne. To obtain the price per MWh for a short tonne of steam coal its price is divided by seven. Assuming the same prices for UK electricity as in the previous example and using a coal price of USD 71.15 per short ton (API 2, 1st Monday Coal Forward; a short ton is 0.907 of a metric tonne), converted at a spot exchange rate of GBP 1.00 = USD 1.90 gives a sterling price of GBP 37.45/tonne. The price expressed in equivalent units of MWh would therefore be GBP 5.35. Using a thermal efficiency of 36% gives the following dark spread: Raw Dark Spread = GBP 34.50 − (GBP 5.35∕0.36) = GBP 19.64

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The ‘clean dark spread’ is calculated using the same value for CO2 emissions as in the previous example but assuming a higher CO2 adjustment of 0.85 (recall that coal generates more carbon dioxide in the production of one MWh of electricity). The cost of emitting one tonne of CO2 is assumed to be GBP 10.75. Clean dark spread = GBP 19.64 − (0.85 × GBP 10.75) = GBP 10.50 If the spread is positive, buying gas and selling electricity will be profitable. However, if the spread were to go negative an electricity producer who has bought gas forward on a fixed basis and has sufficient flexibility within their generation capacity may be encouraged to sell their natural gas back to the market. More importantly it will indicate the increasing impact of the price of carbon on the price of power. This effect varies between markets depending on the source of primary fuel in generation. For example, the impact of the price of carbon is greater in Germany than in the UK given that there are a greater proportion of coal fired power generators. The spreads could be used either by financial institutions to express a view on the differential between the two types of power or could be used by generators to lock in a particular margin. If an electricity producer were to sell the spread (sell electricity, buy natural gas) it would allow them to lock into an advantageous physical margin for future delivery. The exposure could be subsequently unwound by executing a reversing position to buy back the spread. This would have to be executed using OTC forwards as electricity futures are notoriously illiquid.

8.4.6

Marginal heat rates

Another popular measure used often in the US markets is the ‘heat rate’. The concept of thermal efficiency was outlined earlier in this chapter and the heat rate is closely related to this as well as the spark spread. In shorthand terms the heat rate is derived as a ratio of the electricity price and the natural gas price for a particular delivery period. It is calculated as the price of electricity/price of natural gas.

8.5

TRADING ELECTRICITY – AN OVERVIEW

The main participants in the trading of electricity are utility companies, generators, suppliers, industrial consumers, and non-physical participants (e.g. banks, hedge funds, brokers, and trading houses). The country that has the largest population with a wholesale market for the trading of electricity is the USA. However, trading in this country has fragmented into a variety of different regional markets that have evolved in different ways due to the influence of state and federal regulation. In Europe, the largest consumers of electricity in Europe are Germany, France, the UK, Italy, and Spain.

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A detailed description of each market for electricity would consume too many pages and most likely become out of date rather quickly. In this section the aim is to understand in a somewhat stylised manner: ▪ What is meant by trading electricity? ▪ The motives of the main market participants, ▪ How prices are formed in the market. An overview of the electricity market and the key trading linkages is shown in Figure 8.2. Producers Their key activities include: ▪ Long-term commercial contracts with suppliers. ▪ Sourcing or disposing of physical supplies on a particular exchange (e.g. EPEX spot) or via a range of other intermediaries (e.g. energy brokers). ▪ Entering OTC risk management contracts with intermediaries such as commercial banks. ▪ Sourcing exchange traded derivative solutions via exchange members. For example, exchanges such as EEX, ICE, and the CME Group offer electricity futures, but these instruments can only be traded via members of the exchange such as brokers or banks. These futures have traditionally suffered from a lack of liquidity.

Suppliers Their key activities include: ▪ ▪ ▪ ▪

Long-term commercial contracts with producers. Contracts with retail or industrial consumers. Procurement or disposal of physical supplies on exchange. Risk management solutions with intermediaries.

Consumers Although it is unlikely that a retail consumer would seek to hedge their supply of electricity, it may be possible to take advantage of certain offers such as a fixed price supply, which a supplier can offer by using financial swaps. Industrial consumers could enter risk management solutions on the wholesale market rather than via their normal supplier.

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Intermediaries The roles of intermediaries have been touched on, but one additional motivation would be to use financially settled contracts to express views on expected market movements. These views could include: ▪ ▪ ▪ ▪ ▪

Expressing views on the direction of the prices. Exploiting price differences between markets. Making money as a market maker and so profiting from bid-offer spreads. Providing a brokerage service to generate fees. Buying and selling structured products to allow investor participants to benefit from price movements without the need to own the underlying assets.

8.5.1

Load shapes

For contracts that will cover a day or more, how much power is going to be delivered is clearly specified. This is sometimes referred to as the’load shape’. There are several standard load shapes, which include: ▪ Baseload – this type of contract provides for the delivery of a constant (i.e. 24 hour) volume of power for each period (e.g. day, weekend) that the contract covers. ▪ Peak load – although there is no overarching definition of peak load, these contracts would require the delivery of power between, say, 7:00 a.m.–7:00 p.m., Monday to Friday when demand is likely to be high. ▪ Off peak – this covers all other periods outside of the peak load definition. ▪ Overnights – these cover periods such as 11:00 p.m.–7:00 a.m.

8.5.2

Contract volumes

When power is traded it may be quoted in MW, which is sometimes referred to as the contract capacity, contract unit, or unit of power. A Megawatt is an instantaneous quantity of electricity. If I were to switch on a light bulb that consumes 100 watts, it is consuming 100 watts of power at any given time that it is on. An energy-efficient light bulb requires about five watts, a kettle 2,000 watts, and an aluminium smelter a billion watts (i.e. one gigawatt or a 1,000 megawatts) – about the same energy that is produced by a medium-sized power plant. A megawatt-hour (MWh) is the volume of power produced or consumed during a particular hour. If the light bulb is switched on for an hour it will consume 100 watt-hours or 100/1,000,000 MWh. A MWh can be thought of as the rate of delivery power. A typical household may use in the region of 10 kilowatt-hours per day. In trade confirmations the volume per settlement period (e.g. every half hour in the UK) and the total contracted volume (sum of every half hour) will be stated in MWh not MW.

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A couple of examples may help clarify. The following is based on the UK market where each trading day comprises of 48 periods each lasting 30 minutes. Trade 1: ‘winter peak load 20 MW’ should be interpreted as: Duration: each half hour period from 7:00 a.m.–7:00 p.m. on Monday to Friday, from the first day of October to the last day of March inclusive. This is a total of 24, half-hour periods per weekday. Total contracted volume: this is calculated as 20 MW × 12 hours × 5 days × 26 weeks = 31, 200 MWh. Daily volume: this is calculated as 20 MW × 12 hours = 240 MWh Volume per settlement period: this is the amount to be delivered in each half hour period of generation and is equal to 10 MWh. Trade 2: “summer base load 100 MW” is interpreted as: Duration: each half hour from 11:00 p.m. on the last day of March to 11:00 p.m. on the last day of September. The contract delivers for 24 hours a day or 48 half hour generation periods. Total contracted volume: this is calculated as 100 MW × 24 hours × 7 days × 26 weeks = 436,800 MWh. Daily volume: this is calculated as 100 MW × 24 hours = 2,400 MWh during each day. Volume per settlement period: this is the amount of electricity to be delivered in each of the 48 half hour blocks and is equal to 50 MWh.

8.5.3

Contract prices and valuations

Although transactions are entered into with the quantity expressed in MW, prices are agreed in the domestic currency per MWh. When valuing a contract, the total contracted volume (MWh) is multiplied by the price to find the value of the contract. Take for example, trade 1 outlined previously. If the contract had been traded at GBP 14.00/MWh, the total value of the contract would be expressed as GBP 14.00/MWh × 31,200 MWh (total contracted volume) = GBP 436,800. In trade 2 if the contract price had been negotiated at GBP 15.00/MWh the total contract value would be calculated as GBP 15.00/MWh × 436,800 MWh = GBP 6,552,000.

8.5.4

Price formation

The main way in which electricity was traditionally priced in a regulated market was through some mechanism that allowed for operational costs to be covered as well as providing investors with an acceptable return. In Section 8.3 it was argued that there are two main market models – pools and bilateral contracts, and so the next step is to consider price formation within these structures; how much should a generator charge? Irrespective of the market structure, electricity prices are closely related to production costs, that is, the short-term variable costs incurred to generate power. Indeed, increased competition will often drive the wholesale price down to the short-run marginal cost level; logically a generator will only sell their production if they can recover their variable costs. These variable costs are primarily made up of the input fuel as well as operating and maintenance costs (e.g. labour costs). However different generation facilities will have different variable cost structures. Renewable sources

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of fuel incur no procurement cost. You do not have to pay to make the sun shine or the wind blow. So, for this type of plant, their variable costs are operational, and maintenance based. Nuclear plants may have high fixed costs since they are expensive to build but low variable costs. Natural gas plants may have higher fuel costs and lower fixed costs. To illustrate the principles of price formation, consider the following example, which is loosely based on a bilateral market structure. Suppose a generator is approached by a consumer to supply 500 MW for a given period the following day. To what price should the producer agree? To keep the illustration straightforward we will assume that this is the only supply contract on the producer’s books. The producer will need to know what generation capacity is expected to be available for that period and the cost to produce the requisite amount of energy. The producer estimates that they will have 1,000 MW of production capability available, split between a variety of different source fuels shown in Table 8.2: TABLE 8.2 Hypothetical capacity and operating costs for an electricity producer. Input fuel

Available capacity (MW)

Operating costs (USD/MWh)

Diesel Coal Natural gas Renewable Nuclear

40 130 350 120 360

150.00 120.00 110.00 80.00 70.00

The concept of ordering the input fuels according to cost is sometimes referred to as the ‘merit order’ or ‘supply stack’ and is based on the premise that to optimise their output, a producer will start with the cheapest source of fuel, which in this example would be nuclear. Figure 8.6 is a diagrammatic representation of the producer’s merit order.

Operating costs ($ / MWh)

Diesel Natural gas

Coal

Market price Nuclear

Renewable

Demand

FIGURE 8.6 The merit order and price formation.

Available capacity (MW)

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For ease of illustration it is assumed that demand is constant irrespective of the price level (‘inelastic demand’). Some readers may reasonably argue that renewable operating costs should be the lowest in the merit order. However, these can vary considerably depending on the type of renewable energy. Since the consumer requires 500 MW of power, their demand will be met from three sources of fuel: nuclear (360 MW), renewable (120 MW) and gas (20 MW). The single price paid by the consumer will be based on the cost of producing the ‘marginal unit’ of power, which is the cost of natural gas. Hence the consumer will pay USD 110.00/MWh. Note that the profit margin for the nuclear and renewable sources could be substantial, but it is important to bear in mind that the cost of building this infrastructure would have been significant and is not shown in this example. Once these fixed costs are factored into the calculation, they may not be more profitable than the other generation assets. Another shortcoming of the previous example is that it assumes that the price of the input fuel will remain constant as a function of demand. This is perhaps unlikely and so a more realistic representation of the merit order shown in Figure 8.7. From this it is possible to develop a sense of how prices can change: ▪ ▪ ▪ ▪ ▪

Demand may change. Input fuel prices can increase or decrease. Plant availability may suddenly change. Lower electricity prices in other regions may lead to an increase in imports. Higher electricity prices in other locations may make exports more attractive.

Based on this single order the producer has a capacity margin of 500 MW – the difference between what he expects to produce and what he can produce. The amount of spare capacity can also sometimes be a good indicator of the level of margins that producers can charge, i.e. the amount by which the price of electricity exceeds their production costs. This margin is sometimes referred to as a scarcity premium and could last for a single generation period or longer. Levels of reserves or spare capacity are defined

Operating costs Diesel

Natural gas

‘The Devil’s elbow’

Coal

Market price Renewable Nuclear

Demand

FIGURE 8.7 The merit order and price formation.

Production capacity

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as (Installed capacity peak demand)/Installed capacity. Market analysts suggest that once reserve levels fall to about 10–13%, it is likely that there will be strong upward price pressure with increasing margins (Barclays, 2008).

8.5.5

Optimising production

The chapter on crude oil illustrated how a refiner could optimise their production. In this section we will illustrate similar principles for the electricity market. The example is simplified and stylised for clarity purposes. Suppose an electricity producer decides to forecast how much they expect to supply in some future period; perhaps a single day in one week’s time. They will be able to build a profile of their forecasted production based on several factors: ▪ ▪ ▪ ▪ ▪

Existing contracts with suppliers, Forecasted demand, Historical patterns, Weather forecasts, Significant events (e.g. sporting occasions). The producer will then consider how to meet this production requirement:

▪ Produce the electricity from their own resources. ▪ Buy electricity from another producer. For example, if the market price for supplying electricity is below the producer’s marginal cost it may be more efficient to buy the power from another producer. ▪ Buy the electricity via an intermediary (e.g. broker or trading house) or via an exchange in the form of a physically settled forward or future. This will allow them to procure the supplies that they need as well as immunizing them against price volatility. They will be aware that things could change significantly; consumers may choose to use more or less than expected and so suppliers may have to change their demand requirements. As they approach the specific day, they will gradually buy and sell to match their evolving demand pattern. Some market structures have organised exchanges that offer a physically settled ‘day ahead’ and ‘intraday’ facility to accommodate this type of trading. For example, the EPEX spot exchange in the UK offers a ‘double-sided blind auction’. Participants who are looking to either buy or sell to manage their very short-term demand and supply profiles can enter anonymous orders onto the exchange. The exchange will then run an algorithm that creates binding contracts based on matched orders. These principles could be expanded into a longer-term horizon. For example, the demand for a 12-month period could be managed by: ▪ Buying an annual physically-settled forward contract to cover the minimum amount that is expected to be generated. ▪ Seasonal or quarterly contracts could be used to procure supplies in the colder part of the year (e.g. winter and spring).

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▪ Monthly contracts could then be used to manage periods that may be exceptionally cold (e.g. January). ▪ More specific contracts could then be introduced such as off- and on-peak contracts or weekend baseload. The use of forwards and futures can also lead to the amount of traded power exceeding the actual amount that is physically produced and consumed. This could arise when a participant enters a forward commitment and then subsequently decides to terminate the transaction prior to settlement. If traded on an exchange, it would be possible to take an offsetting position, as only net amounts would require delivery. For example, in 2018, the UK generated 333 TWh, while estimates from the London Energy Brokers Association suggested that for the same period approximately 884 TWh was traded on an OTC bilateral basis. Figures for Germany, the most actively traded European market, suggest a physical generation balance of 540 TWh and OTC derivatives worth 5,330 TWh on a notional basis.

8.5.6

System imbalances

Another important aspect to consider within the trading context is the TSO/ISO. Suppliers will make a judgment as to how much electricity they require for their end consumers and then enter contracts with generators to fulfill these commitments. These contracts could cover short- and long-term requirements. Contracts to buy and sell electricity are made bilaterally through commercial over-the-counter (OTC) negotiations or via recognised exchanges. This type of trading will continue until ‘gate closure’, which will be a defined period (e.g. one hour) before the specific generation period. Once a contract has been made, the two parties are required to notify the system operator of the terms of the deal but not necessarily the price. This will allow the system operator to identify and attribute any imbalances after the specified generation period. An imbalance occurs when there is a difference between their actual physical outcome with the trades that they had contractually agreed. Prior to gate closure generators and suppliers must deliver a final physical notification to the system operator, which represents an expectation of how much they will supply and consume. Depending on the structure of the market the generators and consumers may additionally indicate how much they are willing to deviate their production from this indicated level. This is done by submitting bids and offers, which represent the amount and price that they are willing to vary production from their final physical notification. During the period after gate closure as well as during the actual generation period, the transmission system operator will aim to resolve any imbalances between production and consumption on a real time basis. The imbalance can be managed by utilising the extra flexibility to consume or produce by the market participants from their notified levels. The system operator may also be faced with spikes in demand, power station failure, or perhaps physical capacity problems of the transmission grid. During the half hour generation period, power will be delivered or consumed as per the agreed underlying consumer contracts agreed by the producers and consumers.

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After this period, any imbalance is calculated by reconciling what was supposed to be generated or consumed with what was actually consumed. Any surplus or deficit is charged back to the guilty party by the imbalance system based on the prices the system operator were faced with when trying to resolve the imbalance. Imbalances occur for a variety of reasons: ▪ Traders of electricity may buy more or less energy than they have sold. ▪ Generators may produce more or less energy than they have sold. ▪ The customers of suppliers may consume more or less energy than the supplier has purchased on their behalf. ▪ Failure of generation equipment. ▪ Scheduling errors. ▪ Output variances due to ambient temperatures. This is because energy can be ‘lost’ during transmission due to factors such as temperature. As a rule of thumb these losses are around 10%. So, if demand is 100 MW, then it is likely that 110 MW will need to be generated to ensure that the system is in balance.

8.5.7

Timing mismatches

Depending on the structure of the market, there may also be a mismatch in the structural timing of consumer purchases and producer sales. Large power producers may seek to sell their production on a forward basis for cash flow certainty, perhaps to service a loan facility used to construct the plant. Equally, they may be happy to sell on an opportunistic basis if they believe that a certain price represents value. Buyers of power may prefer to buy their power within a shorter forward time frame. This mismatch can be accommodated by non-physical intermediaries who will be willing to manage the associated risks.

8.5.8

UK trading conventions

Until 2014, trading in the UK market was based exclusively on the EFA (Electricity Forward Agreement) calendar. This calendar broke down a year into 12 months each containing four or five weeks, with every week allocated a particular number. At the highest level, the trading year is broken down into two seasons with summer defined as EFA April–EFA September and winter as EFA October–EFA March. The year was also expressed in quarters: Quarter 1 = EFA January–EFA March Quarter 2 = EFA April–EFA June Quarter 3 = EFA July–EFA September Quarter 4 = EFA October–EFA December

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Equally it was possible to break down the EFA trading year into a series of individual EFA months, but it should be noted that the EFA calendar did not always follow the regular Gregorian calendar. Every EFA week was designated a particular number and was broken into EFA days, with a day starting at 23:00 on the previous night to 23:00 on the day in question. Each EFA day was divided into six EFA blocks of four hours each: Block 1

23:00–03:00

Block 2

03:00–07:00

Block 3

07:00–11:00

Block 4

11:00–15:00

Block 5

15:00 –19:00

Block 6

19:00–23:00

Each of these blocks could be referred to in abbreviated fashion using ‘WD’ to denote that the block occurs during a weekday or ‘WE’ for a weekend. So WD3 would relate to a weekday period covering 07:00–11:00, while WE5 would cover a weekend period extending from 15:00–19:00. To further complicate matters each day could be further subdivided into several half hour periods to reflect the actual physical generation patterns. Block 1 of a particular trading day included the 47th and 48th half-hour periods of the previous day and periods one to six of the calendar day in question. This structure would be the same for the remaining EFA daily blocks. These half-hour periods are referred to as settlement periods. After 2014 the market widened to incorporate trades based on a traditional Gregorian calendar to come into line with other European markets. However, contracts based on the EFA calendar traded before 2014, but with an expiry after this date would still be required to apply EFA principles. But like many markets, once an idea is firmly embedded, it can prove to be very difficult to shift and so at the time of writing (early 2020), indices referencing ‘trading blocks’ exactly equal to the EFA approach were still being quoted in the UK market.

8.5.9

US traded markets – an overview

Although oil markets are global, natural gas markets largely continental, electricity markets in the USA are regional. Although there may be some sharing of resources by neighboring markets, the US transmission system was not designed to move large amounts of power across the country or indeed over very large regions. Nonetheless, what sharing of resources that has occurred has led to a relatively small number of actively traded markets. The general principles of electricity regulation in the US traditionally meant that utilities were subject to regulation and often had to prove that they were able to serve customers many years into the future. As a result, they would sometimes collaborate with other local entities to share power plants and transmission lines. This concept of joint planning gave rise to ‘reliability organisations’

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that were mentioned in Section 8.3.4. The traded markets that emerged from deregulation essentially formed around these same organisations and locations as well as sometimes using the same name (e.g. ERCOT). The main wholesale markets are: More actively traded ▪ California Independent System Operator (CAISO) ▪ Midcontinent Independent System Operator (MISO) ▪ New England (ISO-NE) ▪ New York (NYISO) ▪ PJM (Pennsylvania, New Jersey and Maryland) ▪ Southwest Power Pool (SPP) ▪ Texas (ERCOT) Less actively traded ▪ Northwest ▪ Southeast ▪ Southwest When electricity is traded on a wholesale basis, the contracts are physically settled for delivery at a pre-agreed location. Within each of these regions there will be several individual trading points (e.g. PJM-West; Southern California SP-15, Northern California NP-15). There is no single national price for electricity in the USA. Physical producers and consumers will buy and sell electricity in the regions of their physical operations. Power traders (e.g. non-physical intermediaries) may choose to transact in one or more of the regional markets. For example, in the Texas market, there are four related, but distinct sub-regions: North, West, South, and Houston. So, although prices in these regions will be related in terms of physical capacity, restraints have traditionally prevented lower cost energy flowing to adjacent areas where prices are higher. Congestion occurs when lower priced generation is available on one part of the grid, but because of physical capacity constraints, cannot be delivered into another location. As a result, the receiving area must source its generation from local facilities that will be more expensive and so different prices will apply in each location for that generation period. This pricing technique is referred to locational marginal pricing, which is the marginal price for energy at the location where it is delivered or received. When the lowest priced electricity can reach all the locations, then theoretically the price of power across the grid will be the same. For example, on the day of writing this, the PJM1 website listed 22 zones2 , each with a different price for electricity ranging from USD 40.51/MWh to USD 44.21/MWh. According to Blumsack (2018), ‘the locational marginal price at some particular point

1

To give some context, PJM coordinates the movement of wholesale electicity in all or parts of 13 US States and the District of Columbia. 2 Individual locations within a grid maybe referred to as nodes, while a zone represents a number of nodes.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS Transmission capacity = 80 MWh

A

B

Demand = 50 MWh Marginal cost = $10/MWh

Demand = 100 MWh Marginal cost = $15/WMh

FIGURE 8.8 Example of locational marginal pricing. in the grid measures the marginal cost of delivering an additional unit of electric energy (i.e. a marginal unit MWh) to that location’. The following example is based on his text. Suppose there are two linked locations within a grid: node A and node B. A generator in node A has a marginal cost of USD 10/MWh, while local demand is 50 MWh. The generator in node B has a marginal cost of USD 15/MWh and local demand is 100 MWh (Figure 8.8). We will assume that both generators have the capacity to produce 200 MWh at their respective marginal costs. If the transmission line had an infinite supply capacity, then the system operator would dispatch all the required electricity from the generator in node A at a cost of USD 10.00/MWh. This generator would be able to meet demand from both nodes (i.e. 150 MWh) and there would be a single system marginal price of USD 10.00/MWh. Now let us impose a constraint on the transmission capacity between the two nodes of 80 MWh. In this case the system operator dispatches the generator in node A for a total of 130 MWh. This comprises the local demand of 50 MWh and an amount equal to the inter-node transmission capacity of 80 MWh. However, there is still 20 MWh of unfilled demand in node B and so the system operator dispatches the local generator in node B to meet this demand. However, the marginal cost for doing this is USD 15.00/MWh. The customers in node A will pay USD 10.00/MWh; this is their LMP. The customers in node B will pay USD 15.00/MWh for all the energy consumed; this is their LMP. This is even though some of it was supplied from node A at a lower price. The prices paid by the customers in node B are a little unfair and that some form of weighted average would be more appropriate. Sadly, the LMP method does not work that way! From the generators’ perspective, they are each paid their respective marginal costs based on the amount that is generated. The system operator collects revenues from the customers in each node as follows: Node A∶ 50 MWh × USD 10.00∕MWh = USD 500 Node B∶ 100 MWh × USD 15.00∕MWh = USD 1,500 Total collected = USD 1,500 The system operator pays the generators as follows: Node A∶ 130 MWh × USD 10.00 = USD 1,300 Node B∶ 20 MWh × USD 15.00 = USD 300 Total paid = USD 1,300

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Note that the system operator has collected more than they have paid, and this difference is referred to as ‘congestion revenue’ (sometimes variously referred to as a cost, charge, or price). How the system operator allocates this congestion revenue is beyond the scope of the text. Financial Transmission Rights (FTRs) are a popular instrument that can be used when prices vary in different locations. FTRs (also sometimes referred to as ‘congestion revenue rights’, ‘transmission congestion contracts’, or ‘transmission congestion rights’) are ‘contracts for difference’ (CFD) auctioned by a system operator and represent an agreement whereby the system operator will compensate a participant if an actual congestion cost between two points on the transmission system is greater than a pre-agreed level. However, it can also be a liability if the cost is lower than the pre-agreed level. According to Moody’s (2018) they are ‘financial instruments that allow market participants to offset potential losses or hedge against the congestion component of locational marginal prices in day-ahead electricity markets. An FTR obligation contract entitles the holder to be compensated if congestion occurs between two points on the grid in the same direction as stated in the contract. The contract holder is charged if congestion occurs in the opposite direction stated in the contract.’ Returning to our LMP example, suppose that the day before, the generator in node A wishes to sell electricity into node B, and they enter an FTR in the direction from node A to node B. If the clearing price in node B is higher than node A, then the FTR will pay out this differential. So in our example, had the generator in zone A executed such a deal they would have sold their power in both nodes for which they would have received the lower of the two prices (i.e. USD 10.00). Since the LMP in zone B was higher at USD 15.00 the FTR would have paid them a USD 5.00 differential per unit of volume. Since these are financially settled instruments, they can be used by participants to express views on expected congestion costs without any requirement to make or take physical delivery. They can also be structured to act in a similar way to financially settled options rather than the CFD variant noted above.

8.6 8.6.1

ELECTRICITY DERIVATIVES Electricity forwards

Unlike other markets that use a forward curve for pricing contracts for delivery at different points in time, the fact that electricity cannot be stored means that the traditional methods of pricing a forward contract (i.e. spot price plus net carry) will not apply. As a result, expected levels of supply and demand determine the forward. Additionally, the forward price may move independently of the spot price, as there is no mechanism for arbitraging the two markets. So if a forward contract is perceived to be trading ‘rich’ to some notion of theoretical value, it is not possible to sell the electricity forward, buy it for spot delivery, store it for a given period, and then use it to fulfill the forward obligation. Over-the-counter forward deals may be attractive for a variety of reasons: ▪ Price certainty is achieved. ▪ Avoids the need to buy in a volatile spot market. ▪ Physically settled transactions can be a useful tool to secure supplies.

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▪ Can be executed on a ‘paper’ rather than physical basis so that the supply and the risk management can be separated. ▪ Can be used to speculate on movements in the market. ▪ Certain financing transactions may require the end user to use forwards to give certainty of revenues. A fixed price power forward is straightforward in terms of how the contract will be set out. Although each contract will vary the basic terms will be similar. For example, the following criteria need to be specified for a physically settled transaction: ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪

Trade date Buyer Seller Type of governing contract Price Volume Load shape Delivery schedule Delivery point

The contracts will often contain a schedule outlining the detail of the supply. Take for example the transaction for delivery on the RTE Grid in France shown in Figure 8.3. The contract fixes the price for delivery of 50 MW for 12, one-hour periods to give a total contract amount of 600 MWh. At an agreed fixed rate of EUR 60/MWh, the total value of the contract is set at EUR 36,000. TABLE 8.3 Summary of physical supply contract. Total Supply Period Start

Contract Contract Applicable Days From To Capacity quantity End Mon Tue Wed Thu Fri Sat Sun CET CET (MW) (MWh)

3 Aug 3 Aug

X

08:00 20:00

50

Contract Total price (EUR/ amount MWh) (EUR)

600

60

36,000

Another example of a physical forward contract requiring the delivery of a fixed volume of power at an agreed price for an agreed period is given below. Trade date: Effective date: Maturity: Buyer: Seller: Price: Volume per hour: Total Volume: Load shape: Delivery point:

26 June 27 June 28 June Counterparty A Counterparty B GBP 32.00/MWh 50 MWh 1,200 MWh Baseload GB National Balancing Point

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A load shape refers to the level of expected demand during certain times of the day. A baseload contract provides for the delivery of a constant volume of power throughout the day. A peak load contract for the UK typically runs from 7:00 a.m.–7:00 p.m. on a weekday. The other popular standard load shape is off peak, which is defined as everything except the peak period. Since this forward is a baseload contract it requires the seller to deliver a constant volume of power for a 24-hour period. In this example the contract covers a one-day period in one-day’s time, but since these contracts are traded on an over-the-counter basis it would be possible for the counterparties to the trade to agree a longer period if necessary. Floating price forwards Floating price forwards, or ‘index price forwards’ allow the parties to the transaction to deliver a given amount of MW at a given time period in the future at a price that will be set at the point of delivery based on an agreed market price index. Cross market trading One type of trade growing in popularity allows a trader to exploit the difference in power prices between countries. Interconnectors allow participants to move electricity across countries, but to do so the trader must have purchased the right to transmit the power. The capacity to transmit is auctioned on a regular basis by the grid operator. Cross market trades are in essence very simple. Suppose a trader sees that the price of power in France is EUR 55.00/MWh while the price in Germany is EUR 60.00/MWh and that the trader has purchased annual transmission capacity at a cost of EUR 3.00/MWh. He agrees a trade size of 100 MW to buy the power in France and sell it into Germany. An annual baseload contract would generate a profit of: EUR 60.00 − (EUR 55.00 + EUR 3.00) × 24 hours × 365 days × 100 MW = EUR 1,752, 000

8.6.2

Electricity swaps

As entities such as hedge funds do not trade physical power, financially settled swaps represent an alternative way of taking exposure to the underlying market. These types of swap involve the exchange of cash flows where one cash flow is fixed while the other is floating. The floating cash flows reference a market index such as the LEBA (London Energy Brokers Association) day-ahead index. This index price is constructed as the volume, which is the weighted average of all day-ahead baseload trades executed in London by several contributing institutions. GB power swaps settle against the average value of the index through the period being traded, typically months, quarters, seasons, or years. Suppose a hedge fund wishes to express a view on anticipated power market movements over the next winter. They decide to ‘buy’ 30 MW of winter baseload power at GBP 45.50/MWh, referencing to the LEBA day ahead index with monthly settlement covering the six-month period from October–March.

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Payments will take place at the end of the month against the average of the day ahead index values published every day throughout the month in question. To illustrate the cash flow amounts let us assume that one of the months has 31 days and that the floating LEBA index has fixed at GBP 40.00. Since the hedge fund has ‘bought’ the swap they will pay the fixed price and receive the floating index. The cash flows will be: Fixed cash flows paid 30 MW × GBP 45.50 × 24 hours × 31 days = GBP 1,015,560 Floating cash flows received 30 MW × GBP 40.00 × 24 hours × 31 days = GBP 892,800 Since the timing of both cash flows coincides, it is conventional to make a net payment. Hence the hedge fund will make a net payment of GBP 122,760. So, what would be the hedge fund’s motivation for executing this swap transaction? In simple terms, the swap price can be thought of as a weighted average of the forward prices for each of the periods that the swap covers. From the hedge fund’s perspective, the trade is essentially bullish, as they must believe that the actual day-ahead price will on average be greater than the individual forward rates used to initially price the swap. So in the previous example the fixed price would be a function of the forward prices for each individual month within the winter period. As such, the trader’s motivation is simple – they will always aim to ‘beat the forward price!’ Swaps can also be used for hedging purposes. For example, a supplier may have agreed a floating price supply contract with a generator but wishes to transform their exposure such that on a net basis they would pay a fixed price. In this case, they could receive a floating cash flow from a swap provider to negate the underlying exposure with the generator and in return, agree to pay a fixed price under the terms of the derivative. Equally, based on the same parameters a generator could also transform their market risk by paying floating and receiving fixed under the terms of a swap. The generator would receive a variable price for the physical power they sell which can finance the floating swap payment. Their net revenue is therefore the fixed price received under the swap. Continental European power swaps will have several key features with differences to reflect local market conventions. The main markets that will be traded include France, Germany, Spain, Scandinavia, and the Netherlands. However, a few generalisations can be made as to their structure. There will be a stated maturity such as six months as well the frequency with which the cash flows will be paid. This will usually be monthly and is referred to as the calculation period. The contract will outline the load shape, which may typically include: ▪ Baseload – 24 one-hour periods from 00:00–24:00. ▪ Peak load – 12 one-hour periods from 08:00–20:00. ▪ Off-peak – 12 one-hour periods from 00:00–08:00 and 20:00–24:00 Monday–Friday; 24 one-hour periods from 00:00–24:00 Saturday and Sunday.

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Payment is made in arrears after each calculation period usually with a lag, which could be either 5 days or 20 days. In terms of the ‘price’ of the swap, the fixed rate per MWh will be stated as well as the counterparty responsible for making the payment. For continental power swaps, the floating payment may typically be based on hourly prices. The counterparties to the trade would agree a notional quantity for each hour of generation expressed in MWh, which is applied to the floating price derived from the agreed source. The floating payment made at the end of each calculation period is the sum of these monetary values. So as an example, take a 92-day baseload contract with an agreed notional quantity of 6 MWh for each hour of generation. At the end of each month the counterparties would have to take the hourly price observations, apply them to this notional quantity, and add them all up to calculate the floating amount. The total notional quantity for the contract would be equivalent to 13,248 MWh (6 MWh × 24 hours × 92 days).

8.6.3

Contracts for difference

As a way of encouraging low carbon power generation, the UK government has mandated a new product referred to as a contract for difference (CFD), illustrated in Figure 8.9. The low carbon contracts company (LCCC) is a government-owned entity and acts as the CFD counterparty to the generator. The generator will produce their electricity and sell it into the market at the prevailing market price. To help them manage market price movements they could then enter a CFD for a period of 15 years. Under the terms of the CFD the generator will pay or receive a cash flow based on the difference between a pre-agreed strike price and a variable ‘reference price’. The strike price is set by the government and will vary according to the type of technology. For the years 2015/2016 the strike price for onshore wind technology (OWT) was set at a maximum of GBP 95.00/MWh. However, there are circumstances where CFDs are granted on a competitive basis, so this strike price acts as a maximum value. For the period 2015/2016 the fixed rate payable by the LCCC for OWT contracts was set at GBP 79.23/MWh. The variable reference price payable by the generator is based on the average market price for electricity. Suppose an onshore wind generator sells electricity in the open market and receives GBP 70.00/MWh. Under the terms of the CFD and assuming a fixed strike of GBP 79.23/MWh they will receive a supplemental payment of GBP 9.23/MWh such that their

Sale of electricity

Strike price Low carbon contracts company

Low carbon generator Market price

FIGURE 8.9 Example of contract for difference.

Reference price

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income will be equal to the CFD’s strike price. If the price the generator received for the sale of their electricity was, say, GBP 85.00/MWh, then under the terms of the CFD they would be required to pay GBP 5.77/MWh (i.e. GBP 79.23 – GBP 85.00). However, in both scenarios the generator’s net income from both sides of the transaction would be equal to the CFD’s strike price and so they are protected from volatile wholesale prices.

8.6.4

Swaptions

Consumer hedge – manufacturing company A swaption is defined as an option on a swap. Consider the following hypothetical example. A large UK manufacturer is looking to lock in the purchase price of its physical supply of power. Looking at forward prices, they believe the actual price of power will be, on average, higher than the forward prices currently being quoted in the market. They currently consume about 25 million kWh per month of power and are looking to hedge half of this volume. They enter a fixed price swap with the following terms: Swap buyer: Swap seller: Volume: Tenor: Fixed price: Reference price: Settlement frequency:

Manufacturing company Bank 12,500,000 kWh per month 12 months GBP 50.00/MWh GB baseload Monthly

On the last business day of each month the parties would calculate the reference price which, as was illustrated in the last section, would usually be an average of daily prices observed over the month. The swap would be financially settled so as not to interfere with the manufacturer’s physical supply relationship. To illustrate the impact of the swap let us consider some possible outcomes. Let us assume that in one month the average cost of GB baseload power was GBP 55.00/MWh. The manufacturer would pay this amount to his physical supplier and receive the agreed amount of power. Under the terms of the swap the bank would be required to pay this same amount to the manufacturer and in return receive the pre-agreed fixed price of GBP 50.00/MWh. Since both cash flows under the swap coincide there would be a net settlement of GBP 5.00/MWh in favour of the manufacturing company. This means the net cost of buying their power is GBP 50.00/MWh (GBP 55.00/MWh paid out to the supplier with GBP 5.00/MWh received under the swap). If the average price were, say, GBP 40.00/MWh then the manufacturer would pay this amount to their supplier and be required to make a net payment of GBP 10.00/MWh under the terms of the swap. The net result in both examples is that the client achieves a fixed price of GBP 50.00/MWh – the same value as the fixed price in the swap. Had the trade been structured as a swaption, the manufacturer could purchase the right to ‘buy’ a swap (i.e. purchase the right to pay a fixed price3 ). Like the options 3

This could also be referred to as the purchase of a payer swaption.

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319

considered earlier, this transaction would also incur a premium. At first glance it may appear that this transaction would be appropriate if the client believed that power prices were going to rise as they could exercise the option, enter into the swap, and then pay a fixed price. However, this is not the case. If they were certain that prices were going to rise, they would simply enter the swap; entering a swaption will incur a premium whereas the swap is traded on a bid-offer spread. Arguably, the right motivation for the transaction is that the client believes that power prices are going to fall, but decide to take out protection in case their view is incorrect. It is also worth noting that few corporates are willing buyers of options. Anecdotally, their main objection to single option structures is the requirement to pay a premium. As a result, it is most common for banks to structure zero premium transactions where different options are combined such that the client does not incur any upfront charge. A very popular zero premium transaction is termed a ‘min-max’ structure (sometimes referred to as a zero-premium collar). The purchased swaption we considered earlier fixes the maximum price that the client will pay if they decide to exercise the option. To achieve a zero premium, the client not only buys this option but also sells a second option to the bank, which if exercised, would require the client to pay a fixed price albeit at a lower strike. The strike of the sold option is set at a level such that the premium generated fully finances the cost of the purchased option. The sold option fixes the minimum price that the client will pay and would only be exercised by the bank against the client if the price of power is falling. This will prevent the client from enjoying the benefits of lower prices although it should be remembered that they have protection from prices rising at no premium cost. If the price of power is between the upper and the lower strike prices, neither option is exercised, and the client buys their power at the prevailing market price. Given many clients’ wariness of selling options, the transaction term sheets rarely mention the fact that the structure involves the sale of an option and may simply talk about a ‘cap’ and a ‘floor’ price.

8.6.5

Spread options

The mechanics of spread options were considered in Chapter 1. How could they be applied within the context of electricity? In Section 8.4.5., the concept of spark and dark spreads were introduced. A possible ‘view-driven’ strategy would be to execute an option that pays off if the underlying spread were to increase or decrease relative to a pre-agreed strike price. Another application is one where a client could be protected from an adverse movement in the price of power in another country. Suppose that a UK chemical producer has a competitor based in France. In this scenario, power is a significant input to the process and their competitive position could harmed if UK prices rise relative to those in France. A spread option that pays off if the price of French power declines relative to those in the UK could be a solution.

8.6.6

Monetising embedded optionality

Electricity represents a significant cost for an aluminium producer. It is possible that in a deregulated electricity market where the aluminium producer is buying its physical power on a floating price basis, that a spike in power prices could force a potential

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shutdown. If the producer has a flexible power supply contract that grants them the ability to sell on their electricity, they have a form of embedded optionality that could be monetised (Barclays, 2003). When considering the cost of closing a plant, an aluminium producer might consider: ▪ The requirement to keep a certain number of people employed to maintain the plant. ▪ The profit or loss that might be generated from the resale of their raw material, alumina. ▪ The operational costs of physically shutting down and restarting the plant. ▪ The cost of breaching any existing contractual supply contracts. Once these costs have been established it would be possible to calculate an ‘indifference curve’. This would represent a series of aluminium and power price combinations where the producer would be indifferent to whether they will: ▪ Purchase power and produce aluminium or, ▪ Close down aluminium production and on sell their electricity. This relationship is shown in Figure 8.10. This form of optionality can be monetized by the sale of a call option. That is, the aluminium producer sells the right that would allow the option buyer to buy electricity at a pre-agreed strike price and a pre-agreed time in the future. The option is structured in such a way that it will comprise of a time-limited option (e.g. three months), which if exercised, would then result in a forward as opposed to a spot sale of electricity. This delayed sale of electricity would give the aluminium producer sufficient time to shut down their operations. To illustrate how this would work consider the following simplified example. With the current price of electricity at USD 80.00/MWh, an aluminium producer sells Price of electricity

Sell electricity

‘Indifference curve’

Sell aluminium Price of aluminium

FIGURE 8.10 Aluminium producer’s indifference curve.

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321

a three-month out-of-the-money call option that references electricity. If exercised, it would allow the option buyer to receive a certain volume of electricity at a pre-agreed price, say, USD 100.00/MWh. It is assumed that this strike was set at or above their indifference curve. The option would be struck OTM, as it will be exercised only if the price of electricity increases significantly, and so as a result the premium would be relatively low. In this example let us suppose that the option premium is USD 3.00/MWh. The following scenarios would then result: Price of electricity is below the strike price Buyer does not exercise the option. Option expires worthless and aluminium producer retains premium, which can be used to enhance the company’s cash flow. Producer opts to produce aluminium. Price of electricity is equal to the strike price Buyer exercises the option and takes delivery of the agreed volume of electricity at the strike price of USD 100.00. Aluminium producer pays USD 100.00 for the electricity from its supplier but retains the premium of USD 3.00/MWh. Price of electricity is above the strike Buyer exercises and takes delivery of the electricity as before. However, if the price of electricity has exceeded the retained USD 3.00/MWh premium, then the aluminium producer must now pay more to their electricity supplier than they will receive from the option buyer. If they have hedged 100% of their power supply this could incur losses. They may therefore decide to execute the option for part of their electricity consumption. The non-option element of any electricity could then be sold on at a higher price in the open market. One point that comes out of this is that the aluminium producer would find the sale of optionality particularly attractive under conditions of higher implied volatility. The higher the implied volatility of the underlying electricity price, the higher the premium they would receive. The example illustrates that like most strategies, the selling of optionality is not completely risk free. One aspect not considered is if the indifference curve moved after the option transaction date, but before the expiry of the option. This could be because of a rise in aluminium prices, which for a given cost of power would push the producer towards selling the metal instead. One possible solution to this problem would be to create aluminium options that are contingent on the electricity price. One example of this type of transaction was considered is the two-asset barrier option, which was discussed in the chapters on gold and crude oil.

8.6.7

Ratio swap on power and aluminium

Power is a key input in the aluminium process and is arguably the most significant cost faced by a smelter. Conventionally, a smelter may decide to hedge the sale of their

322

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS Sale of physical aluminium

Floating price AL

Physical Aluminium Floating price AL

Fixed price AL Aluminium smelter

Fixed price PWR

Bank

Floating price PWR

Floating price PWR

Physical Power

Purchase of physical energy

FIGURE 8.11 Ratio swap. production and the power exposures separately. However, there is a risk that if the two hedges are not constructed to complement each other, then the smelter will suffer reduced revenues if one side of the transaction moves against them. One possible way to overcome this is by means of a ratio swap, which combines both elements. This is illustrated in Figure 8.11. The aluminium smelter sells their physical metal and receives the prevailing market price. This floating payment is then swapped for a fixed price under the terms of the swap. At the same time, they buy the power they require in proportion to the amount of metal that they wish to sell (e.g. 14 MWh of power for every 1 MT of aluminium that is sold). Again, this is paid for on a floating basis, but this expense is transformed into a fixed cost under the terms of the swap. In a perfect world the net impact of the swap is that all the floating payments cancel out and the smelter is left selling a given volume of metal and buying the required power at two fixed prices.

8.6.8

Monthly and daily power swaps

In the US market ‘power swaps’ are agreements to exchange a fixed price for the delivery of physical electricity in a particular region for a pre-agreed period. The use of the term ‘swap’ is potentially misleading as they are arguably more akin to a physically settled forward.

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A monthly power swap will fix the price for physical delivery in a particular region for a particular month. If a market participant were to execute a ‘PJM monthly July swap at USD 50.00/MWh’ then the buyer (i.e. the payer of the fixed rate) would pay USD 50.00 for every MWh of an agreed volume of electricity delivered in this location during the specified month. The agreement will typically settle just before the start of the applicable delivery month. A daily power swap works in a similar fashion, but, as the name suggests, it will cover the delivery of power in a particular region for a specified single day (e.g. 1 July). This transaction would settle the day before the scheduled delivery.

8.6.9

Options on power swaps

This type of option may also be referred to as a ‘power swaption’ and could be structured with either monthly or daily settlement. The underlying in this case would be either a monthly or daily power swap. Monthly swaptions A call on a monthly power swap would give the buyer the right to receive an agreed volume of electricity at a pre-agreed fixed strike price for a one-month period. Expressing this in conventional option payoff terms would be: Value of call at maturity = MAX (Underlying price − strike, 0) In this case the underlying price would be the prevailing price for a power monthly swap that covers the referenced month. Suppose that in the middle of a particular year a market participant buys the following option: Option maturity: Option type: Option style: Underlying: Market: Load shape: Delivery period: Volume: Total volume: Strike: Option premium: Settlement:

One-month option Call European Monthly power swap PJM Western Hub (Pennsylvania, New Jersey, and Maryland) Peak hours (07:00–23:00 - 16 hours, Monday–Friday) 1–31 July (excluding weekends, 23 working days) 100 MWh 36,800 MWh (100 MW × 16 hours × 23 days) USD 50.00/MWh (ATM) USD 5.00/MWh Financial settlement against CME Group ‘PJM Western hub, Peak calendar month future’

The key features are that it is a one-month option exercisable into a one-month delivery period that financially settles against an observable futures price. Note that the maturity of the option is relatively short. One of the reasons for this is that options that

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reference electricity will tend to trade at very high implied volatilities; values of over 100% are not uncommon. A monthly put swaption would work in a similar fashion although the expiry payoff would be: MAX (Strike − underlying price, 0) Again, it may well be financially settled, but economically the put buyer would ‘deliver’ power in exchange for receiving the strike price. Daily swaptions A daily swaption would have similar characteristics to the monthly structure. The main difference would be that the underlying would be a daily power swap. These transactions comprise of a series of daily options covering, say, a one-month period. In the monthly swaption structure there was a single option that covered 23 working days of a calendar month. An option structure that gives the holder the right of exercise on every one of those days means there are 23 individual options packaged as a single transaction. For readers who are familiar with financial markets, this is like the interest rate cap (i.e. call) and floor (i.e. put) markets. A cap (floor) that covers a predefined number of periods is made up of a strip of individual options called caplets (floorlets). Readers who require more information on this product are referred to Schofield and Bowler (2011). The economics of option pricing means that a single option based on our example of 23 days (a monthly swaption) has a lower premium than 23 options, each covering just one day (a daily swaption for an entire month). Intuitively with the single option structure there can only be one opportunity to pay out; the multi-option structure can pay out up to 23 times and will therefore cost more. Applications An electricity generator could sell put swaptions to boost their cash flows, albeit with some degree of risk. Diagrammatically, the economics of the transaction are shown in Figure 8.12. It is more of an aggressive transaction as can be seen from the associated cash flows, which are shown in Table 8.4. The option strike is USD 50.00/MWh, and the premium is assumed to be USD 5.00/MWh. If the market price for electricity stays above the strike price, the generator retains the premium and is not required to make a payment under the terms of the option. The premium then can be used to improve cash flow. However, once the option becomes in-the-money note that the net cash flow receivable by the generator falls rapidly. As the price of electricity falls, not only would they receive lower income from their sale of physical power, but also they are required to pay out under the terms of the option. One possible hedging application would be for a wholesale power distributor to buy call swaptions that would yield protection against a spike in wholesale prices that may not easily be passed onto their end clients. The call gives the holder the right to ‘buy’

325

Electricity Sale of put swaption

Sale of physical energy

Strike price

Market price Electricity consumer

Generator MWh

MWh

Premium

FIGURE 8.12 Sale of put swaption by electricity generator.

TABLE 8.4 Payoff profile for an electricity producer who has sold a put swaption. Income from selling physical power (USD/MWh) +60 +55 +50 +45 +40 +35 +30

Premium received from sale of option (USD/MWh)

Option payout (USD)

Net cash flow received (USD)

+5 +5 +5 +5 +5 +5 +5

0 0 0 −5 −10 −15 −20

+65 +60 +55 +45 +35 +25 +15

the underlying swap, i.e. pay fixed & receive floating. If prices were to increase sharply leading to an increase in the cost of their physical purchases, the floating leg of the swap would finance these higher payments. The distributor’s net cost of buying power would therefore be the swap’s fixed price. From a ‘view driven’ perspective, market participants could trade options to express views on the volatility of power as well as the volatility of the factors that determine power prices. These might include the prices of input fuels such as natural gas, coal, and weather. If they were looking to neutralise themselves against directional movements in the underlying price, the appropriate delta hedge would be a forward-starting swap. The remaining Greeks such as vega, gamma, and theta could be hedged using power options with alternative maturities or other delivery locations. Some traders choose to use options on natural gas to hedge these exposures as they are considered to have better liquidity. However, this introduces an element of basis risk as the trader would now be reliant on the correlation between gas and electricity prices remaining stable. Another interesting point is to appreciate that power swap prices may behave very differently depending on the region that they reference. For a region like PJM, which uses a wide variety of fuel types the swap price may vary considerably. Those regions that rely on a single fuel input such as natural gas may not experience the same degree of price volatility.

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8.6.10

Heat rate derivatives

Defining the heat rate Section 8.1.2 introduced the concept of thermal efficiency. This was a measure that related the electrical energy produced to the energy content of the input. So if 100 units of natural gas produced 47 units of electricity then the thermal efficiency was 47%. Stated as a formula: Electricity produced∕Energy content of the input A related measure is the heat rate, which measures the number of MMBTu needed for a marginal generating plant to generate 1 MWh of electricity4 . In general terms it is expressed as: Total input fuel used∕total energy produced Where natural gas is the input fuel the expression would be: Input energy (MMBtu∕hour)∕Output power (MW) So, the heat rate of a power plant expresses how much input fuel is necessary (measured in millions of British thermal unit) to produce one unit of energy (measured in megawatt hours). The heat rate is simply the inverse of thermal efficiency and so it follows that a lower heat rate indicates a higher thermal efficiency and therefore a more efficient generation system. Suppose that the energy input was 3,500,000,000 BTUs/hour and this produced 500,000 kW of energy. This would yield a heat rate of 7,000 BTU/kWh. This could also be expressed as 3,500 MMBtu and 500 MW to give a heat rate of 7 MMBtu/MWh. To illustrate the concept, consider the relationship between thermal efficiency and heat rates using the values suggested earlier. These examples are based on the convention that 1 kWh of electricity has an equivalent BTU content of 3,412. ▪ A thermal efficiency of 100% implies a heat rate of 3,412 BTU/kWh. ▪ A thermal efficiency of 47% (e.g. natural gas) implies a heat rate of 7,2660 BTU/kWh (47% = 3,412 / 7,260). ▪ A thermal efficiency of 35% (e.g. coal) implies a heat rate of 9,477 BTU/kWh (36% = 3,412 / 9,477). In the electricity trading markets heat rates are expressed in price terms: Price of electricity (USD/MWh) / Price of the generating fuel (e.g. natural gas in USD/MMBtu) However, the currency component cancels out and the result is again expressed as MMBtu/MWh. 4

The measure can also be reported as Btu/kWh.

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Electricity

Kaminski (2012) makes a useful distinction between the two measures. The ratio of the two market prices is termed the ‘market heat rate’ (also sometimes called the ‘implied heat rate’), while the ratio of the energy input to the power output is the ‘technological heat rate’. He argues that the technological heat rate of the marginal generator will determine the marginal cost of electricity in a particular market. For example, if coal is used instead of natural gas the technological heat rate will change, and since they trade at different prices, this may have an impact on the price charged for electricity. In a perfectly competitive market, the cost of power will be determined by the marginal cost of production so the technological heat rate would be equal to the market heat rate. He points out that the two measures will often diverge: ▪ Marginal cost will typically include an element for operational and maintenance charges, which would be ignored by the financial markets. ▪ If the generator has some degree of market power, they may be able to set prices above marginal costs. Spark spreads were introduced in Section 8.4.5 and in a simplified form they were calculated as: Price of power − (price of input fuel∕thermal efficiency) Given the relationship between thermal efficiency and the heat rate this relationship could also be expressed as: Price of power − (price of input fuel × heat rate) Price reporting agencies will often report market heat rates and to illustrate how these figures would look consider the following example based on day-ahead prices for electricity and natural gas. The example uses S&P Platts, North American electricity, methodology and specifications guide. ▪ Price of electricity = USD 39.75/MWh ▪ Price of natural gas = USD 2.89/MMBtu ▪ Marginal (e.g. market) heat rate = 13.75 MMBtu/MWh. This might also be reported as 13,754 Btu/kWh They also report spark spreads in USD/MWh: Electricity price (USD/MWh) −[natural gas price (USD/MMBtu) × heat rate (MMBtu/MWh)] The reported values use a variety of different heat rates depending on the regional market being analysed (e.g. 7,000, 10,000, 12,000, 15,000; all expressed as Btu/kWh). In our example, using a heat rate of 7 MMBtu/MWh this would give a spark spread of USD 19.49/MWh. (39.75 − (2.89 × 7))

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Heat rate options Although these instruments could be structured with coal as the underlying input fuel, the following examples are all based on natural gas. A European-style heat rate call option written on natural gas has a fixed heat rate strike. At maturity, this option gives the buyer the right but not the obligation to pay an agreed underlying price for natural gas multiplied by the fixed heat rate strike and receive the price of one unit of electricity. The payoff of a call option at maturity is therefore: MAX [(Underlying price of electricity − (Heat rate strike × Underlying price of natural gas)), 0] Comparing this expression to the calculation of the spark spread using heat rates indicates that this payoff represents a call option on spark spreads. A European-style heat rate put option written on natural gas has a fixed heat rate strike. At maturity, this option gives the buyer the right but not the obligation to receive the underlying price of natural gas multiplied by the fixed heat rate strike and pay the price of one unit of electricity. The payoff of the put option at maturity is therefore: MAX [((Heat rate strike × Underlying price of natural gas) − Underlying price of electricity), 0] A typical transaction may contain the following terms: Option buyer: Option seller: Option style: Option type: Maturity: Notional Quantity: Calculation period:

Total volume: Determination period: Monthly premium: Total premium: Premium payment:

Commodity A:

Client Bank European Daily heat rate call option One calendar year 100 MW per hour during each Calculation Period, equal to a total of 1,500 MWh for each calculation period. Daily (excluding weekends and holidays) covering the peak 15 hours of 8:00 to 23:00, Eastern Time. (Number of calculation periods in this example is taken to be 250 for ease of illustration). 375,000 MWh during the option term (1,500 MWh per calculation period × 250 days) Every month during the term of the option USD 11,000 USD 132,000 The option buyer will make a premium payment to the option seller, in arrears each month as part of the net settlement amount. Electricity

329

Electricity

Floating price A:

For each calculation period (i.e. daily) the arithmetic average of the day-ahead price for each hour as published by the ISO New England. Floating price B: For each calculation period: (Heat rate × Natural Gas price) + variable charge. The natural gas price will be the Henry Hub Natural Gas in USD per MMBtu. The Heat rate will be 7 MMBtu/MWh. The variable charge will be fixed at USD 3.50/MWh and accounts for the start up or maintenance costs of a plant. Net Settlement Amount: For each calculation period a settlement amount shall be calculated as follows:

MAX [(Notional quantity × (Floating price A − Floating price B)), 0] The settlement amounts for each calculation period (i.e. daily) during a determination period (i.e. monthly) shall be aggregated into a single net amount. In addition, the option premium payment will be included as a negative amount. If the figure is positive, the option seller will pay the option buyer. If the figure is negative the option buyer shall pay the absolute value to the option seller. The following calculations convey a sense of how the daily settlement amount would be calculated. The analysis aims to show the impact of relative price changes. For ease of illustration, the variable charge and the premium have been ignored and the calculation is based on a single unit of the underlying. We will assume that the current price of electricity is USD 35.00/MWh and natural gas is USD 5.00/MMBtu. The ratio of the two prices returns a ‘market heat rate’ of 7 MMBtu/MWh, which is equal to the strike, so the option is initially at-the-money. Day #1 – spark spread increases Average price of day-ahead electricity = USD 40.00∕MWh Price of natural gas unchanged at USD 5.00∕MMBtu Implied market heat rate (i.e.ratio of the two prices) = 8 MMBtu∕MWh Settlement amount = MAX ((40 − (7 × 5)), 0) = USD 5.00 Day #2 – spark spread unchanged from original value Average price of day-ahead electricity = USD 35.00∕MWh Price of natural gas unchanged at USD 5.00∕MMBtu Implied market heat rate (i.e.ratio of the two prices) = 7 MMBtu∕MWh Settlement amount = MAX ((35 − (7 × 5)), 0)

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Day #3 – spark spread decreases from original value Average price of ‘day-ahead’ electricity = USD 30.00∕MWh Price of natural gas unchanged at USD 5.00∕MMBtu Implied market heat rate (i.e. ratio of the two prices) = 6 MMBtu∕MWh Settlement amount = MAX ((30 − (7 × 5)), 0) From this analysis it follows that: ▪ The payoffs shown above would have to be multiplied by the notional quantity (i.e. 1,500 MWh for each day). ▪ This type of calculation will be performed on each applicable day (the ‘calculation period’). ▪ If the variable charge were to be included with the input cost of the natural gas, then the option payout would be reduced further. At the end of the month (‘the determination period’), each daily calculation would be summed and the monthly premium payable by the option buyer subtracted. A positive sum means seller pays buyer; a negative sum means buyer pays seller the absolute value as the option has expired out-of-the-money and the payment made represents the premium due. Hedging applications A heat rate option is designed to mimic a generation asset. Market implied heat rates can vary considerably depending on the location. If a particular region has capacity to use different fuel types (e.g. nuclear, natural gas, coal) then the market heat rate will change as the source fuel changes. It follows that regions that rely mainly on a single source of fuel (e.g. natural gas) would have a less variable heat rate. A generator could buy a put option on the heat rate which would pay off if the spread between the two fuel prices were to decrease. The fall in their physical operating margins would be offset by the option payout. Another possibility would see the generator selling OTM call options. If the spread between the two prices were to increase, this would represent an increase in their physical operating margins. However, once prices move beyond the strike they would be faced with an increasing payout on the option, which would negate any additional profit. Typically, the strike rate of the option should be set at such a level that its exercise would be unlikely. However, the further away the strike rate from the current value, the lower the premium the generator would earn. View driven applications This type of option is an example of a spread option, and so there is a correlation exposure between electricity and whatever input fuel is chosen. The buyer of a call on the spread will see their option increase in value if the correlation between electricity and

Electricity

331

natural gas were to decrease. This would suggest that the two prices would move in opposite directions making a payoff more likely. From a valuation perspective, a current correlation value could be inferred from other traded heat rate options. If such options do not exist, then a value can be derived using historical forward prices from the two underlying fuels. The use of options would be preferable as the value derived would be an implied, forward-looking correlation figure; the use of forwards returns a historical value. Typically, longdated correlation figures tend to be relatively high because the two fuels will be impacted by similar fundamentals. The correlation for shorter-dated transactions can be lower as physical issues such as transmission problems and weather will impact prices. Like all other options, there are several Greeks that a trader will need to manage. With respect to the delta, this could be hedged by trading the underlying forwards (‘swaps’). Greeks such as vega, gamma, and theta can be hedged using other heat rate options, but it is also possible to use individual options on gas or electricity if the trader believes they offer greater liquidity.

CHAPTER

9

Plastics

9.1

THE CHEMISTRY OF PLASTIC

‘Plastic’ is a general term used to describe different chemical structures. At a very basic level, plastics are formed when carbon and hydrogen atoms are combined in different ways. Groups of atoms bonded together form molecules which, when linked together in different ways, yield plastics that have different physical properties. Hydrocarbons (i.e. molecules of hydrogen and carbon) are classified as either monomers or polymers. A monomer (mono = one) is a building block molecule, which could be chemically reacted to make molecules with longer chains. A polymer (poly = many) is a number of individual monomers chemically joined by a bond to form a single structure. For example, the simplest of plastics is polyethylene (sometimes referred to as polythene), which is made up of ethylene/ethene1 monomers (Figure 9.1). Chemically, the ethylene monomer is expressed as: H C H

H C H

FIGURE 9.1 Chemical structure of an ethylene (a monomer). Where: C = Carbon atoms H = Hydrogen atoms An ethylene molecule has two carbon atoms, which are joined by a double bond. Double bonds are relatively easy to break allowing a new atom or molecule to join the original structure. 1

Ethylene and ethene are different terms used to describe the same chemical structure. Differences in their usage may occur on a geographical basis. The slightly old fashion term of ethylene will be used throughout the text.

332

333

Plastics

When it is chemically reacted with other ethylene molecules a polymer chain is formed to make polyethylene (Figure 9.2). Chemically polyethylene is written as [C2 H4 ]n where the subscript n is used to denote an integer that determines the length of the polymer chain.

*

H

H

C

C

H

H

* n

FIGURE 9.2 Chemical structure of polyethylene (a polymer). Where: C = Carbon atoms H = Hydrogen atoms n = an integer that determines the length of the polymer Although hydrogen and carbon are the two main building blocks, other elements (such as fluorine, chlorine, iodine, and bromine) can be added to the monomer conversion process to change the physical characteristics of the resultant polymer. For example, at the monomer level if chlorine were to replace one of the hydrogen atoms in ethylene, the result is chloroethene (vinyl chloride), which is C2 H3 Cl. After polymerisation, it will form Polyvinyl Chloride or PVC, which has a higher tensile strength but a lower melting point than polyethylene. Because there are thousands of different hydrocarbons it is often convenient to divide them into categories. One such category is alkenes of which ethylene is an example. Alkenes generally have a simple chemical structure, are cheap to make, and are relatively easy to polymerise. Alkenes are also sometimes referred to as ‘olefins’ and their polymers (such as polythene and polypropylene) ‘polyolefins’.

9.2

THE PRODUCTION OF PLASTIC

In the previous section we described the chemical composition of polyethylene and its main monomer building block, ethylene. Here we will describe the main sources of ethylene and how plastic is produced. Plastics can be manufactured from a variety of hydrocarbons, which are extracted from either crude oil or natural gas. There are a variety of hydrocarbons that can be used in plastic production which include: ▪ Ethylene – C2 H4 ▪ Propylene – C3 H6 ▪ Butene – C4 H8 The most common building block is the monomer ethylene introduced in the previous section, which can be derived from either crude oil or natural gas.

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9.3

MONOMER PRODUCTION

9.3.1

Crude Oil

Crude oil has very limited applications by itself and so is refined to produce a variety of products. Chemically, crude oil is made up of many different hydrocarbon structures that are then separated (using a process known as fractional distillation) into different components denoted by the length of their carbon chains. Examples of refined short chain molecules are ethene, propene, and butene, which are also monomers that can be used to make plastic. Longer chain carbon molecules such as naphtha can also be used as part of the plastic production process. Naphtha can then be broken up (using a process known as steam cracking) to yield a number of different products such as high-grade petrol and ethylene.

9.3.2

Natural Gas

Once extracted from the ground natural gas will be processed to remove any impurities and then separated into its component elements, referred to collectively as Natural Gas Liquids (NGLs). These include: ▪ ▪ ▪ ▪ ▪

Ethane Propane Methane Butane Pentane

Once the ethane (C2 H6 ) is collected it is steam-cracked to produce ethylene. This is then polymerised to become polyethylene, which is sometimes referred to as polyethene or simply polythene. However, there is a trade-off between the two routes to produce ethylene. Producing ethylene from natural gas is cheaper but yields a smaller amount; producing ethylene from crude oil is more expensive but returns a higher yield. Geographical access to the raw materials has also played a role. Where low cost access to natural gas is possible it is usually the feedstock of choice for the production of ethylene and polyethylene.

9.4

POLYMERISATION

The next step is polymerisation, which involves reacting ethylene with a catalyst. The choice of the catalyst at this point will impact the final polymer produced as it restructures the bonds that link the carbon and hydrogen atoms. The resultant polymer will be in the form of: ▪ ▪ ▪ ▪

Pellets Film Resin Powder

Plastics

9.5

335

APPLICATIONS OF PLASTICS

Once a particular polymer has been made it has to be fabricated into a final usable product for purchase by a consumer. Listed below are a number of well-known polymers with examples of some of their day-to-day applications: ▪ Polyethylene (PE) – Low Density Polyethylene (LDPE) is used for food bags and squeeze bottles. High Density Polyethylene (HDPE) is used for detergent bottles, refuse bags, and shopping carrier bags. The term linear simply refers to the fact that the carbon atoms are ordered in a straight line, which results in a polymer that takes up less physical space. ▪ Polypropylene (PP) – when rigid it can be used for caps and other closures, when in flexible form used for films for confectionary and tobacco. ▪ Polyethylene Terephthalate (PET) – used for soft drink containers, squeeze bottles and oven safe food trays. ▪ Polyvinyl Chloride (PVC) – thin films, clothing, bottles, and cartons. ▪ Polystyrene (PS) – compact disc cases, cartons, and medicine bottles. ▪ Polyterafluoroethylene (PTFE) – which has non-stick applications used for such items as kitchenware. Once formed, a polymer is said to be thermoset or thermoplastic. The term ‘thermo’ refers to the effect of heat while the terms ‘set’ and ‘plastic’ refer to how the polymer reacts to the heat. A polymer described as a thermoplastic is one where the application of heat will cause the product to change shape, but will not lead to any change in its chemical composition. This would allow the material to be remoulded back into its original shape or may allow for recycling. Examples of this are polythene and nylon. A polymer that is described as being a thermoset is where the application of heat alters not only the shape but also its chemical composition. This means that once it has been melted it cannot be remoulded and will solidify irreversibly – it is ‘set’. Examples in this category include polystyrene and PTFE. Thermoplastics, which constitute the greater demand of the two categories, can be converted into a final product using a number of processes that include: ▪ Injection moulding – the plastic is fed into a heated chamber whereupon it softens into a fluid. It is then injected into a mould and cooled so it solidifies. The mould is then removed, and the object can be removed. This technique is used in the production of butter tubs and yoghurt containers. ▪ Blow moulding – here molten plastic in the shape of a tube is formed. Using compressed air, the tube is then blown to fill the insides of a chilled mould. This method is used to make items such as bottles or tubes. ▪ Extrusion – in this process the plastic is heated in a chamber and then when in molten form is pushed through an opening called a die. The shape of the opening will allow the plastic to cool and set in a particular form. Some polymers may undergo further processing once they are formed to give them specific qualities that are suited to specific jobs. For example, rubber can be vulcanised (i.e. heated with sulfur) to make it stronger and more resistant to heat.

336

9.6

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

SUMMARY OF THE PLASTICS SUPPLY CHAIN

When considering the structure of the plastic production process, broadly speaking there are two different types of producer. An example of an integrated producer would be a large oil major that can extract crude oil or natural gas and then send it for refining. After refining the manufacture of monomers and polymers will follow. A nonintegrated producer would be a buyer of the monomer and would then produce a particular type of polymer. From that point a converter will purchase a particular polymer either directly from a producer or from a distributor and then manufacture an end product for use by an end consumer. Traders will act as a counterparty to different entities in the physical supply chain to facilitate the purchase and sale of different polymers and to offer a variety of risk management services.

9.7

PRICE DETERMINATION

In May 2005, the London Metal Exchange (LME) launched two futures contracts in an attempt to make plastics a tradable commodity. The LME initially listed two different types of contract, polypropylene (PP) and linear low-density polyethylene (LDPE) since at the time these two commodities accounted for about 40% of the thermoplastics market. In the years that followed the LME made a number of changes to the contract to increase the degree of interest from participants along the supply chain. However, the contract was delisted in April 2011 as the exchange was unable to establish any significant volume or open interest. Recall that a futures exchange has three principal roles: 1. A central reference point for the pricing of commercial contracts for the underlying commodity. 2. Provides a series of instruments that allow participants to hedge an underlying exposure. 3. Provides participants with a source of supply for the underlying commodity or allows them to dispose of any excess inventory. One feature of commodity products where no traded market exists is the absence of a transparent method for pricing commercial contracts. Plastics are an interesting case study as they illustrate the role of benchmark indices and their adoption by the market. For an industry to accept a benchmark index it must be: ▪ ▪ ▪ ▪

Transparent, Representative of the most liquid market, Used by a high number of varied market participants along the supply chain, Based on actual trades executed rather than prices quoted.

Since the demise of the plastics futures, commercial transactions have been valued using indices such as IHS Markit and PetroChem Wire (PCW).

Plastics

9.8

337

PLASTIC PRICE DRIVERS

In many respects, the market factors that influence the price of plastics share much in common with those that influence commodities generally. Since crude oil and natural gas play a significant part in the production of plastic, the price factors that influence these commodities will also be important. The key price drivers for the market include: Cost of crude oil and natural gas – Since the basic feedstock in the production process is crude oil or natural gas, the final price of plastic will be heavily influenced by price movements in these sectors. Environmental concerns – Very often the proposed construction of a new petrochemical site in a particular location raises issues surrounding the impact on the environment. This may delay the building of a new facility and add further to any existing capacity constraint. Recycling – Traditionally, plastics have not been easy to recycle, as they are often complex and composite materials. However, investment in new technologies has increased as a result of public concern over single-use plastics and the perceived pollution. For example, in 2015 the UK introduced a small nominal charge of 5p for disposable grocery-style plastic bags, which led to a decline in their usage of about 90%. According to The Independent (2019) the average English shopper now uses just 10 bags a year compared to 140 before the charge came in. For plastics that can be recycled, the bags will act as an extra source of supply. Typically, plastic waste is collected from households and recycling bins. It is then taken to a recycling centre where the plastic is sorted into different grades. Each type of plastic is then washed and decontaminated. The plastic is then shredded into flakes which are heated and turned into pellets. These pellets are then sold to manufacturers to make new containers. Production capacity – If a commodity experiences a sharp increase in price, economic theory tells us that production should respond accordingly. What this does not take into account is the fact there may often be a substantial time lag if there is a need to expand any existing facilities. Lack of production capacity could include not only refining of crude oil or natural gas but also polymerisation. One concept that links some of the price factors together is the regional cost of the feedstock relative to the available capacity. Since hydrocarbons are cheaper to produce in the Middle East, there is expected to be a gradual trend to locate new refining and polymerisation plants in this region. Given the difficulty of building the equivalent facilities in the West it would seem that reliance on the Middle East for energy is only likely to increase. Production disruption – This could be due to a variety of reasons such as natural disasters or labour disputes. For example, hurricanes on the US Gulf Coast have on occasion caused the shutdown of production facilities with US demand being met by imports from other regions such as Asia. Economic cycle – If the economy is experiencing a boom period then there will be a general increase in production with an associated uplift in the demand for plastics. Level of existing inventories – If prices are rising due to increased demand and production has been unable to respond immediately the excess has to be met through existing inventories.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Technological progress – As technological improvements have taken hold, the possibility of substituting plastic for other materials has increased. For example, in the beverage industry, cans have gradually been replaced by PET containers, which have become lighter, stronger and more tolerant to heat. Strength of the US dollar – Similar to most commodities, plastics are quoted in USD. A strengthening dollar will make plastics relatively more expensive in domestic non-dollar currency terms and vice versa. Emerging markets demand – Again similar to most metals, the rapid economic expansion and the associated increase in demand of countries such as China and India will have a significant bearing on the price of the commodity.

9.9

FORWARDS AND SWAPS

The process of hedging allows an entity to protect the economic value of some underlying exposure. Section 9.6 outlined a simplified physical supply chain for the plastics industry. In the absence of a liquid futures market it is still possible to trade OTC forwards, swaps, and options, which can be used at each stage of the lifecycle. Table 9.1 provides a recap of the supply chain, the nature of the price exposure and whether the participant is likely to be a forward buyer or seller. Reference is sometimes made to ‘price fixing hedges’ and ‘offset hedges’. A price fixing hedge will be a transaction that is not linked to a specific underlying exposure and is designed to alter the overall ‘macro’ price risk of a commercial enterprise. On the other hand, an offset hedge will be based on a specific transaction and can be thought of as a micro hedge.

Price fixing hedge The manufacturer of any product may be faced with a situation where the required raw materials may not be priced until their actual receipt. This means the company is exposed to a possible change in its profit margins. As a pre-emptive action, the manufacturer could buy on a forward basis using a contract whose maturity coincides with the pricing date for the underlying commodity. Since the forward is not being used as a source of supply, the derivative transaction could be closed out by taking an equal and opposite position shortly prior to maturity. Say that a manufacturer of plastic water bottles has an ongoing need to buy linear low-density polyethylene. He does not feel he is able to pass on any extra costs to the end user of the water bottles and so decides he need to lock in costs in order to maintain his margins. Looking at the prices in early March, he notes that a June forward contract is trading at USD 1,185/tonne and so decides to buy one forward at this price. Let us assume that the manufacturer decides to close out the position at the end of May when the price for June delivery is at USD 1,250/tonne. Having bought the forward at USD 1,185 and sold it at USD 1,250, the manufacturer has made a profit of USD 65.00/tonne. If the purchase of the physical product had also been based on the same agreed index price then as of

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Plastics

TABLE 9.1 Price exposure and futures strategies for the plastics supply chain. Supply chain role

Polymer price exposure

Forward transaction

Polymer producer Converter Distributor End consumers Traders

Falling prices Rising prices Falling & rising prices Rising prices Falling and rising prices

Sell forward Buy forward Sell/buy forward Buy forward Sell/buy forward

the end of May the net cost to the manufacturer would be USD 1,250 less the USD 65.00 dollars profit per tonne on the forward. That gives a net cost of USD 1,185, which is equal to the price of the original purchased forward. The hedger can also simultaneously execute a series of forward contracts for delivery in sequential months, if they know there will be a regular underlying physical exposure. This is described as a strip of contracts. An alternative to a strip would be to enter a classic fixed-float swap. If the manufacturer is buying the raw materials and is paying the prevailing market price, then a multi-period swap contract would see them receiving floating and paying fixed. The floating leg of the swap will offset their floating payment made to purchase the underlying commodity and they would then be left with a net fixed cost courtesy of the fixed leg of the swap. Some market participants would describe this as ‘buying’ the swap, which means paying the fixed rate. The author is not a great fan of this terminology as it can be somewhat ambiguous and is often not properly defined in customer confirmations.

Offset hedge An offset hedge is where the forward is used to protect the value of a specific transaction. Let us assume that a distributor has agreed to sell some PP in two months’ time. The distributor has agreed a fixed sale price with the end customer. The distributor is not obliged to hedge this exposure but runs the risk that the cost of the raw material will rise prior to the promised delivery, eroding any profit margin. As a result, they decide to buy a forward at the current price. As long as the forward can be traded at a price less than the fixed sale price with the end customer, they will be able to lock in their margins.

Proxy hedges In the absence of a liquid market for hedging, some alternative markets could be used as proxy hedges. Suppose that a clothing manufacturer buys a large amount of polypropylene each year and is looking to hedge their costs. In the absence of a liquid market for the underlying, it may be possible to look at alternative commodities that might offer a partial solution. For example, if it was found that natural gas or crude oil prices displayed a significant correlation with polypropylene, it may be possible to structure a hedge solution using these related commodities. However, it is important to realise

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that the concept of a ‘perfect hedge’ does not exist and it is possible that any historical correlation relationship may break down when markets are stressed.

9.10

OPTION STRATEGIES

Recall one of the earlier comments made about derivative valuation: ‘if you can hedge it, you can price it’! That is, the cost of any derivative is driven by the cost of hedging any underlying exposure. At the time of the launch of plastics contracts, the LME did not implement an option contract. Their argument was that they wanted liquidity to develop in the underlying futures market such that an option trader would have the means to hedge their directional option exposure. Since the futures market never matured, options on this asset class will likely remain relatively illiquid. The main option exposures are ‘delta’ (the direction of the underlying price) and ‘vega’ (the implied volatility). One way of hedging these exposures in the absence of a liquid futures market is by the use of proxy hedges. For example, if the trader believed that there was relatively stable correlation between natural gas and oil with the underlying plastic exposure they are looking to hedge, they could use futures and options on these assets as an alternative hedging mechanism. It will not be a perfect solution but in reality, it is rare to find a situation where a hedge will be 100% perfect. Rather than repeat material covered elsewhere, the interested reader is referred to the gold and base metals chapters for a discussion of different over-the-counter option strategies. The chapter on gold reviews option strategies from a producer perspective, while the section on base metals focuses on consumer transactions.

CHAPTER

10

Bulk Commodities

T

his chapter brings together several related markets, which are sometimes collectively referred to as ‘bulk commodities’. Typically, these products (e.g. coking coal and iron ore) have a unifying characteristic in that they form part of the steel supply chain. In the freight market, about 60% of Capesize vessels are used to transport iron ore. The Singapore futures exchange (2019) claims: ▪ In tonnage terms, the global steel market is about 20 times larger than all other metal markets combined. ▪ Approximately 98% of iron ore is used in the production of steel. ▪ 15% of global coal consumption is used in steel making in the form of coking coal. ▪ China makes up about two-thirds of seaborne iron ore demand. ▪ Most iron-ore reserves are found in Australia, Brazil, and Russia. Market participants do not always accept this definition of bulk commodities. For example, institutions that have a focus on consumers, their iron ore desks may well sit within the base metals function. But for an entity that serves producers, putting coal, iron, and freight into a single unit may make sense. This chapter considers the markets for coal, iron ore, and freight. Steel markets are described in Section 5.4. Bulk markets can also include alumina, bauxite, and grains, but these topics are considered elsewhere.

10.1

THE BASICS OF COAL

‘Coal’, like crude oil, is a general term that is used to describe different types of a particular commodity. The World Coal Institute (WCI) defines coal as: ‘ . . . a combustible, sedimentary organic rock, which is composed mainly of carbon, hydrogen and oxygen. It is formed from vegetation which has been consolidated between other rock strata and altered by the combined effects of pressure and heat over millions of years to form coal seams’. The International Energy Agency (2006) defines coal in a different manner, categorising it as either hard coal or brown coal. ‘Hard coal with a high thermal value . . . is economically suited to international trade, with characteristics making some coals

341

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suitable for metallurgical (coking) uses. Brown coal (lignite) has a much lower thermal value . . . and is suitable mainly for power generation locally or to a lesser extent for briquette manufacture’. The type of coal recovered depends upon the length of time that it has spent in formation, as well as the temperature and pressure to which it has been subjected. Often coal is classified as being either low or high rank, each of which will have different properties. High rank coals encompass anthracite and bituminous coals. These coals will have a higher energy and lower moisture content. Domestic and industrial consumers use anthracite, which makes up about 1% of the world’s reserves, primarily for heating purposes. Bituminous coals (52% of the world’s reserves) can be broken into two main types: thermal or ‘steam coal’ and metallurgical or ‘coking coal’. Thermal coals are used in power generation and cement manufacture, while metallurgical coals are typically used in the manufacture of iron and steel. Coking coal is used in coke ovens to produce coke, which is used in blast furnaces to produce pig iron. Coking coal is harder than thermal coal and consequently trades at a premium. Lower rank coals include lignite (‘red coal’) and sub-bituminous coals. They have a lower energy and higher moisture content. Applications of lignite include power generation, while sub-bituminous coals are used in power generation and cement manufacture. This breakdown is shown diagrammatically in Figure 10.1.

Lower

Carbon/energy content of coal

Higher

Higher

Moisture content of coal

Lower

Coal type

Low rank coals (47%)

Lignite (17%)

Power generation

Hard Coal (53%)

Sub-bituminous (30%)

Power generation Cement manufacture Industrial uses

Bituminous (52%)

Thermal (Steam Coal)

Power generation Cement manufacture Industrial uses

FIGURE 10.1 Different types of coal and their applications. Source: Author, World Coal Association

Anthracite (~1%)

Metallurgical (Coking coal)

Manufacture of iron and steel

Domestic/ industrial

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Bulk Commodities

10.2

THE DEMAND FOR AND SUPPLY OF COAL

Despite environmental concerns, coal is still a popular source of energy. Figure 6.1 showed the primary energy supply by fuel as of the end of 2019 and illustrates that coal accounts for 27% of consumption, second only to crude oil. According to the World Coal Association: ▪ ▪ ▪ ▪

41% of global electricity is fueled by coal-fired power plants. 70% of all steel production uses coal. 200 kg of coal is needed to produce one tonne of cement. 50% of the energy used to produce aluminium comes from coal.

The following chart (Figure 10.2) shows the proportion of proved reserves for coal by region. BP defines the R/P ratio (reserves to production ratio) as reserves remaining at the end of any year divided by the production in that year. The result being the length of time that those remaining reserves would last if production were to continue at that rate. Regional R/P ratios are shown in Figure 10.3. Figures are for commercial solid fuels only, i.e. bituminous coal and anthracite (hard coal) and lignite and brown (sub-bituminous) coal. Figure 10.4 shows how the nature of coal production has evolved since 1981 indicating its ongoing popularity.

North America 24.10%

Asia Pacific 42.70%

S & Cent. America 1.30%

Europe 12.60%

Middle East and Africa 1.50%

CIS 17.80%

FIGURE 10.2 Regional coal reserves. Source: BP Statistical Review of World Energy 2020. BP PLC.

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Middle East and Africa

57

Asia Pacific

77

S. and Cent. America

152

Europe

244

CIS

338

North America

367 0

50

100

150

200

250

300

350

400

FIGURE 10.3 Reserves to production ratio. Horizontal axis is years. Source: BP Statistical Review of World Energy 2020. BP PLC. 180 S & C America Africa Europe CIS N America

160 140 120 100 80 60

Asia Pacific

40 20 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

0

FIGURE 10.4 Regional production of coal in exajoules, 1981–2019. Middle East is not included due to relative size. Source: BP Statistical Review of World Energy 2020. BP PLC. Figure 10.5 shows the regional consumption of coal expressed in million tonnes of oil equivalent. According to the IEA (2019) the four largest exporters of thermal coal (in descending order) are: ▪ ▪ ▪ ▪

Indonesia (435 MT) Australia (203 MT) Russia (173 MT) Colombia (81 MT) While the four largest exporters of coking coal (in descending order) are:

▪ Australia (179 MT) ▪ USA (56 MT)

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Bulk Commodities 180

S & C America Africa Europe CIS

160 140 120

N America

100 80 60 40

Asia Pacific

20

19

65 19 67 19 69 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 20 09 20 11 20 13 20 15 20 17 20 19

0

FIGURE 10.5 Regional consumption of coal in exajoules. Middle East is not included due to relative size. Source: BP Statistical Review of World Energy 2020. BP PLC. ▪ Canada (29 MT) ▪ Russia (26 MT) The main destinations for both types of coal are: ▪ ▪ ▪ ▪ ▪

China (295 MT) India (240 MT) Japan (185 MT) South Korea (142 MT) Chinese Taipei (66 MT)

Figure 10.6 illustrates the movement of the price of steam coal over the period 1983 to 2005 for five major markets (average export unit values in USD per tonne). 250.00

200.00

150.00

100.00

50.00

0.00 1987

1989

1991

1993 NWE

1995

1997 US

1999

2001

2003

Japan – coking

2005

2007

2009

Japan – steam

FIGURE 10.6 Coal prices 1987–2019. Source: BP Statistical Review of World Energy 2020. BP PLC.

2011

2013

2015

Asian marker

2017

2019

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The growth in the production and consumption of coal has been fueled by the following factors: ▪ Increased demand for energy globally. ▪ In some regions coal is cheaper per kilowatt-hour than competing energy sources such as natural gas and crude oil. ▪ The fuel is relatively safe to transport and costs less to move than oil or natural gas. ▪ There are substantial reserves available. According to the BP Statistical Review of World Energy 2020, coal had a reserve to production ratio of 132 years, compared to 49.9 and 49.8 years for crude oil and natural gas, respectively.

10.3 10.3.1

COAL – THE PHYSICAL SUPPLY CHAIN Production

The two methods of extracting coal are by underground or surface (open cast) mining. Although more coal can be recovered from a given deposit by surface mining, most of the coal is extracted from underground mines. Like most commodities that are extracted from the ground it will not be in a form that will be immediately usable. Depending on the physical form of the coal upon its extraction, it may require crushing to make the product physically manageable. The coal is also cleaned and will have any impurities removed. Inevitably the coal will have to be transported to its final location, which could involve a variety of different transport modes depending on the distance to be travelled and the final delivery location. These include: ▪ ▪ ▪ ▪

Lorries Trains Barges Ships

10.3.2

Main participants

The main participants in the coal supply chain and their associated risk management concerns include: Mining companies – Large companies will use risk management solutions to add value to their operations and will tend to trade in significant volumes. Other mines may be looking for financing solutions often linked to coal prices and FX movements. Utilities – These tend to be power-generating companies that operate coal-fired power stations. They may have a preference to use financially settled derivative transactions so they can separate out the physical delivery from the associated price risk, which can exhibit substantial volatility. With the increasing concern over emissions trading they must also consider the cost of emitting carbon. Non-physical participants (e.g. banks and trading houses) – Their trading activity with other financial desks creates liquidity for the market, thereby facilitating the development of risk management solutions. Equally, banks that have a trading capability will

Bulk Commodities

347

be able to offer a hedging solution to other lending banks that wish to offer risk management solutions to their clients without the need for a trading desk. Banks with a trading desk can also offer a mechanism for other banks to offset the market risk inherent within the issuance of commodity-linked investment structures. Industrial companies – Cement producers are major coal consumers, and the cost of the raw material can contribute a significant amount to their overall costs. Steel producers use coking coal but financial markets only trade thermal coal. This is the best available hedge but is not perfect in that the hedger has an exposure to basis risk (i.e. the risk that the price of the two commodities does not move in the same direction).

10.3.3

Factors affecting the price of coal

Steam coal is not a homogeneous product and as such several benchmarks have evolved based on standardised specifications surrounding the ash, sulfur, and energy content. The main pricing locations from which indices have evolved: ▪ ▪ ▪ ▪ ▪

Central Appalachia (USA) Powder River Basin, Wyoming (USA) Europe ARA (Amsterdam, Rotterdam, Antwerp) Richards Bay (South Africa) Newcastle (Australia)

Not all these locations, however, are traded internationally. Electricity industry – Since electricity represents one of the largest uses of coal, an increase in the electrification of a country (e.g. India) will have an impact on price. Although in this instance it may be tempting to suggest that the same would be true of China, this is one instance where China has abundant reserves of coal, which it can use to meet this demand. Planned capital expenditures, for the building of new coal-fired power generating facilities, will influence perceptions of the future balance between demand and supply. Electricity production margins – The main fuels used to produce electricity are natural gas and coal. If the price of natural gas rises relative to coal, then it may encourage producers to switch. With the advent of allowances for installations that emit carbon dioxide, the cost of polluting now must be taken into consideration. This cost is now also expressed in terms of the ‘dark spread’ and ‘clean dark spread’. Technology – Because of the increased environmental concerns, much money has been spent on improving the performance of coal at the point of consumption while aiming to reduce the undesirable environmental side effects. The efforts to clean coal either involve the way in which it is prepared prior to its consumption or by fitting equipment to power stations to reduce undesirable emissions such as sulfur. Another focus of the technology has been to increase the thermal efficiency of coal by fitting more efficient boilers that reduce the carbon dioxide emissions. Environmental issues – Coal is perceived as a significant polluter of the environment and any associated regulation that may hinder its production or consumption could have an adverse effect on its market price. Methane, which is formed alongside coal, is released when the coal is mined, and is classified as a greenhouse gas. Additionally,

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when coal is burnt it releases pollutants such as carbon dioxide, ash, and oxides of sulfur and nitrogen (SOx and NOx ). Freight costs – Although not all coal is traded internationally, the price of coal will be influenced by the cost of transport to an end location. Economic expansion – As an economy expands there may be an increase in the demand for coal. Take for example, the economic expansion of China, which has led to an increase in the demand for steel. This has led to an increase in demand for coking coal to fuel the blast furnaces used in the production process. Coal quality - The heat and sulfur content are considered the primary determinants of steam coal. For example, coal mined from the Powder River Basin in Wyoming is more popular with utilities as it has a lower level of sulfur. Combined with the fact that it is mined from open cast pits, it is cheaper and cleaner than coal extracted from the Appalachian Mountains. One of the main value drivers of coal is its calorific value. Like the concept of a crude oil assay, a sample of coal needs to be checked in laboratory conditions to ensure that it is in line with the specifications defined in a contractual supply agreement. Although the calorific value of coal is affected by several factors, the amount of the moisture in the coal will impact the measure. Some coal contract specifications include the terms ‘net as received’ (NAR) and ‘gross as received’ (GAR). When coal is quoted on a GAR basis the associated calorific value (sometimes known as the upper heating value) is the gross calorific value obtained under laboratory conditions after all the moisture has been removed. Quoting on a NAR basis refers to the net calorific value obtained in boiler plants and is known as the lower heating value. The difference between the two would be the heat of the water vapour produced. Mining related issues – Since coal is extracted from the earth, there are several factors that could influence the price of coal. These were outlined in the chapter on base metals and include: ▪ Capital expenditure ▪ Production disruption ▪ Production costs Whether the coal is mined from open cast or underground sites will influence the cost and drive the economics of production. Reserves that are deep underground are less economical to mine. In some countries such as Russia the coal may need to be transported over significant distances to reach the final point of consumption. Related to this is the availability of logistics at the points of loading and discharging. Equally, since coal is often shipped by rail, derailments and subsidence on the line may have an impact on supply. Competing fuel costs – Liquefaction is the process whereby coal is transformed into a liquid. The resultant liquid fuel can be refined to produce fuels or other oil-based products such as plastic. This conversion will become more attractive as prices for crude oil rises. In a similar vein gasification converts coal into synthetic gas, which can then be used by power stations to generate electricity. Coal, water, and oxygen are mixed in an asifier, which acts like a high-pressure cooker. The combination of heat and pressure

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349

chemically breaks down the coal to produce synthetic gas, while impurities such as sulfur are removed. This ‘syngas’ can be burnt to drive a gas turbine to produce electricity. As an undesirable side effect, the gasification process produces carbon dioxide, but technology is evolving to capture this and bury it underground. Although coal is still used in the production of electricity, the increase in the availability of natural gas (and its resultant price fall) could lead to some electricity generators switching away from coal. However, since natural gas is more of a regionally traded product, an electricity generator in a country with low natural gas reserves would be reliant on supplies of LNG. Influence of non-physical participants – The entrance of banks, hedge funds, and institutional investors could be significant. An increase in investment interest could result in an upward influence on the price, while the trading activities of the banks and hedge funds could provide enhanced liquidity with respect to the provision of risk management structures for the physical supply chain.

10.4

COAL DERIVATIVES

Estimates of the size of the coal market vary but one crude method of assigning a monetary value is to take the volume produced each year and multiply it by the prevailing market price. Using a 2019 production figure of 8.1 billion tonnes1 and a market price of about USD 60.00/MT, this would imply a value of USD 486 billion. The derivatives market for coal is a fraction of this amount with notional values totaling about USD 100 billion. In most derivative markets, this figure would be a multiple of the physical market, suggesting that the coal market is relatively illiquid. Most transactions are financial swaps, but vanilla options are also traded. Financial Coal swaps have been trading in the OTC markets for about fifteen years. There are several different indices traded in the markets reflecting the key locations for seaborne thermal coal. The locations are either sources of coal (South Africa and Australia) or a consuming location such as Europe. Examples of popular indices include: ▪ API2 – This is a CIF (cost, insurance, freight) price for delivery in Rotterdam, which is an average of certain prices and is published by Argus and IHS McCloskey. This is a benchmark for the Atlantic coal market. ▪ API4 – This is a FOB (free on board) price for delivery from Richards Bay, South Africa. This index derives its value from prices quoted by Argus and IHS McCloskey. This is a benchmark for the Pacific coal market. ▪ GlobalCoal NEWC index – this price relates to coal originating in Newcastle, Australia. Within the context of the coal market, API does not refer to the density of the material but simply stands for average price index. This reflects that the index is compiled from several different observations and the final price is a simple average of these 1

BP Statistical Review of World Energy 2020.

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prices. The number (i.e. 2 and 4) that follows the acronym has no significance apart from allowing practitioners to distinguish between the two different pricing locations. Argus/McCloskey quote prices for API 2 (Northwest Europe), 3 and 4 (South Africa), 5 and 6 (Australia), 8 (South China), 10 (Colombia), and 12 (East India). Where two indices exist for a single geographical location the main differentiator will be one of quality; API 3 is for lower grade coal exported from Richards Bay than API 4. Driven by the liberalisation in the electricity markets across Europe, the utilities, who are the biggest users of financial swaps on coal, have been faced with less predictable load factors and are, therefore, moving away from using the one-year fixed price supply contracts, which were the norm. This has led to an increase in hedging requirements using price indices. Prices for coal are considered to be relatively volatile, but still are at the lower end of competing fuel sources. The following ranges of implied volatilities are indicative: API2 Rotterdam API4 Richards Bay GlobalCoal NEWC Crude Oil Natural Gas (US) Natural Gas (EUR)

10.4.1

25–35% 20–25% 18–25% 25–50% 40–120% 40–90%

Exchange traded futures

Exchange traded coal futures exist, but at the time of writing are somewhat illiquid. One example is the API2 Rotterdam coal futures traded on ICE. The contract specification is detailed below (Table 10.1):

TABLE 10.1 Coal Futures Specification. Trading Unit

1,000 metric tons of coal

Price quotation Trading month

US dollars and cents per ton The exchange trades individual month, quarterly, seasons, and annual contracts USD 0.05 (5 cent) per ton Trading terminates on the day of expiry of the delivery month, quarter, season, or calendar. So, a monthly contract of, say, March will terminate on the last business day of that month. Cash settled at an amount equal to the monthly average API2 index as published by Argus McCloskey’s coal price index report

Minimum price fluctuation Last trading day

Delivery

Source: Data from API2 Rotterdam Coal Futures, ICE FUTURES EUROPE, Intercontinental Exchange, Inc.

Bulk Commodities

10.4.2 10.4.2.1

351

Over the counter solutions Coal swaps

Arguably, the most popular OTC solutions in the coal markets are swaps and swaptions on coal. Take for example the risk profile of a large Australian coal producer. The company sells most of its production through traditional long-term fixed price contracts, with the balance sold against an index (API 2 for delivery in Rotterdam) on a floating basis. They have chosen this index pricing basis for their exports as they have access to very favourable shipping rates. However, using a floating index gives the company exposure to fall in the price of coal. As part of its risk management strategy it is willing to swap this index exposure into a fixed price if it believes that the ‘price’ (i.e. the fixed element of the swap) is at an attractive level. It decides to enter a swap with the following terms: Trade date: Maturity: Total notional quantity: Notional quantity per month: Settlement dates: Payment date: Fixed price payer: Fixed price: Floating rate payer: Reference floating price: Tenor:

October Three calendar months, effective from the following June. 15,000 MT (metric tonnes) 5,000 MT Monthly in arrears Five business days after settlement date Bank USD 60.00/MT Client COAL – API 2 – ARGUS / MCCLOSKEY’S Monthly price

With the company receiving the floating index on their underlying physical exposure but paying the same index under the terms of the swap, the net effect is that the two floating exposures cancel leaving the producer receiving a fixed cash flow of USD 60.00 per metric tonne. This presumes, however, that the date at which the floating price is fixed for the swap coincides with that of the physical exposure. A mismatch in the timings of the floating payment would be referred to as basis risk. In this scenario the producer sells most of their production under long-term fixed price agreements. If the demand for coal were to increase, the producer would still use swaps to benefit from any rise in price. They could enter a coal swap referencing the fixed price component of their production. Under the terms of the swap they would receive a floating index price and pay fixed. The net effect of this would have been to leave the producer as a net receiver of the floating index, allowing them to benefit from the rise in the price of coal. In the previous example the cash flow exchanges took place monthly. This would be useful as a hedge for a producer who is selling a regular amount of coal per month over the period in question. However, the swap could also be structured as one three-month contract. Here the contract is most likely acting as a cash-settled forward transaction, where the price is fixed at the start of the period but settled in arrears. For example:

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Trade date: Maturity: Total notional quantity: Notional quantity per period: Settlement dates: Payment date: Fixed price payer: Fixed price: Floating rate payer: Reference floating price: Publication source: Tenor:

October Three months effective the following June 15,000 MT (metric tonnes) 15,000 MT One three-month period paid in arrears Five business days after settlement date Bank USD 60.00 Client COAL – API 2 – ARGUS / MCCLOSKEY’S Argus /McCloskey’s coal price index report Three-month price at start of period

A common feature of OTC coal swaps is that the agreements will include a currency conversion provision, which allows for the payment of cash flows to be denominated in a currency other than USD. For example, a contract that makes the cash flow payments in either GBP or EUR may be based on the average exchange rate for the settlement period (e.g. monthly as in the previous example). 10.4.2.2

Coal swaptions

Another popular trade in the market is the coal swaption (e.g. an option on a coal swap). A possible term sheet for such a trade might look as follows: Option trades Trade date: Expiry: Option style: Option seller: Option buyer: Premium per MT: Total premium: Underlying transaction Effective date: Maturity: Total notional quantity: Notional quantity per period: Settlement dates: Payment date: Fixed price payer: Fixed price: Floating rate payer: Reference floating price: Tenor:

September December (three months) European Bank Client USD 1.85 USD 27,750 December, 12 months after option expiry Three months 15,000 MT (metric tonnes) 5,000 MT Each month in arrears Five business days after settlement date Bank USD 60.00 Client COAL – API 2 – ARGUS / MCCLOSKEY’S Monthly price

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353

Motivation for using swaptions The rationale for the trade will be different depending on the end client. If the client is a producer or consumer of coal, then it is most likely that the motivation will be to hedge, on a contingent basis, some form of underlying exposure. For example, the terms of the underlying swap in the previous term sheet are identical to those presented in the first swap example. We had argued that in that scenario a producer selling on a variable rate basis could receive a fixed price to transform their exposure to a falling coal price. A possible motivation to buy this swaption is that they believe the price of coal will rise, but cannot afford for their view of the market to be wrong. Another popular strategy occasionally used by producers is to sell out-of-the-money (OTM) call options. Suppose that the current price for coal (e.g. the prompt futures price) was USD 50.00. If the producer were to sell a three-month OTM call struck at USD 55.00 then using an implied volatility of 40% this would generate a premium of about USD 2.00/MT. If the price of coal were to fall, then the option would not be exercised and the producer would sell their planned output at the prevailing lower price but would retain the premium, which would help boost cash flow. A similar situation would occur if the coal price were stable or increased by a small amount. If the price of coal were to increase to, say, USD 60.00 the option would now be in-the-money (ITM). The option buyer would exercise and if physically delivered would receive the agreed amount of coal at the strike price of USD 55.00. From the producer’s perspective their net income would be USD 57.00 – the strike price received + the premium. Indeed, once the option is exercised this sum will be their income irrespective of the final price of the underlying. In this sense the sale of the call option would prevent them from benefiting from a sharp rise in the underlying price. In some financial markets this strategy is often referred to as a ‘covered call’ and represents a situation where the option seller is long the underlying asset and sells optionality on this position. Traditionally, the motivation is that the strike is set at a level that the seller believes will not trade and so they will be able to retain the premium. Since the strategy restricts the ability of the seller to benefit from a sharp increase in price, it would not be suitable for those participants who have a particularly bullish outlook on the underlying.

10.5 10.5.1

IRON ORE Background

According to the US Geological Service: ‘The element iron (Fe) is one of the most abundant on earth, but it does not occur in nature in useful metallic form. Iron ore is the term applied to a natural iron-bearing mineral in which the content of iron is sufficient to be commercially usable. Metallic iron, from which steel is derived, must be extracted from iron ore.’

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Reference is often made to ‘fines’, which are essentially heavy grains (like sand). The fines are then transformed into pig iron, which can then be used to make steel using coking (metallurgical) coal in a furnace. Iron ‘lump’ is an intermediate product that sits between iron ore and pig iron. How iron is used in the production of steel is outlined in Section 5.4. Steel is a combination of iron along with a small amount of carbon. Thousands of products having various chemical composition, forms, and sizes are made of iron and steel by casting, forging, and rolling processes. Iron and steel comprise about 95% of all the tonnage of metal produced annually in the United States and the world. On average, iron and steel are the least expensive of the world’s metals. In some circumstances, such as steel framing for large buildings, no other materials are deemed suitable due to strength requirements. According to the USGS (2020) the five largest producers of pig iron are: ▪ ▪ ▪ ▪ ▪

China 820 million metric tonnes (MMT) India 75 MMT Japan 75 MMT Russia 50 MMT Korea 48 MMT

10.5.2

Evolution of iron prices

Iron ore prices are often quoted in terms of its ferrous content expressed as a percentage. One of the most popular grades is iron ore with 62% ferrous content. According to ICE (2009), most commercial grades lie between 58% and 65% with key markers at 58%, 62%, 63.5% and 65%. The evolution of iron prices is an interesting case study on how a commodity can transition from non-traded to traded status. This was covered in Section 1.3.

10.5.3

Iron ore derivatives

At the time of writing the Singapore Exchange listed a suite of iron ore, coking coal, and freight contracts. In relation to iron ore they were offering: ▪ Futures, swaps, and options. The options could either be options on futures or options on swaps. ▪ The underlying commodity was primarily iron fines although a ‘lump’ contract was also traded. ▪ The grade quality varied from 58% to 65%. ▪ The iron ore contracts are quoted on a CFR basis. CFR is ‘cost and freight’ and is used in relation to products that are transported by sea. The seller arranges and pays for transport to a named port. Seller will also deliver and load the goods on the ship. However, once the goods have been loaded, the risk will transfer to the buyer. The seller does not arrange insurance for the goods.

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▪ The contracts settle against an independent published index (e.g. MB iron ore index, 58% FE fines, CFR Qingdao). ▪ The contracts are cash-settled if held to maturity.

10.6 10.6.1

FREIGHT MARKETS – THE FUNDAMENTALS Vessel types

Freight markets are divided into two main categories: wet and dry. Wet freight will include the movement of crude oil and refined products as well as container ships, passenger liners and tugboats. Dry freight covers the shipping of raw materials such as coal, iron ore, bauxite, and grains. It is often convenient to categorise ships in terms of their dead weight tonnage (dwt), which is a measure (usually expressed in metric tons) of a ship’s carrying capacity including fuel, fresh water, crew, and provisions. Within the dry freight market there are several different types of vessel that are used, which include: Handysize These are bulk carriers of approximately 20,000–35,000 dwt and are usually fitted with cranes. Handymax These are bulk carriers of approximately 36,000–49,000 dwt and may be fitted with cranes. These vessels will carry grains and bulk commodities such as steel products and fertilizers. Supramax/Ultramax About 50,000–60,000 dwt. Panamax/Kamsarmax These are ships in the 65,000–83,000 dwt range, but are narrower in the beam so as to be able to navigate the Panama Canal. Their cargo is mainly coal, grain, and ‘forest products’ (e.g. packaging, recovered paper, and printing papers). Post Panamax/Mini Cape About 87,000–120,000 dwt. Capesize 80,000–175,000 dwt. Cannot navigate the Panama or Suez Canal. Will transport goods either via Cape Horn or the Cape of Good Hope. Used mostly for iron ore delivery. Very large Ore Carrier (Valemax, Chinamax) About 220,000–400,000 dwt. Within the wet freight market different cargoes will require different handling and transport and so special types of tankers have been built to accommodate these needs. Like the dry freight market, tankers are classified according to their capacity.

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Product tanker: Panamax: Aframax: Suezmax: VLCC: ULCC:

10,000–60,000 dwt 60,000–80,000 dwt 80,000–120,000 dwt 120,000–160,000 dwt 240,000–320,000 dwt 320,000–550,000 dwt

VLCC is a very large crude carrier, while ULCC stands for ultra large crude carrier.

10.6.2

Freight charges

Within the dry freight market, a distinction is made between a voyage charter (VC) and a time charter (TC; sometimes referred to as a trip charter). A VC is analogous to taking a taxi from one point to another; you know how much the trip is going to cost you. A VC is priced in USD per tonne. On the other hand, a TC is a little like renting a car; you can go wherever you want, but you must return the car back to where you rented it or face a drop-off surcharge. The hirer is responsible for petrol and tolls as well as having to cope with traffic jams and other delays. A TC is priced in USD per day. It is not always straightforward to compare TC and VC prices. The first thing is to make sure that the two routes being compared are the same. To convert a TC into a VC the first step is to calculate the number of days it will take to make the round-trip voyage (allowing for loading and unloading). The cost of fuel will then need to be added. This total cost can then be divided by the total tonnes carried to derive a figure that can be used for comparison purposes.

10.6.3

Freight market participants

There are several different freight market participants: ▪ ▪ ▪ ▪ ▪

Ship builders Ship owners Ship brokers Charterers Operators

Brokers will act as intermediaries between ship owners and those entities with a cargo that they need to move. Charterers might include mining companies, utilities, steel mills, cement producers, or grain traders. A ship operator will assume responsibility for the operation and administration of a vessel (e.g. crewing, technical operation, and maintenance). Some operators could charter a ship from an owner for several years and then charter the vessel to another operator for a higher rate but a shorter period. Although currently owned by the Singapore Exchange, the Baltic Exchange is a membership organisation that provides an independent source of maritime market information, which can be used to settle physical and derivative shipping contracts.

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The members of the exchange comprise of market participants who are active in the dry and wet freight markets. It is the oldest shipping market in the world and can trace its origins back to 1744. To facilitate maritime trade, the Baltic Exchange compiles and publishes a range of benchmark indices. According to their website the indices ‘are an assessment of the price of moving the major raw materials by sea. The indices are based on the assessments of the cost of transporting various bulk cargoes both wet (e.g. crude oil and oil products) and dry (e.g. coal and iron ore) made by leading shipbroking houses around the world on a per tonne and daily hire basis.’

10.6.4

An overview of dry freight indices

The Baltic Exchange publishes several benchmarks that cover a wide variety of different routes and vessels. These indices are designed ‘to provide an assessment of the prevailing market rate for a specified shipping route in the dry or wet bulk market’ (Baltic Exchange, 2019). Several international shipbroking firms who have no direct financial interest in chartering vessels make the assessments. The Exchange acknowledges that the compilation of the index is challenging, citing several factors: ▪ The shipping market is complex, varied, and often opaque. ▪ Shipping contracts are private bilateral contracts. This means the terms are not standardised and will only be known to the two participants. ▪ Rates and prices agreed might be contingent on other conditions being fulfilled. ▪ Shipping markets are generally considered to be illiquid as transactions may be relatively infrequent. As a result, prices can be very volatile. For example, the Baltic Dry Index reached a value of 11,793 on 20 May 2008 but had fallen to just 663 by 5 December in the same year. ▪ There is no obligation on market participants to report transactions. ▪ Ships exist in a very large numbers of different types and sizes and may not match those used in the compilation of a particular benchmark. ▪ Several other factors could influence the market value of a particular ship, which might include maintenance of the vessel and the credit worthiness of the owner. According to the Exchange, when making their assessments for the day the ‘panelists will take cognizance of the totality of market information known to them at the time of reporting, making an appropriate adjustment to accord with the Baltic’s route definitions.’ The Exchange (2019) points out ‘the Baltic has always explained that reporting panels exist because ultimately, there is no independently verifiable ‘right’ or ‘wrong’ rate for index routes. Therefore, market levels at any particular time remain a matter of judgement’. One of the most popular indexes is the Baltic Dry Index (BDI), which as the name suggests is not a price but an index value. This is a weighted average of three other indices published by the exchange: ▪ Baltic Exchange Capesize 2014 Index (40% weight) ▪ Baltic Exchange Panamax Index (30% weight) ▪ Baltic Exchange Supramax Index (30% weight)

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Baltic Exchange Dry Index (BDI)

Baltic Exchange Capesize 2014 Index (BCI)

Baltic Exchange Panamax Index (BPI)

Baltic Exchange Supramax Index (BSI)

30% weight

30% weight

40% weight

FIGURE 10.7 Hierarchy of bulk indices.

The structure of the indices is shown in Figure 10.7. Within each of these indexes a notional vessel is specified by the exchange (e.g. a certain dead weight tonnage, age); within the Baltic Capesize 2014 index, the notional vessel size is 180,000 dwt and has a maximum age of 10 years. Each index will also specify several pre-defined routes, often represented by a series of letters and numbers. Some routes may be time charters, others voyage charters. For example, the Baltic Capesize 2014 index covers 12 routes, which include: ▪ C2 – the journey from Tubarao in Brazil to Rotterdam in the Netherlands, which is used for the transportation of iron ore. ▪ C4 – the journey from Richards Bay in South Africa to Rotterdam in the Netherlands, which is used for the transportation of coal. The panelists submit to the Baltic Exchange their freight rate assessments, and a simple average monetary value is determined for each route. This is then multiplied by a constant number (the multiplier) to convert the dollar amount into an index value. These values are then summed, and this returns the overall value of the index. To convey a sense of how the individual indices could be calculated, consider the following example (Table 10.2), which has been simplified for ease of illustration. TABLE 10.2 Index compilation – Day 1. Route number

Assessed freight rate (USD/day)

Multiplier

1 2 3 4

10,000 11,000 12,000 13,000

0.02500 0.02273 0.02083 0.01923

Contribution to the index 250 250 250 250 Index total = 1,000

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To make the example work a few assumptions have been made: ▪ ▪ ▪ ▪ ▪

This is the first time that the index has been quoted. The assessed freight rates are time charter values, expressed as USD/day. The index compilers have set an initial index value of 1,000. The final index value is the sum of the individual route contributions. Each of the individual routes is deemed to contribute 25% to the overall value of the index. ▪ The calculations have been rounded. In this example, for each of the routes to contribute 25% to the initial value of the index, their individual contributions must be 250. Given that the monetary assessments are different, the multiplier for each route is set at such a level that it returns the appropriate index contribution. So, for route 4, with an assessed value of USD 13,000 and an index contribution of 250, the multiplier would have to be 0.01923 (rounded). These multipliers will then remain unchanged until there is a change in the composition of the index, which could arise if the weightings are changed, or if routes are added or removed. It is also possible to quote the index in USD terms and so on an unweighted arithmetic basis the assessed value would be USD 11,500/day. Consider now how the index would evolve if the following day, the assessed values remain the same apart from route 4 which increases to USD 14,000. The new calculation of the index is shown in Table 10.3. Note that the multiplier for all the routes is unchanged as the assumption is that there has been change to the index specification. The index contribution for route 4 has increased to 269.23, which pushes the index value upwards to 1,019.23. In cash terms the average value for this fictional index is now USD 11,750. This calculation shows how the multiplier can also reflect the effect of a USD 1.00 change in the freight rate on the overall index. So, since the assessed freight rate has increased by USD 1,000 then the index has increased in value by 19.23 points (USD 1,000 x 0.01923).

10.6.5

Worldscale

Rates for wet freight cargoes are often calculated using the Worldscale System. Worldscale is a large table of freight rates for different routes. The table covers over 300,000 TABLE 10.3 Index compilation – Day 2. Route number 1 2 3 4

Assessed freight rate (USD/day)

Multiplier

10,000 11,000 12,000 14,000

0.02500 0.02273 0.02083 0.01923

Contribution to the index 250 250 250 269.23 Index total = 1,019.23

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voyages and offers different permutations about the number of loads a ship is carrying and different discharge ports. The table is updated annually by the Worldscale organisation, a non-profit market association based in London and New York. The table of rates is expressed in USD per metric tonne, with each rate being referred to variously as WS100, 100% of Worldscale, or Worldscale ‘flat’ and is a base value from which an actual rate is negotiated. Actual market rates are agreed to relative to this figure and reflect prevailing demand and supply; a technique referred to as ‘points of scale’. Suppose that two parties are negotiating a rate for the trip from Singapore to Chiba in Japan. They agree to a contract rate of 287 Worldscale points. If WS100 were USD 9.13/MT, this would equate to an amount of USD 26.2031 (USD 9.13 x 2.87). At the heart of the Worldscale calculation is the principle that the scale will provide the same net revenues per day irrespective of the voyage performed by a ‘notional’ vessel at WS100. So, in theory, the rates are calculated such that after allowing for port costs, fuel costs, and canal expenses the net daily revenue will be the same for all voyages. Like dry bulk indices a notional vessel had to be established as the benchmark allowing participants to negotiate a specific rate for their voyage. All the rate calculations are quoted in USD per tonne for a full cargo for the standard vessel based upon a round voyage from loading port to discharging port. To convey a sense of the ‘net revenue’ concept, the notional vessel specification includes some of the following characteristics: Total capacity: Average service speed: Consumption of fuel: What type of fuel used: Price of fuel: Port time: Fixed hire element:

75,000 tonnes 14.5 knots 55 tonnes per day when steaming Very Low Sulfur Fuel Oil (VLSFO – max 0.5% sulfur content) VLSFO USD 550.42 per tonne Four days for a voyage from one loading port to one discharging port USD 12,000/day

If the contracting parties are using a larger vessel, they must agree between themselves a method of reflecting any additional costs.

10.6.6

Freight price drivers

Arguably the main price drivers for the freight market can be categorised under two main headings: fleet development and general economic factors. 10.6.6.1

Fleet development

Availability of ships The Baltic Exchange estimates that there are approximately 9,000 ships in the dry bulk fleet. To put this into context there are about 13,500 yellow cabs in New York. Vessels that are laid up for maintenance would also impact availability.

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Construction of new vessels It is important to distinguish between the number of new vessels being ordered and those that are close to being delivered. This is because on average it may take about 18 months to build a new vessel. If there is an increase in supply of vessels, then shipping costs could fall. Piracy In the late 1990s and the early 2000s the focus on piracy was on the South China Sea and the Straits of Malacca. Since 2005 the focus started to shift to piracy off the coast of Somalia, in the Gulf of Aden and the wider Indian Ocean. For example, in 2018, the International Maritime Bureau reported 223 incidents. The implication for shipping is the possible rerouting of a vessel. For example, a voyage from the Gulf region to Rotterdam might take about 75 days. If the vessel were forced to travel via the Cape of Good Hope, then the voyage time would be about 95 days. So not only does the cost of a single shipment increase, but freight rates may also increase as ships are now at sea for longer periods. The owners of the cargo will also be faced with having to finance their inventories for longer periods, which would increase their costs. Choke points If geopolitical tensions increase, there is always the risk of conflict between countries. This could mean that locations such as the Straits of Hormuz may be deemed unsafe areas for freight. Environmental considerations The general increase in concern over particulate emissions such as sulfur and nitrogen oxides from ship exhaust systems have forced vessel owners to fit ‘scrubbing systems’ to remove the harmful matter. 10.6.6.2

Economic factors

The demand and supply for bulk commodities The factors that influence the price of freight will often be the same as those that affect the individual bulk commodities. Availability of credit A reduction in bank lending may reduce the number of ships being built, which would represent a reduction in supply. During the financial crisis of 2007–2008 there was a substantial fall in shipping rates and some buyers decided to cancel orders, forfeiting substantial deposits as they considered it a more financially viable option.

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Seasonality This could take different forms perhaps in terms of weather conditions along a certain route or demand for goods to coincide with a major holiday such as Christmas. Cost of fuel The Baltic Exchange points out that fuel costs make up between one-quarter and one-third of the cost of running a vessel. Infrastructure If there is congestion at a particular port that leads to delays in loading and unloading this is in effect a form of supply reduction as vessels will not be available. Other key points include: ▪ Like other commodities that display a term structure, different maturities may be influenced by different factors. For example, the number of ships to be delivered, or the change in demand for a particular bulk commodity may influence short-term prices. Longer-term prices may be influenced by environmental issues, which may impact the long-term demand for coal. ▪ Some practitioners suggest that freight prices are a barometer of the current health of the world economy, but some might argue that this is somewhat simplistic.

10.6.7 10.6.7.1

Freight Derivatives Forward Freight Agreements (FFAs)

FFAs are essentially a form of swap and have proven to be a very popular instrument in the shipping market. Consider a mining company that is looking to fix the price of freight for a future date with a ship operator. This deal is sometimes referred to as the ‘physical’ transaction. FFAs sit in the ‘financial’ or ‘paper’ side of the market and can be used to hedge an existing freight agreement. They can also be used to express a view on how markets are expected to evolve and do not require the participants to have an underlying physical exposure. Those participants looking to hedge against (or profit from) a rising rate should ‘buy’ the contract (i.e pay fixed); those looking to hedge against falling rates should ‘sell’ the contract (i.e receive fixed). All the contracts are cash-settled; a ULCC is not going to turn up at your office! From a price formation point of view, in the physical market, the cost of hiring a vessel for three months in six months’ time should be the same as the price two participants could agree in the FFA market for the same period. However, there are occasions where differences between these two prices may emerge, which could be caused by, for example, speculative activity in the FFA market. As such these discrepancies may offer an attractive hedging opportunity as the transaction is trading away from ‘fair value’. Consider the following hypothetical term sheets. Although sometimes referred to as ‘contracts for difference’ they can be agreed to with either multi- or single-period settlement terms.

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Voyage charter (VC) Effective date: Maturity: Calculation period: Settlement: Notional quantity per period: Total notional quantity: Fixed price payer: Contract rate: Fixed amount: Floating price payer: Floating amount: Floating price:

To start 3.5 years after trade date 12 months (1 January–31 December) from effective date Monthly Monthly 10,000 MT 120,000 MT Client USD 11.00/MT Contract rate x notional quantity per period Bank Floating price x notional quantity per calculation period Baltic C4, average of daily published rates expressed in USD/MT

Key points: ▪ The transaction is forward starting in that it only becomes effective 3.5 years in the future. ▪ It is a single transaction covering a 12-month period with monthly cash flow exchanges. ▪ The notional amount is expressed in metric tonnes. ▪ The fixed monthly cash flow payable by the client is USD 11.00 x 10,000 MT = USD 110,000. Sometimes the entity paying fixed is referred to as the buyer. ▪ Although not specified in this term sheet, the client may be using the swap to hedge an underlying fixed price transaction. Suppose they have a physical transaction where they have agreed to a fixed price voyage charter with a mining company. Under the terms of the underlying contract they would receive a fixed cash flow from their counterparty, but could then make a fixed payment to the bank under the terms of the swap. In return they would receive a variable cash flow, which would be beneficial if they thought that freight rates were going to be higher during the period of the swap. ▪ The floating price is referencing the Baltic C4 route (Richards Bay to Rotterdam), which forms part of the Capesize 2014 index. The transaction requires a price rather than an index value. The calculation of an index or monetary value was illustrated in Section 10.6.4. ▪ The value for the Baltic C4 route is published on every good business day of the month (typically about 21 days), and to derive the settlement value an unweighted arithmetical average of all these values is then calculated. ▪ Suppose that the floating price for a particular month fixes at USD 11.50/MT. The floating cash flow will be USD 11.50 x 10,000 MT = USD 115,000. The payer of floating is sometimes referred to as the seller. ▪ Since both payments coincide there will be a single net payment by the payer of floating (in this case the bank) of USD 5,000.

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Time charter (TC) Effective date: Maturity: Calculation period: Settlement: Total notional quantity: Notional quantity per period: Multiplier: Fixed price payer: Contract rate: Fixed amount: Floating price payer: Floating price: Floating amount:

To start 1.25 years after trade date 12 months (1 January–31 December) from effective date Monthly Monthly 182.50 calendar days The number of days in the calculation period. 0.5 Bank USD 15,000 per calendar day Contract rate x (notional quantity per calculation period x multiplier) Client Baltic Supramax S2, average of daily published prices expressed in USD/day Floating price x (notional quantity per calculation period x multiplier)

Key points ▪ Like the VC swap, this transaction is also forward starting with monthly settlement covering a 12-month period. ▪ The notional amount is described in days and this example covers half of the transaction’s maturity. ▪ The fixed amount payable in a month with 31 days would be USD 15,000 x (31 x 0.5) = USD 232,500. ▪ Suppose that the floating price fixes at USD 14,500. The floating amount payable for the same 31-day month would be USD 14,500 x (31 x 0.5) = USD 224,750. ▪ Since both payments coincide there will be a single net payment by the payer of fixed equal to USD 7,750. ▪ This transaction includes the use of a multiplier, which reduces the number of days within the month to which the swap applies and so lowers the cash flow. The use of the multiplier could suggest that the counterparty assumes that the vessel(s) will only be chartered for half of the time. ▪ Not all TC transactions will use a fractional multiplier and so in some cases it is set at a value of 1. ▪ Although not specified by the term sheet, it may be possible to infer the client’s motivation based on some simple assumptions. If the client were chartering their vessels to other market participants, the fact that they are ‘selling’ the swap would suggest that they have a concern that rates are likely to fall. It could be a pre-emptive hedge in that the client knows they will have an ongoing need to charter vessels to other participants and so this may not be linked to a specific transaction.

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Worldscale Effective date: Maturity: Calculation period: Settlement monthly: Total notional quantity: Notional quantity per period: Fixed price payer: Contract rate: Fixed price:

Floating price payer: Floating reference price:

Floating amount:

To start one month after trade date Three months (1 January–31 March) Monthly Monthly 15,000 MT 5,000 MT Bank 178 Worldscale points A price calculated using the following formula USD 24.7954/MT (being the contract rate of 178 x Worldscale flat rate/100) Client Baltic Dirty Tanker Index route TD8 (Kuwait to Singapore), expressed in Worldscale points. Average of daily prices in each calculation period. The unweighted arithmetic average of the reference price for each good business day in the month x Worldscale flat rate/100.

Key points ▪ Since the confirmation states that the fixed contract rate is WS178 and that this converts into a cash flow of USD 24.7954 it follows that the ‘flat’ Worldscale rate (e.g. WS100) for this route is USD 13.93/MT. ▪ The value of the Baltic Dirty Tanker Index is assessed from 14 individual routes (of which TD8 is one), where the main cargo is typically crude oil. Each route and the overall index can be quoted either in Worldscale points or as an index equivalent. ▪ The fixed price payment for each month will be the same and is calculated as USD 24.7954 x 5,000 MT = USD 123,977. ▪ Each good business day (usually about 21 days in a calendar month) a Worldscale value for the route will be assessed and published. At the end of the month, the values are then totaled and divided by the number of good business days to generate the arithmetic average. ▪ Suppose that the floating reference price for the month is calculated at WS170. The floating amount would be USD 13.93 x 1.70 x 5,000 MT = USD 118,405. ▪ Since both payments coincide there will be a single net payment by the payer of fixed equal to USD 5,572. FFAs can offer a great deal of flexibility: ▪ The participants can choose the size of the trade and it does not have to exactly match the underlying exposure.

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▪ The maturity can be agreed between the two counterparties and again does not have to match the underlying. ▪ A position can be added to or reduced. Reducing a position may mean taking an offsetting position. Although the emphasis in this section has largely been on hedging applications, it is possible to use FFAs to express views on how the market may evolve without holding an underlying exposure. Example trades may be: ▪ The spread in price between different maturities of the same contract; sometimes referred to as the ‘calendar spread’. So, in the early part of a particular year a trader could take a view that prices in the third quarter may move relative to the fourth quarter. The periods traded could also include half and full years. ▪ Spreads between indices (e.g. Capesize 2014 vs. Panamax). ▪ Spreads between wet and dry indices (e.g. Baltic Dry Index vs. Baltic Dirty Tanker Index). 10.6.7.2

Liquefied natural gas (LNG)

LNG was covered in Chapter 7 and one of the highlighted themes was the move away from long-term contracts priced against oil to spot transactions priced using the gas markets. In the long-term contract model the cost of freight was usually included as part of the overall terms. As of the time of writing it has been suggested that around 20% of all LNG trades now take place on the spot markets (Risk, 2020), which usually means that freight costs will be a separate variable cost. An LNG trader could buy an LNG freight future so they could buy the natural gas from a particular region where it may be relatively inexpensive and then later charter a vessel in the spot market. The long freight future position would result in a known shipping cost. Freight futures on the NYMEX exchange reference three main routes: ▪ Gladstone, Australia to Tokyo, Japan; ▪ Sabine, USA to Isle of Grain, UK; ▪ Sabine, USA to Tokyo, Japan. The contracts are listed out to two years and are financially settled against a reference index published by the Baltic Exchange. 10.6.7.3

Exotic swap structures

Target payout structures have been popular in a variety of different asset classes such as foreign exchange and have been seen within the freight market, although to a much lesser extent.

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A hypothetical term sheet might look as follows: Freight Index: Put price payer: Call price payer: Strike: Maturity: Calculation period: Settlement: Notional quantity: Put payment: Call payment: Target payout provision:

Target payout amount: Floating price:

Panamax Time Charter 4 (average of P1A_03, P2A_03, P3A_03, P4_03) Client Bank USD 10,000 per calendar day Two years – subject to target payout provision Monthly Monthly Number of days in the calendar month Notional quantity x MAX [0, Strike – Floating price] x 2 Notional quantity x MAX [0, Floating price – strike], subject to target payout provision If the amount paid out under the call payments is equal to or exceeds the target payout amount then the trade will terminate. USD 350,000 The average realised freight index value during the month.

Looking at the structure, the term sheet indicates that it comprises of a strip of options. Each month will consist of a combination of calls and puts. The client buys a call and finances its purchase with the sale of a put. Since the call and the put have the same strike, the client is therefore long a synthetic forward. Note that the client has sold twice the amount of put optionality because the strike of the structure is set at a level that is more favourable than the vanilla rate. This advantage is paid for by a combination of a limit on the customer’s upside benefit and an increase in their downside liability. This trade was designed with a client who would need to charter a vessel and is looking to manage the associated cost. In essence the client is long a forward, which will terminate once the accumulated positive payouts to them has reached the target profit amount. The client cannot receive more than the target profit amount. If there is a decline in prices the client will be faced with having to settle a liability, which will be the difference between the now lower price and the strike price. However, this payment is magnified by a factor of two. Although there is a risk that the cash flow paid under the swap will increase, there should be a fall in the associated ‘physical’ market cost. 10.6.7.4

Option structures

Option structures have been traded in the freight market. Example structures would include single option positions (e.g. calls and puts) as well as premium reduction strategies (e.g. zero premium collars, three ways). Rather than repeat ideas covered earlier in the text, readers are referred to Chapter 5 on base metals for example trades.

CHAPTER

11

Climate and Weather

11.1 11.1.1

THE SCIENCE OF CLIMATE CHANGE Definitions

In the first edition of this text, the author used the phrase ‘global warming’, which at the time was a commonly used term. However, over time this has been superseded by the phrase ‘climate change’. I often feel there is a tendency for people to confuse weather and climate, so it is worth defining both terms. NASA’s (2020) global climate change website provides some useful terms of reference: ‘Weather refers to atmospheric conditions that occur locally over short periods of time; from minutes to hours or days. Familiar examples include snow, clouds, winds, floods, or thunderstorms. Climate, on the other hand, refers to the long term regional or even average temperature, humidity and rainfall patterns over seasons, years, or decades. Global warming is the long-term heating of Earth’s climate system observed since the pre-industrial period (between 1850 and 1900) due to human activities, primarily fossil fuel burning, which increases heat-trapping greenhouse gas levels in Earth’s atmosphere. The term is frequently used interchangeably with the term climate change, though the latter refers to both human- and naturally-produced warming and the effects it has on our planet. It is most commonly measured as the average increase in Earth’s global surface temperature.’

11.1.2

Greenhouse Gases

The earth is warmed by energy radiated by the sun. Although some of this is reflected back into space, a significant proportion will reach the surface of the earth. Most of the energy is absorbed by the earth’s surface but some is reflected back into space in the form of infrared radiation. This infrared radiation, however, may not directly exit into space, as its eventual escape may be blocked by greenhouse gases (GHG) that make up about 1% of the atmosphere. The main greenhouse gases are: ▪ Water vapour (H2 O) – the most abundant greenhouse gas. ▪ Carbon dioxide (CO2 ) – this is generated by burning fossil fuels and by the respiration of humans and animals.

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▪ Methane (CH4 ) – this may be released when mining for coal or searching for natural gas and oil. It can also be generated by landfills and livestock. ▪ Nitrous oxide (N2 O) – this can be generated by burning fossil fuels or may be found in fertilisers. ▪ Hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs) – produced by refrigeration and air conditioning units. ▪ Sulfur hexafluoride (SF6 ) – which is used in a variety of manufacturing processes. The focus of the climate change debate to date has been on carbon dioxide emissions. As a result, it is common to express the amount of these other GHGs in terms of tonnes of CO2 equivalent. (CO2 e). This is a measure for comparing the radiative effect of different GHGs in terms of the corresponding impact of emitting carbon dioxide. Carbon dioxide equivalents are calculated by multiplying the Global Warming Potential (GWP) of a gas by its emitted weight. Name of gas

GWP

Carbon dioxide Methane Nitrous Oxide Hydroflourocarbons Perflourocarbons Sulfur hexafluoride

1 25 298 Up to 14,800 Up to 12,200 22,800

GHGs are not inherently bad as they trap heat and maintain the planet some 30 ∘ C warmer than it would otherwise be. Most greenhouse gases do occur naturally, but their volume is increasing because of human activity. According to the IPCC (2014) the primary drivers of GHGs are: Energy industry: Agriculture, forests, and other land uses: Industry: Transport: Building sector:

11.1.3

35% 24% 21% 14% 6.4%

The carbon cycle

The carbon cycle describes the possible pathways a carbon atom takes through the different components of the ecosystem. A convenient starting point is the atmospheric content of carbon dioxide. Carbon atoms may be retained in the air until eventually they will be absorbed by green plants, combined with water, and turned into starch. This could occur over a matter of hours or hundreds of years.

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The carbon atom is now part of a large starch molecule. There are two possible pathways the atom may now take: ▪ It may be used by the plant in respiration, thus releasing the carbon atom back into the atmosphere as carbon dioxide. ▪ It may be further processed and become part of the plant in the form of wood or other plant cells or molecules. If the carbon becomes part of the plant, it then may take one of three possible pathways: ▪ The plant may die and be decomposed by bacteria in the soil, thus releasing the carbon as carbon dioxide back into the atmosphere. ▪ An animal may eat the plant. ▪ If the plant is burnt (either directly or as a fossil fuel), carbon dioxide is released back into the atmosphere. If eaten by an animal (as part of a larger organic molecule such as fat, carbohydrate, or protein) it will then follow one of three pathways: ▪ The carbon is used in respiration and released into the atmosphere as carbon dioxide. ▪ The carbon becomes part of the animal having been used to build protein, fat, or carbohydrate. ▪ The carbon remains in the state it was eaten, is undigested, and is passed out of the animal as faeces, which will be broken down by micro-organisms and the carbon in them released once more as carbon dioxide into the atmosphere. From here we start to ‘recycle’ in that the animal may die or be eaten by another animal and again the carbon atom can follow several different pathways. The carbon will always eventually end up back in the atmosphere as carbon dioxide, which is why the system is called a cycle, even though it does not really follow a single, simple pathway.

11.1.4

Feedback loops

The science of global warming is complex in that the effect of rising temperatures may well be accompanied by other changes in climate. These changes, which are referred to as feedback loops include: ▪ ▪ ▪ ▪ ▪ ▪

The amount of cloud cover. Levels of precipitation. Wind patterns. Rising sea levels. An intensification of the water cycle increasing the risk of droughts and floods. A change in the duration of the seasons.

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Although some of these effects may give rise to cooling effects, such as increased cloud cover that may block out sunshine; others may exacerbate the rise in temperatures. For example, if the Siberian permafrost were to melt exposing the peat surface beneath, there would be an increase in the amount of methane released into the atmosphere. Man-made aerosols, which are microscopic particles that reflect sunlight back out into space, may offer some temporary cooling effect but have their own side effects such as a reduction in air quality.

11.2

THE CONSEQUENCES OF CLIMATE CHANGE

The debate over climate change has evolved from whether the earth is getting warmer to one which tries to identify to what extent human activity has contributed to the change, so-called anthropogenic activity. NASA (2020) provides a useful illustration of the balance that exists between an insufficient and excessive greenhouse effect. Mars has a very weak greenhouse effect as it has a thin atmosphere, comprising mostly of carbon dioxide. There is little methane or water vapour that would help reinforce the greenhouse and as a result the planet is largely frozen. Venus is an example of a planet with a significant greenhouse effect. Like Mars its atmosphere is nearly all carbon dioxide, but it has 154,000 times more of the gas as Earth. This produces ‘a runaway greenhouse effect and a surface temperature hot enough to melt lead’. NASA argues ‘The consequences of changing the natural atmospheric greenhouse are difficult to predict but certain effects seem likely’. ▪ On average the Earth will become warmer. Although warmer temperatures may benefit some regions, for others it will have a negative impact. ▪ Warmer conditions will probably lead to more evaporation and precipitation overall, but this will vary between regions. Some will become wetter, others dryer. ▪ A stronger greenhouse effect will warm the oceans and partially melt glaciers and other ice increasing the sea level. Ocean waters also expand if it warms, contributing further to sea level rises. ▪ Some crops and other plants may respond favourably to increased CO2 as they will grow more vigourously and use water more efficiently. However, changing climate patterns may alter the areas where crops grow best.

11.2.1

Fifth assessment report of the IPCC

The fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC) was published in 2014. The main findings of the report included the following observations: ▪ Human influence on the climate system is clear, and recent anthropogenic emissions of greenhouse gases are the highest in history. Recent climate changes have had widespread impacts on human and natural systems.

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▪ Continued emission of greenhouse gases will cause further warming and long-lasting changes in all components of the climate system, increasing the likelihood of severe, pervasive, and irreversible impacts for people and ecosystems. Limiting climate change would require substantial and sustained reductions in greenhouse gas emissions which, together with adaptation, can limit climate change risks. ▪ Adaptation and mitigation are complementary strategies for reducing and managing the risks of climate change. Substantial emissions reductions over the next few decades can reduce climate risks in the twenty-first century and beyond, increase prospects for effective adaptation, reduce the costs and challenges of mitigation in the longer term and contribute to climate-resilient pathways for sustainable development. ▪ Many adaptation and mitigation options can help address climate change, but no single option is sufficient by itself. Effective implementation depends on policies and cooperation at all scales and can be enhanced through integrated responses that link adaptation and mitigation with other societal objectives.

11.3

THE ARGUMENT AGAINST CLIMATE CHANGE

‘Nobody knows just how much carbon dioxide the world is going to produce in the future. Nobody knows just what it will do to the temperature. Nobody knows just how temperature rises will affect the world economy’. —The Economist – 4 November 2006 Although there has been a growing consensus that human activities have contributed significantly to the warming of the earth, there is still an undercurrent of disagreement on the subject. The main reasons for disagreement are as follows: ▪ Climate change has been defined solely in terms of the study of the effect of greenhouse gases. One argument is that solar activity is a significant contributor to the climate and that there is a possibility that a reduction in the sun’s activity could lead to significant cooling. This argument is disputed by bodies such as NASA. ▪ Just because most people believe in something, this does not necessarily mean that it is right. ▪ The main research that supports the current majority theory is not independent and is being funded by those with an interest in propagating the current consensus view. ▪ Obtaining funding for scientific research that may contradict global warming is difficult to procure. ▪ As a result of the current concern over climate change, a new industry has developed, which many individuals and institutions have an interest in perpetuating. ▪ Any information that may contradict current thinking is not given the prominence that it deserves. For example, those arguing against the extent of anthropogenic activity point out that: ▪ The earth underwent a similar period of warming from 1918 and 1940.

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▪ ▪

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▪ The earth cooled from the 1940s to the 1970s. This is countered, however, by the argument that this was caused by the cooling effect of sulfur in the atmosphere generated by industrial activity, which is now in decline. ▪ Crops in areas normally associated with warm temperatures have been ruined by unseasonably cold weather. ▪ Some areas in East Antarctica are becoming colder. ▪ Between 1998 and 2005, global average temperatures did not increase. The choice of language in the predictions is too vague: ‘Since the early 1990s, the columns of many leading newspapers and magazines, worldwide, have carried an increasing stream of alarmist letters and articles on hypothetical human-caused climate change. Each alarmist article is larded with words such as ‘if’, ‘might’, ‘could’, ‘probably’, ‘perhaps’, ‘expected’, ‘projected’, or ‘modelled’. Even with a high probability of an event occurring, the margin for error is still significant, ‘a 10% uncertainty in any theory is a wide open breach for any latter-day Galileo or Einstein to storm through with a better idea’. The science is too complex to reconstruct past global temperatures and model them to predict future outcomes. The contrary argument says that the climate will change naturally, sometimes predictably sometimes unpredictably. The changes could be gradual, while others will be shorter and difficult to explain. The IPCC has been criticised for using 30 different computer models none of which produce the same result (Financial Times, 2020). The time frames over which climate judgments are made are often selective. For example, over 90% of the last two million years, the climate has been much colder than it has been today and if looked at from this perspective the planet is emerging from an ice age. There is a lack of information from the Southern Hemisphere. A report on the economics of climate change issued by the UK House of Lords Select Committee on Economic Affairs (prior to the publication of the 4th Intergovernmental Panel on Climate Change report) included the following comments: ▪ There was concern about the objectivity of the IPCC process in that some of the scenario analysis and summary documentation was influenced by political considerations. ▪ Some of the positive aspects of global warming were downplayed in the third IPCC report. ▪ The preoccupation of setting emissions targets at an international level was not an effective method of addressing the climate control issues. ‘The Kyoto Protocol makes little difference to rates of warming and has a naïve compliance mechanism which can only deter countries from signing up to subsequent tighter emission targets’.

11.4 11.4.1

HISTORY OF HUMAN ACTION AGAINST CLIMATE CHANGE Formation of the IPCC

The first world conference on climate change took place in 1979, but it was not until 1988 that the World Metrological Organisation and the United Nations Environment

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Programme established the IPCC. The IPCC reviews published research on the issue of climate change and issues influential assessments on a periodic basis and to date they have issued reports in 1990, 1995, 2001, 2007, and 2014.

11.4.2

The Earth Summit

The IPCC’s first report in 1990 formed the basis of negotiations for the United Nations Framework Convention on Climate Change. The text of the convention was launched in June 1992 at the Rio de Janeiro ‘Earth Summit’. The convention identified a number of countries referred to as Annex I parties, which comprised the industrialised nations that were members of the OECD in 1992 plus countries that were deemed to be in transition (e.g. the Russian Federation). This listing would eventually determine how many countries needed to ratify the subsequent Kyoto Protocol for this to become legally enforceable.

11.4.3

The Kyoto Protocol

The second IPCC assessment report concluded, on the balance of available evidence, that human activity was influencing the climate and that this would pose a threat to human and economic development. These results paved the way for the development and signing of the Kyoto Protocol in December 1997. The Protocol set individual, legally binding targets for several industrialised countries (the Annex I countries) willing to take steps to curb their emissions of greenhouse gases. For the Protocol to be legally binding it had to be ratified by an agreed number of developed countries who were determined to be responsible for most global emissions in the industrialised world. Only those countries that ratified the protocol become parties to the treaty, but ratifying the Protocol did not require the signatory to adopt legally binding emissions targets unless they were an Annex I country. The Kyoto Protocol outlined a variety of mechanisms that would allow countries to meet their commitments. Each of the countries for which the Kyoto principle is legally binding were assigned an emission limitation or reduction target. The emission targets varied from country to country and ranged from a cut of 8% to an increase in 10% of a baseline value measured from 1990. Despite the different target ranges, the main aim of the accord was to achieve an overall reduction in greenhouse gases by 5% in the 2008–2012 period, termed the ‘Kyoto period’. The Protocol outlined three mechanisms to help achieve this aim. The three Kyoto mechanisms were: ▪ Emission Trading Schemes (ETS) ▪ Clean Development Mechanism (CDM) ▪ Joint Implementation (JI) Two of the mechanisms (CDM and JI) are project-based, while the third is a market-based mechanism (ETS). These mechanisms, however, were never intended as the only way in which countries would tackle emissions. In addition, countries are

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expected to pursue policies that would encourage an overall reduction in the levels of emissions. Emission trading schemes – The market for trading emissions involves the purchase or sale of the right to emit an agreed amount of a specified pollutant. Emission trading schemes are sometimes referred to as ‘carbon markets’ as carbon dioxide is the most widely produced greenhouse gas. Participants can use the mechanism to acquire rights in order to meet their emission targets. Under the terms of the Kyoto Protocol these rights were referred to as ‘assigned amount units’ (AAU) where one AAU is equal to one tonne CO2 e. Hence if an installation had emitted 100 tonnes CO2 e in 1990 then over the Kyoto period of 2008–2012 they would be faced with a target of, say 92 AAU. If the installation chose to emit more than this amount, they would either have to buy the necessary allowances in the market or invest in technology to reduce their level of emissions. Within the EU Emissions Trading Scheme (ETS), these allowances are termed EUAs (European Union Allowances) and are either allocated or auctioned by regulators. The EU ETS is an example of what is known as a ‘cap and trade’ scheme. A national regulator allocates allowances to different sectors and then individual eligible firms. The regulator will be responsible for monitoring compliance within the limits and will also enforce penalties for non-compliance. Clean development mechanism (CDM) – this represents investment by an Annex I country in a developing country that will result in measurable long-term climate change. CDM projects, which became effective in 2005, must reduce emissions below those emissions that would have occurred in the absence of the project. These projects are monitored and certified by the UN, who will then issue credits on an annual basis equal to the amount by which emissions have been reduced. CDM credits are referred to as certified emission reductions (CERs). The CERs generated by such project activities could be used by eligible entities in Annex I countries to help meet their emissions targets under the Kyoto Protocol or be traded on a secondary market basis. Typical projects include: ▪ ▪ ▪ ▪

Energy efficiency schemes. Methane capture. Fuel switching (e.g. from coal to gas). Capture and destruction of certain industrial gases.

According to the United Nations Framework Convention on Climate Change (UNFCCC) 2018 annual report the CDM involved 140 countries with 7,803 projects. Joint implementation (JI) – In this mechanism, one Annex I country invests in an emission reduction project in another Annex I country. The costs of cutting emissions in the target country is cheaper than in the investing country. This allows for the transference of allowances from the target country to the investing country. These allowances are referred to emission reduction units (ERUs), but unlike the clean development mechanism there is no overall change in emissions. The JI mechanism took effect from 2008 to coincide with the Kyoto period.

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From Kyoto to Paris

After Kyoto, the next significant landmark agreement was at the ‘Conference of Parties’ (COP) 21 in Paris in 2015. The agreement came into force in November 2016 and as at the time of writing had been ratified by 96% of the parties to the convention. Some of the key elements of the agreement were: ▪ A long-term temperature goal – The aim is to limit global temperature increases to well below 2∘ C, while pursuing efforts to limit the increase to 1.5∘ C. ▪ Global peaking and climate neutrality – To achieve the temperature goal, parties to the agreement aim to reach a global peak of GHGs as soon as possible. ▪ Mitigation – The Paris Agreement establishes binding commitments by all parties to prepare, communicate, and maintain a nationally determined contribution (NDC) and to pursue domestic measures to achieve them. ▪ Sinks and reservoirs – parties are encouraged to conserve and enhance GHGs sinks and reservoirs. ▪ Finance and technology – The Paris Agreement reaffirms the obligations of developed countries to support the efforts of developing country parties to build clean, climate-resilient futures. ▪ Global stock take – To take place in 2023 and every five years thereafter, will assess collective progress toward achieving the purpose of the Agreement in a comprehensive and facilitative manner. ▪ Mitigation mechanisms – The accord aims to establish a new mechanism that will replace the CDM and JI frameworks. According to the Intergovernmental Panel on Climate Change, in order to limit warming to 1.5∘ C, CO2 emissions will have to fall by about 45% by 2030, relative to their 2010 levels. Limiting global warming to 2∘ C will require a transition to become a carbon-neutral economy by the middle of this century.

11.5

PRICE DRIVERS OF EMISSIONS MARKETS

Like all commodities the market clearing price will be determined by the interaction of demand and supply (Figure 11.1). In its simplest form, market participants will demand more of a product as the price falls. On the supply side, participants will provide greater volume in response to higher prices. The equilibrium or market clearing price is where demand and supply interact. However, within emissions markets the interaction of these two variables is slightly different than the classic economic representation. Figure 11.2 illustrates a possible interaction. The supply curve for emission allowances will generally be fixed on an annual basis although it is possible that certain schemes may allow for the use of ‘offset credits’ (e.g. CERs). The demand curve initially follows the traditional representation of sloping from top left to bottom right, but there are one or two anomalies. If demand exceeds supply, then participants will usually face a fixed fine, say, EUR 100.00. The level of

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Price

Price

Demand Volume

FIGURE 11.1 Classic demand and supply curves.

Fixed supply of allowances

Price of carbon

Price

Demand for allowances Volume of credits

FIGURE 11.2 Demand and supply within the emissions markets. Source: European Commission. this fine would place an upper limit on the price of allowances. In this scenario, no one would pay, say, EUR 110.00 for an allowance if the fine is set at a level that is EUR 10.00 lower. Also note the demand curve becomes more smoothed at higher prices. This could be reflective of the fact that allowances will always have some monetary value and if not used in the current compliance period could be carried over to the next period. Economic growth – As an economy expands it is likely that production of carbon and other industrial gases will increase. For action on global warming to be truly effective, an overall global limit on the amount of greenhouse gases produced would be needed. Politically this would be exceptionally difficult to achieve, as emerging countries such as India and China are unlikely to agree.

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Supply of allowances – If the supply of allowances is significantly larger than actual emissions then the price will fall. The aim of such schemes is to make sure that the supply is lower than the verified emissions to encourage a reduction in emissions perhaps by the implementation of new technology. The supply of allowances may also be impacted by political rather than economic decisions. Demand for allowances – The choice faced by installations subject to emission targets is whether they should invest in technology to reduce their emissions, therefore being able to sell any surplus allowances, or to simply buy their allowances from another market participant. Logically, participants will choose the lower cost option of either investing in abatement technology or buying allowances. Weather patterns and fuel prices – Since one of the biggest sources of emissions is power generation, weather patterns and fuel prices will influence the price of allowances. If a generator has the ability to substitute different fuel sources, such as coal or natural gas, they may compare the carbon-adjusted dark and spark spreads to determine the optimum fuel source. If the price of natural gas were to increase, combined with a period of cold weather, a generator may be encouraged to switch to coal as the primary fuel input. Since coal generates more greenhouse gases, the generators would need to buy more allowances to cover the increased use of the commodity. This should then drive up the price of allowances, the cost of which would be passed onto consumers in terms of a higher electricity price. Intuitively, there is a positive correlation between the prices of carbon and the prices of both power and gas. There is a negative correlation between the price of coal and the price of carbon. Penalties for non-compliance – These are determined by each country or region. Fees for non-compliance in the EU scheme have been established but irrespective of the charge, any breach of the targets will need to be made up in the following year. Alternative sources of electricity production – The cost of emissions will be affected by the planned increase in alternative low carbon technologies such as nuclear power and renewable sources. If such technological changes are expensive this will lead to an increase in the demand for allowances. Regulation – Since this is a business that is driven by government regulation there is always the risk that politicians may choose to change the rules of the game. Factors that might affect the price of allowances could include: ▪ The stringency of allowance allocations. ▪ Whether project-based credits can be included and the extent to which they could be used. ▪ Whether allowances or credits can be carried over between compliance periods. ▪ The perceived strength of the compliance regime used to police a particular scheme. Linkages with other energy markets – In an article entitled ‘The Energy Revolution’, Bond (Barclays, 2007) provides an interesting insight into the linkages that exist between different energy markets and the price of carbon. He argues that the early part of the twenty-first century may ‘be seen as an inflexion point in the global economic order’. He points out that the market is signaling that the supply of conventional energy

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sources needs to be increased, but political sentiment is moving away from the reliance on hydrocarbon-based fuels. ‘Put bluntly the world has simultaneously discovered that the supply of energy may not match future demand and that the type of energy currently supplied is incompatible with survival. Market prices signal the need for dramatic increases in the supply of hydrocarbon-based energy, while political shifts signal the need for an equally dramatic decrease in the use of hydrocarbon-based energy’. —Barclays, 2007 Furthermore, he argues the global economy needs to invest heavily in the energy infrastructure to meet a projected 50% increase in demand over the next 30 years. To avoid the worst consequences of global warming, however, there needs to be an 80% cut in energy supplied from fossil fuels to alternative sources. Bond points out that a positively sloped forward curve (i.e. a market in contango) signals a longer-term excess of demand over supply; a curve in backwardation would therefore be indicative of a shorter-term imbalance between markets (demand exceeding supply) and a longer-term excess of supply over demand. At the time the piece was written, forward curves for the energy markets that emit the most CO2 were in contango (e.g. coal, crude oil) while the curves for cleaner energy were backwardated (e.g. natural gas). Based on these observations he concluded: ‘We can deduce that as yet, the markets do not believe that policy changes will successfully reduce global demand for the dirtier fuels in favour of cleaner energy sources’. Although the quote may seem somewhat dated, there is a wider point in that interpreting forward curves in this manner can give some insight into the markets’ collective view on the efficacy of action on climate change.

11.6

EU EMISSION TRADING SYSTEM

‘The carbon market works like any other commodity market; companies trade and the market sets prices. But it is unusual in that the commodity being bought and sold does not exist: it is the certified absence of carbon emissions’. —The Economist – 9 September 2006

11.6.1

Background

The EU Emissions Trading System (ETS) was launched in 2005 and was the first ever emissions market. The market has evolved through different stages: ▪ Phase 1 (2005–2007) ▪ Phase 2 (2008–2012)

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▪ Phase 3 (2013–2020) ▪ Phase 4 (2021–2030) The system works on a cap and trade principle. This means that a cap is set on the total amount of GHGs that can be emitted by installations who operate within the scheme. This cap is designed to fall over time to achieve an overall reduction in emissions. The other main feature is that participants are either allocated or must buy allowances that permit to emit GHGs. Any unused allowances can be traded within the marketplace. Worked example: Let us say that two manufacturing companies A and B both emit 100,000 tonnes of CO2 per year and each entity is given 95,000 emission allowances. One allowance represents the right to emit one tonne of CO2 . So, neither company is fully covered for its emissions. At the end of each year, the companies must surrender the number of allowances that correspond the amount they have emitted during the year. If they fail to do so, they face a fine of EUR 100 per tonne. Companies A and B do not want to pay the fine and both must manage the excess 5,000 tonnes of CO2 . They have two ways of doing this. They can either reduce their emissions by 5,000 tonnes, or purchase 5,000 allowances in the market, either in the secondary market or via an auction. To decide which option to pursue, they will compare the costs of reducing their emissions by 5,000 tonnes with the market price for allowances. Suppose that the allowance market price is EUR 10.00 per tonne of CO2 . We will also assume that Company A’s reduction costs are EUR 5.00 (i.e. lower than the market price). Company A will reduce its emissions because it is cheaper than buying allowances. Company A may even reduce its emissions by more than 5,000 tonnes, say, 10,000 tonnes. For Company B, the situation may be the opposite: its reduction costs are EUR 15.00 (i.e. higher than the market price) so it will prefer to buy allowances instead of reducing emissions. Suppose Company A spends EUR 50,000 on reducing 10,000 tonnes at a cost of EUR 5.00 per tonne and receives EUR 50,000 from selling 5,000 excess allowances at the prevailing market price of EUR 10.00. So, from the perspective of Company A, the net cost to reduce their emissions by 10,000 tonnes is zero. In the absence of a trading scheme, they would have been forced to reduce their emissions by 5,000 tonnes and their net cost would have been EUR 25,000. From Company B’s perspective the cost of reducing their emissions by 5,000 tonnes would be EUR 50,000 (buying 5,000 allowances at a price of EUR 10.00). In the absence of the trading scheme, their cost of reducing their emissions would be EUR 75,000 (5,000 tonnes at EUR 15.00).

11.6.2

System design

At a conceptual level, the design of such a scheme is relatively straightforward: ▪ What emissions will be targeted? ▪ Which entities will be covered by the scheme? ▪ How is the right to emit GHGs evidenced?

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How will the allowances be distributed? How is ownership of allowances monitored? What is the level of the cap? How are emissions monitored and verified? How long will an allowance last if it is not used for compliance purposes? Should the system be linked to similar programs in different geographical locations?

Which emissions will be targeted? The system focuses on carbon dioxide (CO2 ), nitrous oxide (N2 O), and perfluorocarbons (PFCs). Which entities will be covered by the scheme? The sectors that are covered include oil refineries, steel works, iron, and steel works, aluminium producers, cement producers, glass, ceramics, pulp, paper, cardboard, acids, and bulk organic chemicals. From 2012, airlines became subject to the rules of the scheme. All airlines operating in Europe (European or otherwise) are required to monitor, report, and verify their emissions. How is the right to emit GHGs evidenced? Participants can only emit GHGs if they hold sufficient allowances. For the EU ETS these are referred to as European Union Allowances (EUAs). If they emit more than the allowances, they hold then they will be subject to a fine of EUR 100.00 per tonne. Each allowance gives the holder the right to emit one tonne of carbon dioxide or the equivalent amount of N2 O and PFCs. In the absence of global agreement as to how airline emissions should be handled the EU ETS decided to issue a separate category of allowances to airline operators referred to as European Union Aviation Allowances (EUAA). Airlines may use EUAs to meet compliance requirements, but the opposite does not hold, i.e. non-airline entities cannot use EUAAs to satisfy their emission commitments. How will the allowances be distributed? In phase 1, virtually all allowances were given away from free. This proportion fell to about 90% in phase 2 as the preferred method of auctioning allowances started to take effect. Although some allowances will still be given away for free the figure subject to auction is expected to gradually increase. This is based on the principle that the polluter should pay. Allowances are distributed on an annual basis and the main auction platforms are the European Energy Exchange (EEX) and ICE Futures Europe. The revenues generated from the sale of the auctions are returned to each EU member state and can be used to finance other climate-related projects. Typically, a proportion of the annual cap is auctioned every week. Free allowances are allocated at the end of February for the current compliance year.

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Allowances originating from the auction process are referred to as ‘the primary market’. The structure of the system allows the participants to transfer the ownership of these allowances on a price basis, which is referred to as the ‘secondary market’. The scheme also operates a New Entrants Reserve that can provide allowances for new projects aimed to mitigate the impact of climate change (e.g. carbon capture, renewables). The 2008 financial crisis had a very serious impact on the EU ETS as the fall in industrial production reduced the demand for allowances. By 2013 there was a surplus of 2.1 billion allowances, which resulted in very low prices. The EU addressed this in two ways. The first was to postpone the auctioning of 900 million allowances until 2019/2020. This is referred to as ‘back loading’ and did not reduce the number of allowances that were auctioned during phase 3, but merely changed the timing of their release. This reduced the surplus to 1.78 billion allowances by 2015. The second method was the establishment of a market stability reserve (MSR), which acts according to a set of pre-defined rules. If there is an excess supply of allowances the MSR can restrict the amount offered for sale at the annual auction. Currently, if the number of allowances in circulation exceeds 833 million then the next auction will be reduced by a figure of 12% of the amount available. The MSR can return the allowances under certain market conditions such as high prices (because of high demand) or low supply. So, when there are 400 million allowances or less in circulation a fixed annual amount of 100 million will be added to the amount to be auctioned. How is ownership of allowances monitored? The EU has established an online registry that records the ownership of allowances of each participant. Each participant will hold an account at the registry and any transfer within the secondary market will be recorded. The registry also records the verified emissions of each participant as well those allowances surrendered for compliance purposes. All transactions between accounts in the registry are checked and authorised by the European Union Transaction Log (EUTL). What is the level of the cap? Phase 1 of the ETS was designed as a trial period and during this time there was no reliable emissions data available to make a judgment as to the true level of emissions. As a result, caps were set based on estimates. These estimates proved to be too optimistic and as a result the market was oversupplied with allowances. Phase 2 saw the introduction of a single EU-wide cap which replaced the previous system of individual national caps. From 2021 onwards the overall number of emission allowances will decline at an annual rate of 2.2%. At the end of each year each participant must surrender enough allowances to cover all its emissions or face a fine. If the company has an excess of emissions at the end of the year it can use these allowances to cover its future needs or sell them to another company that is short of allowances.

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How are emissions monitored and verified? The ETS compliance cycle is an annual process. Each participant much monitor and report their emissions. The data for a given calendar year must be independently verified by 31 March of the following year. Once verified, the participant must surrender the equivalent number of allowances by the end of the following month, i.e. 30 April. The allowances are then canceled and cannot be used again. If actual emissions exceed the number of allowances surrendered the participant is subject to a fine of EUR 100.00 per tonne. How long will an allowance last if it is not used for compliance purposes? If a market participant has more allowances than are needed for compliance purposes, then broadly speaking they will have two options. They can sell any excess allowances on the secondary market or retain the allowances for the next compliance period. ‘Banking’ an allowance is the process of retaining unused allowances in one period to be used in the future. Any unused allowances need not be used in just the following year; they can be used in any future compliance period. Related to the concept of ‘banking’ is that of ‘borrowing’; this process allows a participant to use allowances from future periods to meet the current compliance requirements. Note that for the EU ETS, market participants must submit the required number of allowances for the previous compliance period by 30 April. However, the allocation of any free allowances for the current period is made by the end of February. In effect, this allows those participants who enjoy a free allocation to borrow from the current year to be compliant with the previous year. Should the system be linked to similar programs in different geographical locations? There is a movement towards linking trading systems around the world to encourage the development of a global market. As of the time of writing this has not yet been formalised. However, the EU ETS has allowed the partial use of international credits generated from the CDM and JI to be used by participants towards fulfilling part of their compliance obligations. It seems likely that this practice will be discontinued with the start of phase 4.

11.6.3

Cap and trade versus carbon taxes

One subject that is often debated is whether the cap and trade systems should be replaced by a direct tax levied by the government. Advocates of a tax argue that if the number of permits allocated is misjudged the price of carbon would increase or decrease significantly. Such price volatility may deter people from investing in green technology. They also point out that if the scheme operates by allocating a fixed amount (rather by auction), there is no adjustment for the fact that during a recession companies produce less and therefore pollute less. In the early phases of the EU ETS permits were given away for free but were tradable on the secondary market. This allowed some market participants to enjoy a windfall gain by selling their ‘free’ allowances. As well as raising revenue, a tax provides a clear price floor for carbon and hence a minimum return for investors willing to innovate in new green projects. Under a cap

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and trade scheme an invention that reduced the cost of cutting carbon emissions could push down the price of permits, reducing the investors’ returns.

11.7 11.7.1

EMISSION DERIVATIVES Introduction

In its annual ‘State and Trends of Carbon Pricing 2019’, the World Bank noted: ▪ Globally, there were 57 carbon pricing initiatives implemented or scheduled for implementation. ▪ These initiatives covered 11 gigatonnes (Gt) C02 e, which covered about 20% of GHG emissions. ▪ Prices within the different schemes varied from USD 1.00–127/tC02e. However, 51% of the emissions covered were priced at less than USD 10.00. ▪ The various schemes raised about USD 44 billion in carbon pricing revenues. For a participant who believes they will need to buy allowances, the decision as to when they should be bought during the year requires them to develop a view as to how prices could evolve during the period. They could: ▪ Buy the allowance for spot value and hold for the period. ▪ Buy the allowance for forward delivery. The price would be fixed at the trade date but paid at the contract’s maturity. If the maturity date for the forward matches the anticipated holding period for the spot ‘buy and hold’ transaction, then the costs should be identical. However, fair value pricing does not always hold in the market and is discussed in a subsequent section. ▪ Enter some form of option-based contract. Depending on the structure this may require the payment of a premium

11.7.2

Spot transactions

EUAs can be sold on a spot basis with delivery occurring one day after trade date. This could be done on an over-the-counter basis or via an organised exchange such as ICE or the EEX. Trades tend to be executed on a standardised number of allowances: 10,000, 25,000, 50,000, and 100,000 being typical. Futures EUA futures can be traded on exchanges such as EEX and ICE. The specification for the ICE EUA future is: Unit of trading: Currency: Contract series: Expiration date: Settlement:

One lot represents 1,000 EUAs EUR Quoted with monthly, quarterly, or annual settlement. Last Monday of the contract month. Physical by delivery and transfer of the EUAs from the seller’s account to the buyer’s account at the European Union Registry.

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Forwards Contracts traded on an OTC forward basis would be structured with a delivery date that would be agreed between the two participants. For example, transactions that have been traded include: ▪ A fixed price forward transaction would have similar characteristics to that of the future. It would be a physically settled purchase or sale of the EUA at a fixed price on a fixed date. ▪ A physically settled forward purchase at a fixed price for delivery on a pre-agreed date but where the seller has the right to deliver the allowance on an earlier date. If the seller delivers, they will receive a present-valued cash flow. ▪ A floating price forward will still commit the participant to either buy or sell the underlying allowance on a pre-agreed fixed date, but the price at which the trade would executed is not determined until sometime closer to the settlement date. Typically, the contract price would reference an average of some agreed index value such as a futures price. ▪ A floating price forward where the buyer has the right to nominate the volume of EUAs it wishes to price prior to the determination of the contract price.

11.7.3

Forwards – fair value pricing

Since the EUA is 100% fungible, the cost of an allowance for settlement between two different years in the same compliance period can be accounted for using standard forward pricing techniques (see Chapter 2). That is, a forward price can be calculated as the spot price plus the cost of borrowing money to buy the allowance. As of the day of writing (March 2020) spot EUAs were trading at EUR 18.40, while delivery for March 2021 was EUR 18.15. The analysis is somewhat complicated by the fact that 12-month wholesale borrowing rates were −0.25%, i.e. you can be paid to borrow money. A market participant who decides to buy a spot contract for EUR 18.40 and borrow the same amount to finance it would be required to repay about EUR 0.05 less than they borrowed (EUR 18.40 × −0.25% × 365 / 360). This would suggest that the fair value of the March 2021 contract should be EUR 0.05 lower than the March 2020 equivalent, i.e. EUR 18.35. The quoted market price is some EUR 0.20 lower than this ‘fair value’. Since firms receive their allowances from governments more than a year in advance before they need them for compliance purposes they could sell them for spot value (EUR 18.40) and buy them back under the terms of a forward or futures agreement at EUR 18.15. The cash proceeds they would be holding for the period would be economically equivalent to borrowing money at a negative rate of interest (approximately 1.34%).

11.7.4

Repurchase agreements

An extension of the physically settled spot and forward transactions is a process known as ‘inventory monetisation’. Under the terms of this transaction a corporate can use their inventory of EUAs to borrow money at an attractive rate. This is an instrument that has been used in several different financial and commodity markets for many years.

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Under the terms of the deal there will be two separate transactions executed simultaneously as a single package. The first deal is a spot transaction where the corporate sells their inventory of allowances to a market participant such as a trader at an investment bank. Under the terms of the second deal, the corporate agrees to buy back the same volume of allowances for forward delivery. The prices at which the two transactions are executed are determined using time value of money principles. Suppose that a corporate decides to use this mechanism to borrow money for a one-year period for a holding of one million allowances. A trader at the investment bank calculates that the 12-month forward price of the contract is EUR 15.00 meaning that the amount that the corporate will have to repay at the end of the period will be EUR 15,000,000. The amount that the corporate can therefore borrow at the start of the period is simply the present value of this sum. The trader sees that 12-month interbank borrowing rates are 5.00% and so decides to apply a credit spread of 0.50% to this rate. The present value of the forward proceeds is therefore EUR 14,207,772, which is calculated as EUR 15,000,000/(1 + (0.055 x 365/360)). The impact of the deal is that the corporate is effectively borrowing at a rate of 12-month Euribor plus 0.50%. Some readers may reasonably query why the bank did not simply use the current spot rate to determine the initial proceeds. Recall that in some commodity markets, the spot rate could be less liquid than the forward, with the latter being perceived as a more accurate measure of fair value. This trade would be advantageous to the corporate if they normally borrow money at a rate greater than 0.50% over 12-month Euribor. The profit to the bank depends on the strength of their balance sheet. To be able to finance the loan to the corporate, the bank will have to borrow in the money markets and if they can achieve this at say Euribor without any spread, they will also be able to profit.

11.7.5

Swaps

Emission swaps are financial in nature in that they are cash settled. They are only effective for one day and will involve an exchange of cashflows fixed for floating. In some respects, they are like single day contracts for difference that are popular in the equity markets. An indicative set of terms is shown below: Trade date: Effective date: Termination date: Pricing date: Delivery month: Commodity: Total notional quantity: Fixed rate payer: Fixed price: Floating price payer: Reference price: Settlement:

March (current year) 1 December (Year following trade date) 1 December (Year following trade date) 1 November (Year following trade date) 1 December (Year following trade date) EU Allowance 25,000 Company A EUR14.00 Bank LEBA – CARBON – INDEX on the designated pricing date for the relevant delivery date. Cash

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A swap contract would be useful if a participant wanted price protection but did not require physical delivery. Equally the contract would be useful for those participants who wished to express a view on the movement of allowance prices. It is financially settled, as it does not require ownership of an allowance to be transferred. The participants agree a cash settlement amount based on the difference between two prices.

11.7.6

Physical and cash-settled options

Underlying commodity: Notional quantity: Option style: Option type: Option seller: Option buyer: Reference price: Delivery month: Option expiration:

Strike price: Premium:

EUA allowance 30,000 allowances European Call Bank Client ICE EUA futures settlement price for contract delivery date December Nine months; to coincide with expiration date of December future (in this case the last Monday of the delivery month) EUR 20.00 (At-the-money forward) EUR 2.39/allowance. Total premium EUR 71,700

Notes: ▪ The transaction is an option on an exchange traded future. ▪ If the option is designated to be cash-settled the payoff to the call buyer will be: MAX (Underlying price – strike, 0). ▪ If the option is designated to be physically settled, then if the buyer chooses to exercise, they will take delivery of the agreed number of allowances that would be transferred into their emission allowance account. ▪ The ICE futures expire on the last Monday of the delivery month but given Christmas holidays and the contract specification this may be the earlier in the month. ▪ Implied volatilities for EUAs can be significant with values sometimes reaching more than 60%. A figure of 35% was used to value this option.

11.7.7

‘View driven’ strategies

Although the EUAs can be used to meet compliance with the emission targets, traders will also be looking for opportunities to execute more speculative transactions. Some simple trading strategies might include the following: Identifying a mispriced contract – Say for example, a trader believed that a futures contract due to mature in one year’s time was not trading at its fair value and was considered expensive. The trader could buy a spot contract and sell the forward. The trader

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could take delivery of the spot contract, finance the holding for a 12-month period, and deliver the allowance to meet the commitment created by the sale of the forward transaction. Buying and holding the allowance would realise the fair value of the position, which should be less than the proceeds received from the sold forward. Term structure slope trades – It is also possible to trade the futures term structure. This would be the purchase (sale) of a short-dated contract combined with the sale (purchase) of a longer-dated contract. This is referred to as ‘trading the calendar spread’ and is used to express a view on the price spread between two maturities. The trade would be closed out when the trader believed that prices had come back into line. Geographic arbitrage – If the price of an EUA is different on different exchanges in different geographical locations (e.g. ICE vs. EEX) a trader could buy and sell to exploit the differential. EUA / EUAA spread – Typically, EUAAs are a less liquid market than EUAs as the latter have great applicability. As a result, EUAAs tend to trade at a discount to EUAs. Spread trades can be initiated if a trader believes that the differential is not fundamentally justified. For example, if the trader believed that the discount is too high (i.e. EUAAs are trading significantly lower than EUAs), then the trader would buy the EUAA and sell the EUA. Option strategies – For those participants wishing to express views on volatility, the range of ‘classic’ option strategies such as straddles and strangles could be utilised. Volatility strategies were covered in Chapter 3.

11.8

WEATHER DERIVATIVES

‘I think it’s a perfect market. You can’t spook it, you can’t manipulate it. You can’t make people think it’s going to be 110 degrees in London next week,” he says. “And of course, weather is absolutely uncorrelated [to other asset classes]’. —Financial Times (2007) The common misconception relating to the difference between weather and climate was highlighted at the start of the chapter. Although weather derivatives have been traded for many years, the market is relatively small and niche. So, what is weather risk? Arguably from a corporate perspective it represents the potential adverse impact of weather on cash flow and profits. The classic representation of this is given by the impact of a cold summer spell on the sales of ice cream. However, other potential users might include insurance companies, farmers, or ski resorts. Quantifying their exposure to weather is anything but trivial. The first weather derivative was attributed to a 1997 swap transaction between Enron and Koch. Under the terms of the deal, Enron would pay Koch USD 10,000 for every degree the temperature fell below a predetermined level; Koch would pay the same for every degree above it. It may be tempting to think of a weather derivative as a form of insurance. The essence of insurance is to cover high-risk, low-probability events such as hurricanes or floods. On the other hand, weather derivatives protect revenues against low-risk, high-probability events such as mild winters that would reduce heating demand or wet

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summers. With insurance the claimant must prove that they have suffered some form of financial loss in order to be compensated. However, with derivatives an independent third party will establish whether a payout is due under the terms of the contract.

11.8.1

Potential industries

Examples of potential users include: ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪

Agriculture Aviation Construction Energy Film production Retail Tourism Wholesale

11.8.2

General characteristics

Some common weather derivative characteristics include: ▪ ▪ ▪ ▪ ▪ ▪ ▪

An underlying weather index or variable. Temperature (average temperature, heating degree days, cooling degree days). Precipitation (rainfall, snowfall). Apparent temperature (wind chill, heat index). A period over which the index is measured (e.g. month, season, or year). A weather station to report the underlying variable (e.g. London Heathrow). A dollar value for each index point move such that either the index or the variable can be ‘monetised’. ▪ A strike price for the index, which may be based on some historical value.

11.8.3

Exchange traded futures

The CME has traded weather futures for many years. The concept of Heating Degree Days (HDD) and Cooling Degree Days (CDD) were introduced in the electricity chapter (Section 8.4). These measures relate to the energy required to heat a space such as a room or a building. The metrics are expressed relative to some benchmark value such as 65∘ F. For actual temperatures below this benchmark, the space will require heating, while above this level it will require cooling. It is tempting to think that HDD refers to increases in temperature, but it is the opposite; the same is true of CDD. In relation to exchange traded futures, the definitions for each term is: ▪ HDD index – This index is based on the sum of the average degrees that the outside air temperature drops below the base temperature of 65∘ F (18∘ C for non-US cities) in the specified city each day in the contract month. This could be written as: HDD = SIGMA MAX (0,65∘ F − Actual temperature)

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▪ The HDD index will increase as the actual temperature falls relative to the stated average of 65∘ F. ▪ CDD index – This index is based on the sum of the average degrees that the outside air temperature rises above the base temperature of 65∘ F (18∘ C for non-US cities) in the specified city each day in the contract month. This could be written as: CDD = SIGMA MAX (Actual Temperature − 65∘ F, 0) ▪ The CDD index will increase as the actual temperature relative to the stated average of 65∘ F increases. ▪ Reference is sometimes made to a Cumulative Average Temperature (CAT) index. This index is based on the sum of the average temperatures recorded in the specified city for each day in the contract month. As an example of a futures contract consider the following contract specification: Contract name: Contract unit: Price quotation: Minimum price change: Settlement: Reference city:

US monthly weather Cooling Degree Day USD 20.00 times the respective CME Degree Days Index Dollars per index point One index point Cash-settled Dallas, Texas

By way of illustration, suppose that the futures index value for the month of August is quoted at 691. To calculate the index, it is necessary to record the mean air temperature each day. If it was 100∘ F in Dallas on a particular day the index would be recorded as 35 (100∘ F − 65∘ F). If the temperature recording returned a value of 60∘ F then the index would take a value of 0. Typically, these calculations are done daily and then summed to determine a monthly or annual value. Note that the value used in this example was based on a quote given in March of the same year so it suggests that traders will require some form of model to predict the weather. The most known models are: ▪ The Global Forecast System (GFS) from the USA. ▪ The European Centre for Medium Range Weather forecasts (ECMWF) from Europe. The futures methodology then assigns an arbitrary fixed value of USD 20.00 (‘tick size’) to each of those index points. The absolute value of this tick size is to an extent irrelevant as it is the same for all the participants. So, the August contract analysed earlier will have an associated monetary value of USD 13,820 (691 × USD 20.00). Readers familiar with equity derivative index futures will recognise this method of ‘monetising’ an index value.

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11.8.4

Over-the-counter structures

Some typical characteristics seen in OTC trades are: ▪ Deals can be structured to cover a wider array of underlying exposures such as precipitation, snowfall, wind speed, and sunshine hours. However, transactions that reference temperature are the most popular. ▪ May be able to accommodate any basis risk. That is, there could be a difference between the weather at an official station and the affected site. Arguably this is more relevant for precipitation than temperature. ▪ They will be traded for monthly, season, or annual periods. ▪ HDDs for winter months would typically be defined as October–April, while CDDs for summer months would cover the May–September period. Autumn would be defined as September–November, and Spring as March–June. ▪ The transaction will reference a given city (e.g. Dallas, Texas) or weather station (e.g. London Heathrow). Most weather observations are sourced from government-run weather stations that follow standards set out by the World Meteorological Organisation. ▪ Weather data is usually ‘cleaned’ as they sometimes contain errors or missing data. There is no single market-wide technique used to clean data. ▪ Each transaction will have an associated tick value, which will determine the magnitude of the payout. In the Enron/Koch swap example cited earlier this was USD 10,000. The tick value is negotiated between counterparties but could be 1,000, 500, or 200 in the respective currency. ▪ Transactions may be relatively short dated (e.g. current month or month ahead). ▪ Payments may be capped as, theoretically, there is no maximum or minimum value for an observed temperature.

11.8.5

Swaps

A possible swap transaction could be: Underlying commodity: Trade date: Effective date: Maturity: Tick value: Fixed index value: Floating payment:

Cooling Degree Days 1 March 1 August One month (e.g. the month of August) USD 500.00 per index point 691 Average of daily observed CDD index for Dallas, Texas

The settlement amount for this swap could only be calculated in the month that follows the chosen period. To calculate the floating amount, the transaction participants would need to collect a daily value of for the index, which will then be averaged to calculate a settlement value. Suppose that the observed CDD value for the

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month of August turns out to be 700. The difference between the observed and initial fixed index value is 9 points. With a tick value of USD 500.00 per point this would equate to a payment of USD 4,500 by the floating payer.

11.8.6

Options

From an option perspective both vanilla and exotic structures have been traded. The payoff of a call option referencing weather would be: Dollar value (tick value) of an index point × MAX (Index level − strike, 0) The payoff of a put option referencing weather would be: Dollar value (tick value) of an index point × MAX (Strike − Index level, 0) The exotic structures have tended to be binary options where the option buyer would receive a fixed payoff if the option is exercised, irrespective of how far above the option is in the money.

11.8.7

Applications – cattle industry

Suppose a cattle farmer has analysed the impact of weather on his livestock and concludes that he has an exposure to below average temperatures in the autumn and above average temperatures in the spring. For example, excessive heat may limit the growth of animals in the spring, while younger animals may suffer if the temperature is very cold. Weather could have an indirect impact on cattle costs as it may impact crop yields which would influence the price of animal feed. One solution using options would be: ▪ The purchase of a call option on a CDD index for the spring period. As the temperature rises above the agreed strike, business losses will be offset by a payout on the option. ▪ The purchase of a call option on a HDD index for the autumn period. For every index point that the temperature falls below strike in the fall the farm will receive a payout on the call option. Readers may reasonably question why a call option rather than a put option has been used for the HDD structure. Recall that any HDD index will increase in conditions of relatively cold weather. If the actual recorded temperatures in Fahrenheit over a one-week period were 60, 55, 58, 61, 59, 56, 62 then the HDD index would be 44 (5 + 10 + 7 + 4 + 6 + 9 + 3). So, as it becomes colder the realised HDD index would increase. Using these figures, the buyer of a one-week call option with a HDD index strike of, say, 0 and an agreed dollar value per index point of USD 200.00, would receive a payout of USD 8,800 (USD 200.00 × 44). The strikes could be set either based on historical average temperatures or around temperatures that the farmer considers optimal for feeding purposes. If the farmer believed that in the autumn period (91 days) losses would be incurred when temperatures were below 40∘ F he may choose a strike of 2,275 ((65−40) × 91) for the period.

Climate and Weather

11.8.8

393

Applications – power utilities

A power utility in the US mid-west has determined that they have exposure to weather risk in the summer. This is mainly driven by the demand for air conditioning units so when it is cool there is less demand for electricity and therefore profits will fall. As a result, they decide a hedge that references an average temperature would be appropriate. They determine that for every 1∘ F the temperature is below the current long-term average, they will lose USD 50,000. There could be several different ways to structure the transaction: Buy a put option – This would reference the average temperature with the strike set at an appropriate level that suits the client’s tolerance with respect to the upfront premium payment, the amount of downside risk and their ability to benefit from temperature increases. For example, an OTM put option, which reduces the premium would have the strike level set below the long-term average temperature. Zero premium collar – This would be structured as the purchase of an OTM put along with the sale of an OTM call. The put option would provide the required downside protection and the strike of the sold call would be set at such a level that the upfront payment would be eliminated. It would mean that the client would not be able to benefit from an increase in temperatures above the strike of the call. This type of structure is also referred to as a min-max transaction and was covered in greater detail in Chapter 5. Swap structure – This would have the effect of fixing the company’s exposure to temperatures to a given level. There would be no downside risk if temperatures fell, as they would receive under the swap but neither would there be any upside participation, as the swap would require the client to make payments under the terms of the transaction. Again, since there is theoretically no maximum or minimum value for temperature, each derivative component may incorporate a limit on the payouts in either direction (e.g. USD 300,000).

CHAPTER

12

Agriculture

12.1

AGRICULTURAL MARKETS

When discussing this segment of the commodity market it is often convenient to distinguish between two main sub-categories. Soft commodities include products such as coffee, sugar, cocoa, and cotton. The production of these commodities is often concentrated in a small group of developing countries and as such can be prone to output problems. Agricultural commodities are typically widely produced in developed countries. For example, wheat is widely produced and as a result farmers can usually respond quickly to rising prices by expanding their acreage.

12.2

DEFINITIONS

As ever, it is always useful to define some relevant terms: Supply – this usually comprises of three main components: ▪ Surplus stocks left over from the previous year. This could be referred to either as ‘inventory’ or sometimes ‘carry in’. ▪ Production from the current year. ▪ Imports. Demand – typically comprises of two elements: ▪ Domestic use ▪ Exports Carry over – this is defined as the remaining supply from the previous year plus current year production plus imports. Stocks to use ratio – this is defined as the current year ending stocks divided by current year use. As a rule of thumb, in ‘normal’ markets the ratio should be 20–40%. A lower ratio could indicate market ‘tightness’ and possibly increased price volatility.

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Agriculture

12.3

AGRICULTURAL PRODUCTS

12.3.1

Physical supply chain – wheat

The physical supply chain (Figure 12.1) for grains such as wheat would typically start with private farmers who would grow the crop. This source of supply could either be domestic or could comprise of imports. The farmers would store this temporarily in their own silos before selling it to a larger commercial trader referred to generically as a grain elevator (although strictly speaking a grain elevator is a term used to describe a building used to store grain before onward shipment). These larger commercial traders (e.g. Cargill) could accumulate and combine the production of several smaller farmers. They may also perform activities such as inspecting, cleaning, and blending. These commodity trading houses in the agricultural markets are dominated by four main entities, referred to as the ABCDs. ▪ ▪ ▪ ▪

Archer Daniels Midland Company Bunge Ltd. Cargill Inc. Louis Dreyfus Co.

The next stage is milling, whereby the wheat is ground and sifted to make flour for human consumption and mill feeds, which are sold as animal feed. The final stage is the baking process, which would produce breads and cakes. Flour can also be used in the production of pasta-style products or for home baking. This part of the market would include well-known household names such as General Mills, Kellogg, and Kraft. The final product would then be sold to the end consumer either through a shop or restaurant.

Bakery

Retail outlets

Farmers

Consumer Merchant / elevator

Flour mills

Other manufacturers

Imports Animal feed

FIGURE 12.1 Simplified physical supply chain for wheat.

Restaurant

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Wheat

There are several varieties of wheat, but its main use is in the production of flour, which is then used in foods such as bread and pasta. Although there are many different ‘species’ of wheat, the US produces six different types: ▪ Hard Red Winter – used for milling baking flour, Asian noodles, hard rolls, flat breads, tortillas, and general-purpose flour. ▪ Hard Red Spring – sometimes referred to as the ‘aristocrat’ of wheat used for rolls, croissants, bagels, and pizza crusts. ▪ Soft Red Winter – used in cookies, crackers, pretzels, pastries, and some flat breads. ▪ Durum – pasta, couscous, and Mediterranean breads. ▪ Hard White – similar uses to hard red winter. ▪ Soft White – cakes and pastries. The spring/winter classification relates to when they are planted with most of the production being based in the Midwest and eastern states. Figures used in the first edition of this text indicated that global production for 2006–2007 was approximately 585 million tonnes, while consumption for the same period has been estimated at 613 million tonnes. By 2020 the figures were 764 million and 754 million, respectively. Both figures indicate that production and consumption are rarely equal indicating that the level of inventories is a key price driver. In terms of production by region (Figure 12.2), the EU accounts for 26% of the global total. The second largest producer is China at 23%, followed by India (17%), Russia (15%) and United States (8%). In term of consumption by country (Figure 12.3), the single biggest consumer of wheat is the EU, which consumes 21% of all wheat. China accounts for 20% of the global total, India accounts for 16%, while the figure for the USA is 5%.

12.3.3

Corn

Traditionally corn (sometimes referred to as maize) has been used as a feed for livestock. However, it has applications for human consumption such as sweeteners for soft drinks. However, the demand and supply dynamics of this product can be impacted by the price of oil, as farmers may be tempted to direct their output towards the production of ethanol. Global production of corn in 2006–2007 was estimated at 689 million tonnes, while the figure for consumption was 724.1 million tonnes. Like wheat, both production and consumption has increased significantly so that by 2020 the figures were 1,111 million tonnes and 1,135 million tonnes, respectively. The largest producer of corn is the USA (Figure 12.4) accounting for about 34% of the global total. China is the second largest producer (24% of the total), with the next largest being Brazil (7%) and the EU (6%). The United States consumes about 28% of global production (Figure 12.5), while the respective value for China is 25%, the EU is 7%, and Brazil is 6%.

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Agriculture USA 52,258

EU 154,000

Russia 73,500

India 102,190

China 133,590 U.S. Department of Agriculture

FIGURE 12.2 Wheat production (thousand metric tons). Source: USDA, www.ers.usda.gov USA 31,706 Russia 39,500

China 128,000

India 98,000

European Union 127,000

FIGURE 12.3 Wheat production (thousand metric tons). Source: USDA, www.ers.usda.gov

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS Argentina 50,000 European Union 65,000

Brazil 101,000

USA 347,782

China 260,770

FIGURE 12.4 Corn production (thousand metric tons). Source: USDA

Mexico 44,500 Brazil 66,500

USA 313,578

European Union 82,500

China 279,000

FIGURE 12.5 Corn consumption (thousand metric tons). Source: USDA

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12.3.4

Palm oil

Palm oil is one of the major edible oils and fats that are traded on a global basis. Other competing products include soya bean oil and rapeseed oil. Palm oil can be used for a variety of purposes reflecting the different applications of agricultural products: ▪ Food products – cooking oils, shortening or dough fats, and margarine. ▪ Chemical feedstock – used in cosmetics, toiletries, industrial cleaning agents, and candles. ▪ Fuel – can be used in the production of biodiesels. Most palm oil (70%) is used within the food industry with the remainder (30%) used for industrial purposes (Figure 12.6). Production is dominated by Indonesia and Malaysia who make up nearly 85% of all production (Figure 12.7). This is because oil palms can only be grown in countries with a tropical climate that is 10∘ N or 10∘ S of the Equator. The major importers are India, the European Union, and China (Figure 12.8). There are three main types of oil palm: Dura, Pisifera and Tenera, the latter of which is the most used in commercial production. The production cycle is relatively short and so the production response to higher prices is relatively quick. There is a nursery stage of 12–18 months before planting with the first harvest and can be harvested around 30 months later. The oil palm will have a lifespan of about 25–30 years with peak production in years 8–15. Since the plant is grown in a tropical climate it can be harvested all year round. Barclays (2011a) estimates that as a rule of thumb, one hectare can produce about four tons of palm oil although this will vary depending on the fertility and toxicity of the land and the incident of diseases.

80 70 60 50 40 30 20 10 0 2007

2008

2009

2010

2011

2012

2013

Industrial use

2014

FIGURE 12.6 Usage of palm oil (millions metric tons). Source: USDA

2015

Domestic use

2016

2017

2018

2019

2020

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Thailand 3,000

Colombia 1,680 Nigeria 1,015

Malaysia 19,800

Indonesia 42,500

FIGURE 12.7 Production of palm oil (thousand metric tons). Source: USDA

Philippines Egypt 1,150 USA 1,220 1,550 Bangladesh 1,700

India 9,750

Pakistan 3,350

China 7,200

FIGURE 12.8 Importers of palm oil (thousand metric tons). Source: USDA

European Union 7,300

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12.3.5

Soybeans

Soybeans are believed to have originated in China before appearing in Europe about 300 years ago. They are generally planted in the spring (April and May), but can be planted as late as July. If the crop is planted later in the year there is a possibility that it could be damaged by frost, which would reduce supply and potentially lead to higher prices. Soybeans are classified as an oilseed, a category that also includes peanuts, sunflower seeds, and rapeseed. The first step in the production lifecycle is the removal of the outer skin of the bean, which is referred to as the soy hull. This can be used as feed for the dairy industry. The bean could then be consumed as food or crushed (with or without the hull) to produce soybean meal and soybean oil. Christian (2006) argues that this crushed material is sometimes used as a proxy for demand although not fully accurate as it does not reflect the fact that some beans are consumed without crushing and other beans are used as seeds for the following year. Soybean meal is used as a feed for livestock while soybean oil can be used for human consumption (soy milk, oils, and dressings) as well as applications as diverse as soap and explosives. Figures 12.9, 12.10, and 12.11 show the production of soybeans, soybean meal, and soybean oil; the so-called ‘soybean complex’.

China 18,100

Argentina 54,000 Brazil 126,000

United States 96,841

FIGURE 12.9 Production of soybeans (thousand metric tons). Source: USDA

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Brazil 33,950

United States 44,881

FIGURE 12.10 Production of soymeal (thousand metric tons). Source: USDA

Argentina 8,500 China 15,411

Brazil 8,400

United States 11,018

FIGURE 12.11 Production of soy oil (thousand metric tons). Source: USDA

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12.4 12.4.1

SOFT COMMODITIES Sugar

According to the International Sugar Organization (2020): ▪ About 110 countries produce sugar. ▪ Sugar can be produced from either cane or beet, but production is dominated by cane, which accounts for about 80% of output. Beet tends to be grown in the Northern Hemisphere while cane is produced in the Southern Hemisphere. ▪ The main producing countries are India, Brazil, Thailand, China, USA, Mexico, Russia, Pakistan, France, and Australia. These countries account for about 70% of output. ▪ Sugar can be used for food, animal feed, and fuel (sugar-based ethanol). ▪ By 2018 the annual consumption of sugar was just over 172 million tonnes. Although overall consumption continues to increase, in recent times the rate of growth has decreased. ▪ The main consuming markets are India, EU, China, Brazil, USA, Indonesia, Russia, Pakistan, Mexico, and Egypt. ▪ Approximately 64 million tonnes of sugar are traded internationally. Brazil, Thailand, the EU, Australia, and India accounted for 70% of exports with the market being dominated by Brazil. The major importers are Indonesia, China, and the USA.

12.4.2

Coffee

The International Coffee Organisation (ICO) defines coffee in a somewhat formal manner as ‘(a) general term for the fruits (cherries) and seeds (beans) of plants of the genus Coffea, as well as products from these fruits and seeds in different stages of processing and use’. Coffee bean structure When a coffee plant matures, the fruit, which contains the bean, will have either a red or yellow external colour. Each plant will have several outer layers, which cover the coffee bean. The next layer is the pulp, which consists mainly of water and sugar and is removed and can be used as compost. The mucilage is a sweet coating, which can be used to make jelly. The parchment is the last outer layer before the bean, which can be transformed into either mulch or paper. The coffee bean (a.k.a. the seed) is protected by a silver skin, which has applications as a cigarette filter. Where is coffee grown? Coffee is indigenous to Africa with arabica believed to have originated in Ethiopia and robusta from the Atlantic coast. The bulk of coffee is produced in Latin America with Brazil the dominant grower. The other major producers are Vietnam, Colombia,

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Indonesia, and Honduras. It is also common to refer to either the ‘bean belt’ or ‘coffee belt’, which is a region that sits between the Tropics of Cancer and Capricorn where the environmental conditions for growing coffee are ideal and encompasses the majority of production. Types of coffee There are two main types of coffee bean that are traded internationally: arabica and robusta. Two other types exist (excelsa and liberica) but these are only produced in relatively small quantities. Internationally traded coffee is often referred to as beans, which is a commercial term used to describe the dried seed of the coffee plant. Arabica is often perceived as having a smoother flavour while robusta is relatively bitter and often used for instant coffee. The ICO reports four categories of coffee from different countries each group having distinctive characteristics: ▪ Brazilian natural arabicas – coffees from Brazil, Ethiopia, Paraguay. ▪ Colombian mild arabicas – Colombia, Kenya, Tanzania. ▪ Other mild arabicas – made up of 22 countries such as Costa Rica, Peru, and Rwanda. ▪ Robustas – made up of 23 countries such as Ghana, Indonesia, and Vietnam. Reference is sometimes made to ‘specialty coffee’. Arguments abound as to how this is actually defined but the Specialty Coffee Association (SCA) describes it as ‘coffee that met all the tests of survival encountered in the long journey from the coffee tree to the coffee cup’. So, this perspective does not look exclusively at the quality of the bean but the entire supply chain process. Readers interested in the technical standards applied by the SCA are referred to their website. Overview of production process The plant will first produce a flower followed by the fruit, which contains the final bean. Each plant will take about three to four years from first planting to produce coffee and with careful management will last about 25 years. The fruit is then harvested, washed to remove any dirt or stones, and then dried for one to two weeks to remove as much moisture as possible. The beans are then packaged into sacks and sent to a warehouse where they will typically spend between six months to a year maturing to improve their flavour. Some producers will mature them for up to three years as they will keep quite well if they are completely dry. Roasting is done at temperatures of 190–250∘ F. The longer the roast time, the darker and more flavorsome the coffee becomes, and vice versa. Some roasting examples include: ▪ 8 minutes – Light roast ▪ 12 minutes – City roast (style of roast preferred in the US)

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▪ 20 minutes – Italian roast ▪ 24 minutes – French roast ▪ 26 minutes – Extreme dark Once roasted the beans are ground and are then ready to be brewed into the final drink. As a rule of thumb, it takes about 10 lbs. of beans to produce 2 lbs. of coffee. Amount of caffeine The following types of popular drink contain different amounts of caffeine: ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪

Decaf – 3mg Hot chocolate – 19mg Green tea – 20mg Shot of espresso – 27mg Can of cola – 40g Black tea – 45g Energy drink – 80mg Instant coffee – 82mg Brewed coffee – 95mg

Different forms of coffee When discussing coffee, reference is often made to coffee in different forms at different processing stages: ▪ ▪ ▪ ▪

Green coffee captures all coffee in the naked bean form before it is roasted. Dried coffee cherry means the dried fruit of the coffee tree. Parchment coffee means the green coffee bean contained in the parchment skin. Roasted coffee means green coffee roasted to any degree and can include ground coffee. ▪ Decaffeinated coffee means green, roasted, or soluble coffee from which the caffeine has been extracted. ▪ Liquid coffee means the water-soluble solids derived from roasted coffee and put into liquid form. ▪ Soluble coffee means the dried water-soluble solids derived from roasted coffee. Production and consumption statistics The concept of a ‘marketing year’ is often referred to with respect to agricultural commodities. This is typically a period of one year where data such as production and consumption trends are reported and analysed. This period may or may not coincide with the harvest period but may be determined by wider market activity. Since coffee is produced in different regions each will have their own harvest date and so the ICO adjust all the data such that it is all reported on a common basis matching the marketing

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year. For example, the International Coffee Organisation (ICO) has a marketing year that commences on 1 October that attempts to capture most harvest dates. Production is often described in terms of units of 60-kilogram bags. For 2019 the ICO estimates production at approximately 168 million 60-kg bags, with consumption being a little higher. Production of the two main coffee types was 96 million 60-kg bags with Arabica accounting for an estimated 72 million 60-kg bags. From a geographical perspective, the relative production and consumption values are shown in Figures 12.12 and 12.13.

Market structure Figure 12.14 aims to capture in a simplified manner the different stages of the coffee supply chain. In many countries (e.g. Costa Rica) coffee is largely produced in small-hold operations although larger production facilities exist. A local co-operative could then act as a single point of contact to collect the different sources to create an overall larger volume that could be sold commercially. The beans could then be sold either to a trading house acting as an intermediary or directly to a roaster. These roasters will then transform the beans into different flavours of coffee by roasting and/or blending various beans.

Africa 11%

South America 46%

Asia & Oceania 30%

Mexico and Central America 13%

FIGURE 12.12 Global coffee production by region. Source: International Coffee Organisation

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Agriculture Africa 8% North America 23% Asia & Oceania 26%

Mexico and Central America 4%

Europe 39%

FIGURE 12.13 Global coffee consumption by region. Source: International Coffee Organisation Smaller producer

Co operatives

Larger producer

Initial processing

Initial processing

Trading house

Example • Louis Dreyfus

Roaster

Example • Specialist • Retail coffee shops (e.g. Starbucks) • Commercial producers (e.g. Kraft)

Retail outlet

Example • Shop • Coffee shop • Supermarket • Institutional

End product

Example • Beans • Ground • Soluble • Decaf • Ready to drink cans

FIGURE 12.14 Simplified coffee supply chain. Roasters range in size from small specialist operations to the very large commercial producers. By way of illustration the following quote is taken from the 2019 Starbucks annual report: ‘To ensure compliance with our rigorous coffee standards, we control substantially all coffee purchasing, roasting, and packaging and the global distribution of coffee used in our operations. We purchase green coffee beans from multiple coffee-producing regions around the world and custom roast them to our exacting standards for our many blends and single origin coffees’.

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The final product could then be sold in a variety of different retail outlets such as branded coffee shops or supermarkets. The end retail product could consist of items that vary from the simple whole bean to ready-to-drink coffee in a can. Prices Like many products the coffee market tends to rely on a futures price for the pricing of commercial contracts. In its annual report Starbucks says: ‘Although most coffee trades in the commodity market, high-altitude arabica coffee of the quality sought by Starbucks tends to trade on a negotiated basis at a premium above the “C” coffee commodity price. Both the premium and the commodity price depend upon the supply and demand at the time of purchase. Supply and price can be affected by multiple factors in the producing countries, including weather, natural disasters, crop disease, general increase in farm inputs and costs of production, inventory levels and political and economic conditions. Price is also impacted by trading activities in the arabica coffee futures market, including hedge funds and commodity index funds’. The ‘C’ coffee price refers to the futures price for arabica coffee traded on exchanges such as the ICE. Like all futures exchanges it can be used as a source of supply, a risk management and trading venue, as well as a pricing basis for commercial transactions. The C contract references arabica beans of a specified grade from one of 20 countries. Since no two beans will be perfectly identical any beans that will be physically delivered are tested for grade and flavour. Grading can be based on criteria such as: ▪ ▪ ▪ ▪ ▪

Altitude or region Preparation Bean size, shape, colour Number of defects Flavour

The exchange uses certain coffees to establish a baseline (e.g. Mexico and Costa Rica). Certain coffees are judged to be of a higher quality and are priced at a premium (e.g. Colombia), while those judged inferior are priced at a discount (e.g. Brazil). Note that the premium mentioned in the Starbucks quote relates to bilaterally negotiated contracts and is therefore variable. The premium used in the futures market is a fixed value established by the exchange, which is applied to the final invoice if physical delivery were to take place. The ICO also publishes a series of prices, which are designed to track the spot prices of the four main coffee categories established by the organization. They also produce a Daily Composite Indicator price that combines all these prices to give a single measure that represents the current international coffee price.

12.4.3

Cocoa

According to the International Cocoa Organisation, cocoa is produced in countries in a belt between 10∘ N and 10∘ S of the Equator, where the climate is optimal for growing

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cocoa trees. The largest producing countries are the Ivory Coast, Ghana, and Indonesia. In terms of consumption, the EU region followed by the USA account for most of the demand. Within the market, consumption is not measured directly but is inferred from the amount that enters the grinding stage of the process. The plant can be harvested all year round but generally needs opposite conditions to coffee, i.e. lower altitudes and higher temperatures. From its initial planting it will take about 1.5 years for a plant to flower then another six months before the fruit (known as pods which contain the cocoa beans), are produced. The outer husk of the plant can be used as compost. Inside each pod there are several beans contained within a milky fluid. This white fluid and the beans are then left to ferment for up to a week before separation. The beans are then dried for one to two weeks to remove any moisture. The beans are then roasted for about five minutes at 50∘ C to make them ‘crunchy’ such that the outer shell can be easily removed. The inner ‘nibs’ are then ground to create cocoa liquor, which has the consistency of paste. This paste is then pressed, which separates into cocoa butter and ‘presscake’. The cocoa butter is used in the production of chocolate and has applications in cosmetics (e.g. lotions) while the presscake is pulverised to form cocoa powder. There are three main types of chocolate: ▪ Dark – cocoa, sugar, and fat, ▪ Milk – cocoa, sugar, fat, and butter, ▪ White – cocoa, white sugar, fat, powdered milk. The world cocoa market distinguishes between two broad categories of cocoa beans: ‘fine’ or ‘flavour’ beans and ‘bulk’ or ‘ordinary’ beans. In terms of market structure, at a very high level it will resemble the illustration in Figure 12.4. The largest confectionery company is Mars Wrigley, and they may wish to buy the beans directly from source before processing and producing the final product. There are also smaller entities such as Hotel Chocolat in the UK that specialises in the production and retail sale of ‘luxury’ chocolate produced from their own plantation in Saint Lucia.

12.5

ETHANOL

‘If you look at the ethanol landscape worldwide, the US and Brazil are like Kuwait and Saudi Arabia’. —Fabrizio Vichichi – Financial Times, 26 January 2006

12.5.1

What is ethanol?

Ethanol has the simplest chemical structure of the hydrocarbons within the family of alcohols. In chemistry, alcohol is used to describe a hydrocarbon with an -OH group attached to a carbon atom. Ethanol is just one of many alcohols, though the words are sometimes incorrectly interchanged in the media. When ethanol is produced for fuel, the goal is to maximise its strength and minimise any impurities. As a result, the primary production inputs such as corn and sugar cane

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are chosen for their ease of cultivation and their high carbohydrate levels. The energy to input ratio for ethanol from sugarcane is 8.3 versus 1.9 for sugar beets and 1.8 for corn. Initially the corn or other crop is mashed and then heated to destroy any bacteria or other microorganism that may interfere with fermentation. The mash is then cooled and yeast is added. The yeast feeds on the mash releasing carbon dioxide and ethanol. Since the carbon dioxide is a gas, it bubbles out of the fermenting mash leaving the ethanol behind. At this stage, the ethanol contains many impurities, which, along with any water, are removed by distillation. Any remaining impurities are removed by using a molecular sieve. Proponents of ethanol produced from sugar cane argue that when used as a fuel it is environmentally friendly; the carbon dioxide produced from burning it is neutralised by the carbon dioxide absorbed by the plants from which it is grown. However, counter arguments point out that the increased demand for sugar cane in Brazil may encourage production to expand into environmentally sensitive areas such as the Amazon. Critics also argue that some of the technology used to produce ethanol requires a substantial power input, which may offset any perceived environmental benefits. Other issues relate to the use of fertilisers for the rapid and efficient growth of the sugar and corn. Fertilisers are synthesized industrially from ammonia, which is made from nitrogen and hydrogen. The latter is obtained from hydrocarbon reserves with the inevitable production of carbon dioxide, and so any ‘green’ benefits derived from ethanol may be limited. There are alternative biofuels that include: ▪ Cellulosic ethanol – uses a variety of other materials such as waste plant material to produce the ethanol, without as many side effects. ▪ Biobutanol – produced from sugars like ethanol and has a higher energy content. Can be used in higher concentrations in existing car engines. ▪ Biodiesel from energy crops – this is biodiesel produced from oil from plants that can be grown on land not suitable for food production. ▪ Biomass to liquids – Biodiesel produced by taking gas from decomposing vegetation and turning it into a liquid. At the time of the first edition of this text, world production in 2004 for ethanol was estimated at 10.7 billion gallons (approximately 49 billion litres) and 12.1 billion gallons (55 billion litres) in 2006. (Financial Times, 9 May 2006). By the end of 2018, production was approximately 24 billion gallons (108 billion litres).

12.5.2

History of ethanol

According to the International Sugar Organisation (2020), ethanol for fuel can be used in two ways: ▪ It can be blended with gasoline to reduce petroleum use, boost octane ratings, and cut exhaust emissions. ▪ ‘Pure’ ethanol, defined as a fuel made up of 85–100% ethanol, which can be used in specially designed engines such as flexifuel vehicles.

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Arguably the first significant use of ethanol as a biofuel was in Brazil in the 1970s. At the time, Brazil imported 90% of its crude oil so the government acted to reduce the impact of rising prices. Through a series of subsidies to sugar mills, ethanol was promoted as an alternative fuel source. By the 1980s, new car production was focused almost exclusively on cars that ran purely on ethanol. However, this first boom was short lived because of a combination in factors: ▪ The country struggled to produce sufficient sugar cane to meet demand. ▪ The government lifted controls on the pump price of the fuel, leading to an increase in price. ▪ An increase in the global price of sugar, which encouraged producers to switch back to using the raw material to make refined sugar. ▪ Mediocre performance of the vehicles. ▪ Subsequent price collapse of crude oil, making gasoline relatively attractive. However, in 2003 the country introduced flexifuel cars, which operate either on ethanol or petrol or a mixture of the two fuels. By 2006 estimates suggested that 50–75% of all domestic new car sales were of the flexifuel variety and that about half of the country’s sugar cane crop was being used for domestic ethanol production. As a result of their knowledge and experience gained in the 1970s and the relatively low-cost nature of their ethanol operations, Brazil became known as the ‘Saudi Arabia of biofuel’. However, based on current statistics, the USA produces about 56% of all ethanol, while Brazil produces just 28%. In the USA, about 40% of the annual corn crop is processed into fuel ethanol (Financial Times, 2019a). Traditionally, the government has offered a range of incentives (e.g. government mandates, tax relief, import tariffs) along the supply chain to encourage production and consumption. The demand for ethanol in the USA was boosted when the government banned the gasoline additive MBTE (methyl tert-butyl ether) for environmental reasons. As a substitute, ethanol is now added to gasoline in concentrations of between 10% (so-called E10 fuel) to 15% (E15). Beyond this level most normal internal combustion engines experience operating difficulties unless they have been specially converted. In Europe, ethanol is produced from sugar beet (12.1 million tonnes), maize (4.1 million tonnes), wheat (3.9 million tonnes), barley (0.4 million tonnes) and rye (0.4 million tonnes).

12.5.3

Supply chain: corn to ethanol

Corn kernels are first delivered to a processing plant, where they are stored before entering the production cycle. The kernels are then ground into a fine powder called meal. This meal is mixed with water and enzymes that converts starch to sugar. This liquid mixture is now called ‘mash’ and is heated to reduce levels of bacteria. The mash is then cooled, and yeast is added to ferment the sugars into alcohol and carbon dioxide. The alcohol is then separated by means of distillation. A molecular sieve removes any remaining water, and the resulting ethanol can then be stored or shipped.

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One of the main stumbling blocks to the global usage of ethanol as a source of fuel for transport is the cost of developing a retail distribution network. Additionally, questions have been raised about how feasible it would be to produce ethanol in sufficient quantities to replace the current reliance on gasoline as the amount of land required to produce sufficient quantities would be enormous. This could influence the amount of land dedicated to grow corn for feed, which would impact other parts of the food supply chain. There is also the related issue of moving the ethanol to the end point of consumption. In most countries the main method is to move it by trucks or train. It is not feasible to move it using the existing hydrocarbon pipelines, as water tends to build up in them, which would attach it to the ethanol, watering it down and rendering it useless as a fuel.

12.6

PRICE DRIVERS

There are three main themes commonly discussed within the context of agriculture. They are the three ‘Fs’ of food, feed, and fuel. By way of illustration, consider the following short quiz. What commodity links the following situations? ▪ ▪ ▪ ▪

A sugar cane farmer in Brazil. A corn farmer in the USA. Increase in demand for meat in China. Increase in the price of soybeans in Iowa.

When the author asks this question in a classroom, typical answers include water, land, fertiliser, transport, and climate. Some participants manage to identify the correct answer, which is crude oil. The linkage? Rising crude oil prices would make it more attractive for Brazilian producers to make more ethanol since it is a form of fuel substitute. Ethanol can also be produced from corn and so this might encourage US farmers to divert more of their crop to this end use. However, corn can also be used as a feed for cattle and as incomes in China increase there will likely be an increase in the demand for meat. With a large proportion of corn being diverted into ethanol production, there will be less corn for animal feed and so its price will increase. If US farmers respond by planting more corn, then there is a smaller area of land available for producing soybeans. Since the supply of this product now falls the price would rise.

12.6.1

Physical market factors

Weather and climate change A strong harvest will increase the amount of the product coming to the market. In this respect the key factor is weather. A very hot summer, or indeed a very cold one, may have an adverse effect on the size of the harvest. The impact of climate change will influence long-term trends and is addressed in Chapter 11.

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One significant aspect of weather is the El Niño Southern Oscillation (ENSO), which is a climate pattern that is used for seasonal forecasting several months into the future. This is a natural phenomenon that occurs from the interaction of the ocean and atmosphere. ENSO comprises of two extremes El Niño (‘the boy’) and El Niña (‘the girl’), which are, respectively, the warm and cold-water phases of the climate pattern. They were so named by South American fishermen who, every few years, would observe the conditions, which usually peaked around Christmas time. These two phases are cyclical environmental patterns that occur across the Equatorial Pacific Ocean. In neutral years, the trade winds will blow from east to west and as a result warmer water is pushed towards the eastern shores of Indonesia and Australia. These warmer sea temperatures lead to warmer air rising, which can lead to more cloud and unsettled weather. Off the coast of South America, as the warmer water is pushed away, colder water will start to rise to the surface. This split between warmer weather in the west and colder weather in the east leads to atmospheric circulation, which pushes cooler dryer air towards the east. El Niño is associated with a weakening of the trade winds which reduces the temperature differential as the warmer waters are not pushed as far west as a neutral year. As a result, the eastern waters off South America become relatively warmer. This change in weather patterns will have an impact on temperatures and rainfall. La Niña is the opposite of El Niño and describes a situation where the trade winds would be stronger than a neutral year. This pushes the warmer waters further westwards and as a result the waters off South America become colder and extend further into the Pacific. El Niños typically occur every three to five years, and although there are some common characteristics shared by each event, no two occurrences will be identical. According to the National Oceanic and Atmospheric Administration’s website (https://www.noaa.gov/education/resource-collections/weather-atmosphere/el-nino), the most common effects of El Niño are: ▪ Deficient rainfall over Indonesia and northern South America. ▪ Excess rainfall in the southeastern South America, eastern equatorial Africa, and the southern US. La Niña is the opposite pattern. For example, in the USA there will be drier weather in the South, but the North West will be colder and wetter than average. Whereas El Niño is associated with a reduction in hurricanes that form in the Atlantic, La Niña events tend to be related to an increase. The somewhat obvious conclusion is that ENSO’s influence on rainfall and temperature can have a significant impact on the production and availability of food. Physical constraints and restraints Supply for a particular product may reach a peak if the country runs out of land that can be used for production, or there is no labour or water available. There may also be environmental and political pressures that could restrain the expansion of a particular product.

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Transportation issues A significant proportion of agricultural products that are exported will be done so by seaborne means. Several ‘choke’ points exist where political events may result in a disruption to supplies. These include: ▪ ▪ ▪ ▪

Panama Canal Strait of Malacca Strait of Hormuz Bosphorus Strait

Cost of production inputs Although supply chains will vary amongst different sectors an increase in the cost of inputs such as diesel, fertilizer, and seeds will ultimately feed through to higher prices. Innovation and investment One of the more popular examples of innovation has been in the coffee market with the introduction of single serve capsule machines. Although in the long term it is expected that this may attract new consumers into the market and increase demand, the initial impact was the opposite. A common refrain was that a lot of coffee was often ‘consumed by the sink’, but the single serve capsules removed this waste, reducing demand. If a particular product is faced with challenges to increase supply, it may require some form of innovation. This could encourage better plant breeding of development of higher yielding seed material. Genetically modified crops are now very common and result in greater crop yields and more effective resilience to disease. However, not all areas of the world will accept such grains and this type of investment often requires a significant capital outlay. Another form of investment is that some large end consumers will often work with small hold growers of certain crops, particularly in emerging markets. They may provide expertise and perhaps funding to secure the quality and quantity of the raw materials that they need. Crop switching Following the sharp rise in energy prices during the early part of the century, the interest in ethanol as a fuel substitute had a subsequent effect on the demand for its primary production inputs, which include sugar, corn and soybeans. In theory as crude oil prices increase, the demand for ethanol from sources such as corn becomes more economical to produce. As a result, farmers will plant more of the crop that is in demand and less of the lower demand crop. This is sometimes dubbed ‘the battle for acreage’.

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A related biofuel is biodiesel, which can be produced from renewable resources such as soybeans or palm oil. Biodiesel has several advantages that make it attractive: ▪ It can be used in existing diesel engines. ▪ It can be blended with normal diesel. ▪ It is environmentally very friendly, emitting a lower amount of carbon than conventional fuels. Elasticity of supply In the energy and metals chapters it was noted that the supply side response to an increase in demand was relatively slow due to the time needed to construct the required infrastructure. However, with respect to the agricultural sector, the response time is determined by the relatively short period it takes to plant and harvest a particular product. Product substitution One practice used in the coffee industry is for roasters who deal in less high-end coffee to add more robusta to blends at times when arabica prices are high. Current levels of inventory The level of stockpiles (‘carry over’) is an indication of the balance between demand and supplies and as such will have an impact on price. Another popular term that is used in the market is ‘stock to use’ ratio. This indicates the amount of inventory carried over into a new reporting year as a percentage of the total use of the commodity.

12.6.2

Societal factors

Health The demand for certain soft commodities such as sugar may also be affected by a growing awareness of health-related issues. For example, a change in the way that food is packaged may result in a change in dietary habits if the amount of sugar is made more visible. Additionally, the development of sugar substitutes such as stevia may also result in a fall in demand. Stevia is a plant and is 300–400 times sweeter than sugar, but has no calories and does not raise blood sugar levels. Population growth In very simple terms a greater population means more mouths to feed and so in theory greater demand. At the time of the publication of the first edition of this book (2007), the world population was about 6.7 billion. At the time of writing some 13 years later, it is now nearly 7.8 billion (Figure 12.15).

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9,00,00,00,000 8,00,00,00,000 7,00,00,00,000 6,00,00,00,000 5,00,00,00,000 4,00,00,00,000 3,00,00,00,000 2,00,00,00,000 1,00,00,00,000

19 5 19 0 5 19 2 5 19 4 5 19 6 5 19 8 6 19 0 6 19 2 6 19 4 6 19 6 6 19 8 7 19 0 7 19 2 7 19 4 7 19 6 7 19 8 8 19 0 8 19 2 8 19 4 8 19 6 88 19 9 19 0 9 19 2 9 19 4 9 19 6 98 20 0 20 0 0 20 2 0 20 4 0 20 6 0 20 8 1 20 0 1 20 2 1 20 4 1 20 6 18

-

FIGURE 12.15 World population 1950–2018. Source: Food and Agricultural Organization of the United Nations (FAO). Holiday periods and religious events Agricultural product prices may exhibit some form of seasonality depending on the time of the year. ▪ Christmas and US Thanksgiving – Prices of turkeys will increase, generally peaking in November. Fish related products such as smoked salmon and lobster will tend to be high in the October to December period. ▪ Religious holidays – At Easter time approximately 80 million chocolate eggs are sold in the United Kingdom (population approximately 67 million). As a result, cocoa butter tends to rise in the first half of the year and then fall back. Ramadan is associated with higher consumption of meats such as lamb.

12.6.3

Governmental intervention

Quality of data It would be virtually impossible to be able to count every single agricultural product cultivated in a particular country on a real-time basis. Consequently, reporting agencies use a variety of different sampling techniques to obtain the data. For example, one key report published by the US Department of Agriculture is the ‘Prospective Plantings’ report, which is based on a sample of about 80,000 farm operators from an estimated population of two million farms. Although the process is often very rigorous it is unlikely to be perfect and revisions to data in some (but not all) reports can occur. The Financial Times (2010f) reported that some trading houses would often employ staff to stand at the gates of every cocoa warehouse in Abidjan, Ivory Coast, to count the movement of their of competitor’s trucks to get a better picture of the country’s output. Anecdotally, the authors recall doing some work at an agricultural hedge fund where the fund managers would often charter helicopters to see how well various crops were growing.

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Protectionism Inevitably when considering the nature of agricultural commodities, the issue of tariffs and subsidies will arise. Subsidies will influence where and how much is produced, while import tariffs may be designed to protect a domestic industry for social or political reasons. For example, acreage switching due to differing grain subsidies is a factor monitored by some traders. More extreme measures may include limits on production, a ban on food exports (to keep food in domestic markets), or a ban on imports (to protect local producers from cheaper imports). Sometimes, export tariffs may encourage consumers to switch new sources of supply in a different geographical region. Subsidies to farming usually take the form of either an income supplement or a minimum price guarantee. This has led to international trade disputes such as those seen between the USA and Europe. The EU has long operated a Common Agricultural Policy to support its farmers and has used several trade barriers to minimise the competition faced by their domestic suppliers.

12.6.4

Financial factors

General price level of food In general terms the price of food has been rising steadily over the last 20 years. Currency impacts As with many other commodities, the agricultural suite of products will be predominantly traded in US dollars. A substantial move in the exchange rate could have an impact on both producers and consumers, depending on the direction of the move and the location of the market participant.

140 120 100 80 60 40 20 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Consumer price indices; 2010 = 100; FAO

FIGURE 12.16 World food prices. Consumer price indices. Source: FAO

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Investor activity With the increasing use of commodity derivatives, large flows of speculative money have moved into the futures market. For example, with the general increase in investor interest in commodity indices such as the S&P GSCI, the ‘rolling’ of the index’s constituent futures (see Chapter 14) will influence the shape of the forward curve. This has led some commentators to suggest that ‘speculation’ has caused the price of food for the end consumer to be adversely impacted. This is a very contentious area, but there are a couple of questions worth asking: ▪ How is speculation defined? ▪ Do speculators exploit trends or define them? ▪ Would the absence of speculators in the market decrease liquidity, therefore impacting the ability of commercial participants to hedge their exposures? ▪ What is the size of the futures markets relative to the underlying physical market? ▪ Since futures are typically semi-processed rather than the final products that are consumed, what part of the physical supply chain is being impacted? ▪ Are the final prices paid by an end consumer impacted by futures activity? For example, although Starbucks price their physical purchases using the coffee C contract, the cost of beans only makes up a small proportion of the final price paid by the consumer. ▪ Although futures may have a short-term effect on prices, will they influence prices over the longer term? While researching this text the author came across examples of volatile markets where there is either no or a very small futures market in operation. Examples include: ▪ Peanuts – US prices tripled in 2011 because of drought. ▪ Rubber – Prices increased by 75% in 2010. The rise was attributed to a fall in production in the previous year, rising demand, higher oil prices, and some investor activity. At the time there was only a relatively small futures market for the product based in Tokyo. Being able to attribute price movements to each of the underlying factors would be nigh on impossible (Financial Times, 2010e). ▪ Barley – Again in 2010 the price of barley doubled in six weeks due to drought conditions in Russia. ▪ Rice – In 2008, the price of rice increased from just over USD 300/tonne to over USD 1,000/tonne over a couple of months. This led to extensive civil unrest as approximately 3 billion people regard the commodity as a food staple (Financial Times, 2008). Commitment of traders report The Commodity Futures Trading Commission (CFTC) produces a ‘Commitment of Traders’ (COT) report on a weekly basis. According to the CFTC, ‘The COT reports provide a breakdown of each Tuesday’s open interest for markets in which 20 or more traders hold positions equal to or above the reporting levels established by the CFTC’. Open interest is the total of futures and/or option contracts entered and not yet offset

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by a transaction, exercise, or delivery. The total of all long open interest must equal the total of all short open interest. Traditionally, the reports classified a trader as either being ‘commercial’ or ‘non-commercial’. Broadly speaking a commercial user will have some form of underlying economic exposure that they are seeking to hedge using futures or options. A non-commercial user would be more likely to use the contracts as a way of profiting from an expected market movement. One aspect of this approach is that it does not reveal the trader’s underlying motivation. So, a commercial user could execute a transaction for speculative purposes rather than traditional hedging motivations. To illustrate this, consider the following abbreviated report (Table 12.1) based on the Soft Red Winter Wheat contract. Total open interest was 359,729 contracts. From 2009, the CFTC supplemented this legacy method by introducing four categories of traders: ▪ Producer/merchant/processor/user – this designation was designed to capture those participants engaged along the physical supply chain and would be more likely to use futures for hedging purposes. ▪ Swap dealers – the CFTC define this category as ‘an entity that deals primarily in swaps for a commodity and uses the futures markets to manage or hedge the risk associated with those swap transactions. The swap dealer’s counterparties may be speculative traders like hedge funds or traditional commercial clients that managing risk arising from their dealings in the physical commodity’. ▪ Managed money – this could include commodity trading advisors (CTAs: individuals or organisations who provide advice and services relating to commodity derivatives) and commodity pool operators (CPOs: individuals or organisations who accepts money for the purpose of trading commodity derivatives). ▪ Other reportables – every other trader subject to the reporting requirements and not captured by the other three categories is placed in this category. Table 12.1 uses the same futures data as Table 12.2 but uses the amended reporting format. TABLE 12.1 Commitment of traders report – Soft Red Wheat futures traded at the Chicago Board of Trade, 24 March 2020. Entity Position

Non-commercial Long Short Spreads

Commercial Long Short

Total Long Short

Non-reportable positions Long Short

Commitments 97,437 62,621 121,381 113,970 133,809 332,788 317,811 26,941 Percentage 27.1 17.4 33.7 31.7 37.2 92.5 88.3 7.5 of open interest Number of 97 75 108 77 108 239 244 traders

41,918 11.7

Note: A spread contract could be where a trader has both a long and short position in the same contract but for different maturities. Source: CFTC

TABLE 12.2 Disaggregated commitment of traders report – Soft Red Wheat futures traded at the Chicago Board of Trade, 24 March 2020.

Position Commitments Percentage of open interest Number of traders Source: CFTC

420

Producer / merchant / processor / user Long Short

Long

28,192 7.8

104,769 29.1

69,832 19.4

13,094 3.6

51

87

20

10

Swap dealers Short Spreading

Managed money Long Short Spreading

Other reportables Long Short Spreading

15,946 4.4

62,852 17.5

42,709 11.9

88,589 24.6

34,585 9.6

19,912 5.5

32,792 9.1

17

59

33

58

38

42

50

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These reports are often used as a measure of market sentiment and are often reported with associated price movements. For example, the reports will show the change in positions from the last reporting period and so significant swings could indicate that the market is particularly bearish or bullish. The popular media will often focus on activities of the more speculative categories of traders when trying to explain price movements. Emerging market wealth effects No commodity price analysis would be complete without some mention of India and China. As both countries continue to urbanise, it is likely that diets will evolve to include more processed foods with higher sugar content and more protein. In addition, there is likely to be an increase in demand for meat. The Economist (2007) points out: ‘calorie for calories, you need more grain if you eat it transformed into meat than if you eat it as bread: it takes three kilograms of cereals to produce a kilo of pork, eight for a kilo of beef.’ So, the increase in wealth in these nations should lead to an increase in the demand for corn as a feed for livestock. A more general point about per capita incomes could be illustrated in the coffee market. An increase in incomes may tempt drinkers away from instant coffee (perhaps made with the cheaper robusta bean) towards more expensive drinks that will be brewed using arabica beans.

12.7

EXCHANGE TRADED AGRICULTURAL AND ETHANOL DERIVATIVES

Contract specifications There are several competing exchange traded agricultural futures contracts, and a sample of three popular commodities traded on the CME is listed in Table 12.3. The exchange publishes a substantial amount of literature covering many aspects of their use, which is available from their website (https://www.cmegroup.com/education .html). Popular trading strategies It would be somewhat repetitive to reproduce all the futures content covered in other chapters, so the intent in this short section is to highlight some popular trading strategies. Over the years several different agricultural futures strategies have evolved to replicate various underlying market relationships: ▪ ‘Hog crush’ trade – simulates the feeding process for hogs and consists of long positions in soymeal and corn against a short position in lean hogs. ▪ BBQ spread – replicating a possible barbecue menu would be coal or natural gas futures against live cattle. ▪ Popcorn spread – corn against sugar.

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TABLE 12.3 Futures contract specification for corn, soft red winter wheat, and soybeans. One bushel of corn weighs approximately 56 pounds/25kg, while for soybeans and wheat a bushel is taken to be 60 pounds/27kg. Corn Contract size Deliverable grades

Tick size Price quote Contract months Last trading day

5,000 bushels No. 2 yellow at par, no. 1 yellow at 1 1/2 cents per bushel over contract price, no. 3 yellow at a discount between 2 and 4 cents/bushel depending on broken corn, foreign material, and damage grade factors. 1/4 cent/bushel (USD 12.50/contract) Cents/bushel Dec, Mar, May, Jul, Sep The business day prior to the 15th calendar day of the contract month

Chicago Soft Red Winter Wheat

Soybeans

5,000 bushels Principally, no. 2 soft red winter at par; no. 1 soft red winter at 3 cents/bushel over contract price.

5,000 bushels No. 2 yellow at par, no. 1 yellow at a 6 cent/bushel premium, no. 3 yellow at a 6 cent/ bushel discount

1/4 cent/bushel (USD 12.50/contract) Cents/bushel Dec, Mar, May, Jul, Sep The business day prior to the 15th calendar day of the contract month

1/4 cent/bushel (USD 12.50/contract) Cents/bushel Jan, Mar, May, July, Aug, Sep, Nov The business day prior to the 15th calendar day of the contract month

Source: CME Group

The CME trades the entire soy complex and from this, a range of strategies has evolved. The ‘crush spread’ is the expected gross margin from the processing of soybeans and is a dollar amount determined by the price of soybeans relative to the combined price of soybean meal and soybean oil. The trading of the spread is predicated largely on expected price movements of the soybeans against the meal and the oil components of the crush. The trade is constructed using futures by the purchase (sale) of the soybean contract and the sale (purchase) of both the soybean oil and soybean meal contracts. Christian (2006) argues that one of the motivations for trading this price spread is since the oil content and the yield will vary between crops and harvests. A typical bushel of soybeans weighs around 60 pounds (just over 27 kg), which when crushed might yield 11 pounds (5 kg) of soybean and around 44 pounds (20 kg) of soybean meal. About 5 pounds (about 2.26 kg) will go to waste. If meal demand is high and oil demand is not, then processors may decide to switch the balance of production between the two products. One popular way of trading this relationship is by means of options on the spread between the prices. The fundamentals of spread options were covered in Chapter 1.

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‘Chocfinger’ – a case study on short squeezes In June 2010, press reports surfaced that the July cocoa futures price had risen above GBP 2,500 for the first time in 33 years. This was initially attributed to a poor harvest in the Ivory Coast earlier in the year, which had led to a fall in supply. The cocoa plants were characterised as being old and prone to disease and with demand having outstripped supply for five years, prices had been rising steadily. As events started to unfold it became clear that the ‘open interest’ in the July contract was significantly higher than normal, raising suspicions that prices were being driven higher by speculative activity, with perhaps one or two dominant players having large, long positions. Initially, the impact on market participants was twofold. As prices increased, cocoa bean consumers started buying greater volumes of July expiry call options. But this had an unintended impact on market prices because of the hedging activities of the banks that had sold the options. The sale of call options by the banks would expose them to potential open-ended losses if prices continued to rise. The classic hedging strategy to mitigate this is for the banks to ‘delta-hedge’ their directional exposure by buying futures. This offsetting position should offer some protection against rising prices. However, this had something of a feedback effect in that the purchase of these futures would push prices even higher. The second impact was the hedging activity of cocoa processors who transform the beans into cocoa butter and liquor, which are intermediate products in the production of chocolate. The processors are buyers of cocoa beans and sellers of the intermediate butter and liquor products. These processors would typically sell cocoa futures to hedge the sale of their intermediate products against a possible fall in price. This strategy assumes that the price of the cocoa future moves broadly in line with the prices of the intermediate products. Typically, the processors will have an ongoing hedging requirement and would not be either willing or able to take the contract to final delivery. Since the contract was physically settled, the processors would be required to either deliver what inventory of beans they held or procure additional physical supplies from the market. Since the end products they were trying to hedge (i.e. butter and liquor) were not eligible for delivery into the futures contract, these participants would typically roll their exposure. The processors would sell (say) the July contract and shortly before its expiry, close out the exposure by taking an offsetting long position. They would then immediately sell a longer-dated maturity such as September to maintain their exposure to the market. This short September position would again be held until close to maturity where the roll strategy would be repeated; buy to close out the September contract, sell December to re-establish their directional hedge. As prices continued to increase, the market turned into backwardation with the July contract trading GBP 156.00 higher than the September maturity. This backwardation was signaling a short-term excess of demand over supply. This prompted some market participants to complain to the exchange (at the time NYSE LIFFE, now the ICE) that the market was being manipulated. One market participant commented: ‘the shorts are the ones complaining . . . if they believe it is all just speculation, they can call the bluff and deliver at expiry physical cocoa and scare the speculators’, (Financial Times, 2010g). As demand continued to increase, the price spread between the first and second ‘prompt’ futures increased to GBP 300.00/tonne as the contract approached expiry.

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The July 2010 contract finally matured on the 15 July with the price hitting GBP 2,750/tonne. It then transpired that a UK hedge fund, Armajaro, had taken physical delivery of 240,100 tonnes of cocoa. As a result, Anthony Ward, the owner of the fund was dubbed ‘Chocfinger’ by the press. Since one future was 10 metric tonnes, the hedge fund had gradually built up a long position of 24,010 futures, with an at expiry market value of about GBP 660 million. Press reports suggested that the long position in the July 2010 contract had been initiated in October 2009 and had been added to on an incremental basis. This was the largest physical delivery seen on the exchange for 14 years and represented about 7% of annual global production. Indeed, this was not the first time that Ward had taken large positions in cocoa futures. In 1996 he used the futures market to take delivery of 300,000 tonnes of beans (about 10% of global production at the time) and in 2002 a similar strategy saw him take delivery of 148,000 tonnes. Although the exact motivation of the hedge fund has never been revealed, their strategy appeared to suggest a belief that prices would continue to increase and that the October 2010 crop would be poor, following the trend of previous years. By early September, reports emerged that the October crop in the Ivory Coast would be better than expected and that the market would return to a surplus of supply for the first time in several years. As a result, futures prices for December delivery started to fall below GBP 2,000. It is unclear from reports in the public domain the extent to which Armajaro’s strategy was profitable. Some commentators suggested that the hedge fund had in place several offtake agreements with chocolate producers so it seems likely that these deliveries would have taken place sometime in the third quarter of the year. Most chocolate producers tend to increase production from about September to meet Christmas demand. By November 2010, the price of cocoa beans had fallen to GBP 1,770 and since some articles suggested that Armajaro had paid on average between GBP 2,100 and GBP 2,200/tonne, the fund may have been facing a loss on any remaining inventory. Additionally, the cost of financing a long position held in a warehouse would be significant at about USD 7–10 million a month (e.g. interest costs, warehousing rent). Armajaro started to sell its remaining physical position in September 2010 and completed it by December of the same year. Interestingly, as the December 2010 contract expired, nearly 110,000 tonnes of cocoa were physically delivered, the largest amount for the year-end contract for 10 years. It was suggested that Armajaro made most of the deliveries. It is perhaps plausible to suggest that after taking physical delivery in mid-July, the hedge fund may have established a short December futures position at what was then a higher price than the final settlement price. Focus then turned to the buyers of this December delivery, which turned out to be principally two large traders. Arguably, they were concerned with rising prices as their purchases coincided with political unrest in the Ivory Coast, which led to a virtual close of the cocoa industry. The incident does highlight several interesting points: Difficulty in defining market manipulation – Although the regulatory definition of market manipulation is couched in somewhat formal legal language some, but not all, of the main principles involved are: ▪ Providing misleading signals that may impact the supply or demand of a product. ▪ Buying and selling at off market prices. ▪ Entering a transaction that employs some form of deception.

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▪ Knowingly disseminating false or misleading information to impact either supply and demand or price. ▪ Inputting false or misleading information into the process of compiling a benchmark index. ▪ Trading at opening and closing prices, which may mislead investors. ▪ Voicing an opinion in the media in which may benefit an existing position without declaring the conflict of interest. One definition that is worth reproducing in full that is relevant to the case is (European Union, 2014): ‘The conduct by a person, or persons acting in collaboration, to secure a dominant position over the supply of or demand for a financial instrument, related spot commodity contracts . . . which has, or is likely to have, the effect of fixing, directly or indirectly, purchase or sale prices or creates, or is likely to create, other unfair trading conditions’. The allegation of market manipulation made by the market participants in relation to the July 2010 contract was investigated by the exchange that argued that the trading activity was not designed to specifically to distort the price of the contract. The exchange pointed out that since the hedge fund had taken delivery of the physical product they had made use of one of the primary functions of the exchange in that it is willing to act as the buyer and seller of last resort for physical supplies. Admittedly, the EU definition of market manipulation supersedes the 2010 incident, but it illustrates not only the difficultly of applying regulations that are based on principles rather than strict rules, but also how regulation will often evolve to address developments in the market. Liquidity – Typically when buying and selling most financial products on an exchange there may be an expectation that a position can be easily reversed. Consider the situation of the processors who were structurally short futures and had become used to the idea of buying back the position to avoid physical delivery. No doubt as the contract’s maturity approached, they started to realise it was nearly impossible to find a willing seller as the dominant participant was intent on taking physical delivery. Presumably, to buy back their position so as to avoid physical delivery, they were willing to bid prices higher and higher, further contributing to the price increase. Proxy hedging – Although information in public domain is somewhat sketchy, there is a possibility that the rise in price and the associated movement of the curve into backwardation could impact the processors in two different ways. If they had not hedged their purchase of beans, the rise in futures prices may well have led to an increase in their physical purchase costs. Secondly, the losses incurred from their short futures position could reduce their overall profitability as the income from the sale of the butter and liquor products would not automatically increase. Like many market participants, they were caught between two different markets and therefore had an exposure to the price spread. There was no exchange traded solution that allowed them to manage their exposure to a fall in the price of their liquor and butter products and so they used the cocoa bean futures contract as a proxy. Arguably, an over-the-counter structure would have provided a better solution although it would

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leave their counterparty with the ‘proxy risk’. This risk would have to be priced into the contract making it less attractive but arguably resulting in a more effective hedge. This is a similar problem to the jet fuel hedging example illustrated in Chapter 6.

12.8

OVER-THE-COUNTER AGRICULTURAL DERIVATIVES

Anecdotally, the maturity of hedges instigated by participants in the food sector will often be shorter than in other industries. As production can vary from year to year due to factors such as weather or disease, companies are very often reluctant to hedge beyond a 12–18-month period (Financial Times, 2010d).

Swaps OTC contracts such as swaps exist for most agricultural products and often banks can offer swaps on products where no liquid future exists. This idea was discussed in Chapter 6 with respect to jet fuel. Like examples in previous chapters, swaps could be used for several reasons that include: ▪ Transforming an underlying price exposure from floating to fixed or vice versa. ▪ Taking a directional view on the price of the commodity without having to take physical delivery. The swap could either cover a single period in the future or involve multiple periodic cash flows. A hypothetical term sheet may look as follows: Commodity: Trade date: Effective date: Termination date: Notional amount: Fixed price payer: Fixed price: Floating price payer: Reference price:

Corn August Three months from trade date (i.e. 1 November) 1 month from effective date (i.e. 30 November) 700,000 bushels Counterparty USD 3.5000/bushel Bank Corn – CME; the arithmetic average of the daily settlement price of the first nearby month futures contract over the period of the swap

OTC swap contracts for wheat will be very similar in structure and typically settle against the CME futures price. Similar to the base metals market, commercial contracts may well be linked to a futures price as this allows the hedger to ensure that the price on which the physical contact is based is the same as that used for the applicable hedging instrument.

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Fixed price spread Client

Bank Monthly average of spread

Soybean oil price

Diesel

FIGURE 12.17 Vanilla swap referencing the spread between soybean oil and diesel.

Vanilla swaps – exotic requirements Biodiesel is a fuel made from a variety of different sources, which include vegetable oils such as palm oil. It is more environmentally friendly as in its pure form it is non-toxic and biodegradable. Like ethanol, biodiesel can be blended in certain proportions with conventional diesel fuel without any need to modify the engine. Consequently, biofuel producers are faced with a spread exposure as part of the business. They consume agricultural products and have their outputs linked to an oil product. Although this spread exposure may appear to be ‘exotic’ it would be possible to structure a vanilla swap that transforms a variable spread exposure to a fixed value. Figure 12.17 illustrates the concept at a high level. In this example the client is a biofuel producer who has an expense related to soybean oil but receives income from the sale of their biodiesel fuel. In the swap transaction they pay away this ‘floating’ spread. This spread could be calculated as the average of daily prices observed over a given period such as a month. In return they would receive a fixed cash flow. So this would be beneficial if the price of soybean oil increases for a prolonged period relative to the cost of diesel. There is something of a basis risk here as the producer is selling biodiesel but exchanging cash flows whose values may well reference a liquid futures price such as ultra-low sulfur diesel.

Options Vanilla options on agricultural products are well established and readers interested in different structures are referred to the examples documented elsewhere in the book (e.g. Chapter 4 for gold and Chapter 5 for base metals).

Options on spreads Biodiesel producers will often monitor certain spreads that measure the margins between biodiesel and diesel fuel. These spreads include: ▪ POGO (Palm oil minus gas oil). ▪ BOHO (Soybean oil minus heating oil). ▪ BOGO (Soybean oil minus gas oil).

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Suppose that a biodiesel producer sees that palm oil prices are declining, making the commodity attractive for blending into diesel. They see that the current POGO spread is trading at −USD 50.00/MT (i.e palm oil prices are lower than gas oil), which is below the long-term average they have calculated as being + USD 100/MT. However, they realise that this may not persist as other producers would also likely take advantage of the situation with the possibility that stocks of palm oil could fall causing the POGO spread to increase in the medium term. As a result, they agree to sell a put option on the POGO spread so they could monetize any physical optionality that allows them to switch to palm oil in their manufacturing process. The payoff to the holder of a put option on a spread of prices is: Put payoff = MAX (Strike − price of asset 1 + price of asset 2, 0) We will assume that the prices of the two products are: Palm Oil futures: Gas oil futures:

USD 250.00/MT (asset 1) USD 250.00/MT (asset 2)

Returning an initial spread of zero, the option has a maturity of six months and the implied volatilities for both assets are set at an arbitrary value of 30%. The option premiums (rounded) for a variety of strikes and correlations are shown in Table 12.4. From these results we can see that the spread option in put format is correlation negative. As correlation decreases, the cost of the option increases. The payoff from the option is not intuitive, but will be most profitable to the holder if the spread were to decrease. To illustrate this, consider the following at maturity payoffs for a variety of different spreads and strikes (Table 12.5). Returning to our example, let us suppose that the biodiesel producer sells this put option on the spread of prices at a zero strike and an associated correlation value of 0. They would collect the USD 30.00/MT premium up front on whatever tonnage was agreed with the option buyer. Assume that at maturity price of palm oil has decreased with the spread moving to −USD 50.00/MT. The buyer exercises the option, and the producer settles the outstanding amount in cash. However, since palm oil is now relatively more attractive to produce than biodiesel, they can offset this negative cash flow by switching to the cheaper input. If the price of palm oil increases, the spread increases, the option would not be exercised, and the producer would retain the premium. TABLE 12.4 Option premiums on POGO spreads expressed in USD/MT. Correlation

Strike = USD 0.00/MT

−1 0 +1

42.00 30.00 Negligible

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TABLE 12.5 At maturity, payoffs for a put option on a spread of prices. Expiry prices (USD/MT) Palm oil = 200 Gas oil = 250 Palm oil = 250 Gas oil = 250 Palm oil = 300 Gas oil = 250

Spread (USD/MT) −50

Payout if strike= 0 (USD/MT) MAX (0−200 + 250, 0) = +50

0

MAX (0−250 + 250, 0) = 0

+50

MAX (0−300 + 250, 0) = 0

Target Redemption Structures (TARNs) Although these structures have been marketed in many different formats, e.g. as an investment product or a hedge, they will tend to have similar features. Within a hedging context, the structure allows the participant to either buy or sell a particular commodity at a relatively attractive price. However, as one would reasonably expect it is not possible to get something for nothing. The benefits that the participant can earn are typically capped at a pre-agreed target value and there is often a downside, which can be significant. Consider the following structure linked to CME corn futures. The notional amount is set equal to the futures contract size for ease of illustration. Client: Notional: Leverage factor: Fixing: Reference price: Settlement: Upfront cost: Strike price: Current prompt futures price: Knock out level:

Accumulation period:

Producer 5,000 bushels per settlement period if reference price is less than strike price. Two; notional will increase to 10,000 bushels per settlement period if reference price is greater than strike. Weekly, based on closing value of reference price. CME corn futures contract maturing in six months’ time. Weekly, by physical delivery Nil USD 3.45/bushel USD 3.15/bushel If at any time during term of transaction the reference price trades below USD 2.85/bushel, the contract is automatically terminated. Six months

The structure will pay out according to the following conditions: ▪ If the price of the six-month futures contract trades at or below the knockout level at any time during the six-month accumulation period, the trade is automatically terminated.

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▪ If the price of the six-month futures contract closes below the strike price of USD 3.45 and above the knockout level of USD 2.85, then the producer will sell 5,000 bushels at the strike price for that weekly settlement period. ▪ If the price of the six-month futures contract closes above the strike price of USD 3.45 then the producer will sell 10,000 bushels at the strike price for that weekly settlement period. Notice that there is a downside to the structure if prices rise above the strike price. If the producer has the inventory available to sell, they will incur an opportunity loss, as they will be selling a greater volume at a fixed price, which will now be below the prevailing market price. If they do not own the inventory, then they will need to buy the requisite amount of the commodity from another participant at the prevailing market price, which will now be higher than the price that they will sell under the terms of the TARN. Although these structures would be typically valued using a Monte Carlo approach, the intuition of the product can be conveyed using vanilla options. A typical TARN could be thought of as a strip of call and put options each with a one-week maturity. In our corn example, a long put position provides the producer with their downside gain, but since they lose out when prices increase, this suggests that they have sold a call option. The strikes of the two options are identical, but are set at a more attractive selling rate than the reference future, which in this case is the future maturing in six months’ time. This attractive sale rate is achieved because of two factors. The first is the capping of the benefit. Note that the structure would become extremely attractive if the price of corn were to fall substantially but the TARN limits the benefit to a lower threshold of USD 2.85, where the structure would terminate. In this sense it might be useful to view the options as ‘down and out’ barriers. The leverage aspect reflects the fact that if the price increases, the producer would incur a loss. A rise in the price above the strike requires them to deliver twice the number of bushels, which means that the sold call option has a notional twice the size of purchased put option. TARN structures can take several different variations with the offering institution tweaking the deal terms in different ways. One such variation would be a TARN collar. Again, the following example is based on a notional equal to one exchange traded future although this could be scaled accordingly. Client: Notional: Fixing: Settlement: Reference price: Upfront cost: Client buys call strike: Client sells put strike:

Consumer 5,000 bushels per settlement period Monthly, based on average of closing value from the front month reference price. Monthly, in cash CME corn futures Nil USD 2.65/bushel USD 2.00/bushel on twice the notional amount

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Current prompt futures price: Target payout: Knock out condition: Accumulation period:

USD 3.15/bushel USD 1.00 × one month’s volume (i.e USD 5,000) If target payout is reached the entire structure will terminate. Six months

To illustrate how the structure works, consider Table 12.6. The key features of the product are: ▪ Recall that corn futures are quoted in cents per bushel so a price of USD 3.20 would be expressed as 320 cents. ▪ The client will receive a cash payout from the call option if prices settle beyond the strike. This payout follows the vanilla call option settlement, i.e. MAX (Underlying price – Strike, 0). This is shown in column 3. ▪ The figures in column 3 and 4 are shown on a per bushel basis in USD/bushel but the actual cash flow would be 55 cents × 5,000 bushels = 275,000 cents or USD 2,750. ▪ The call component is initially deeply in the money, and if the price remains stable it is likely the customer would receive the full target amount without incurring any liability. ▪ Taking month one as example, the consumer is buying their corn at a below market price. That is, the client pays the call strike of USD 2.65/bushel rather than the current prompt futures price of USD 3.15/bushel. Even though the TARN is cash-settled the consumer can use any cash receipt to reduce their cost of buying the physical product. ▪ If the price settles between the strike of the call and the put, then the client receives or pays nothing. Month four is such an instance. ▪ If the price settles below the strike of the sold put the client will pay out the difference between the strike and the reference price on twice the notional. In month five the reference price is 10 cents below the strike and so the client receives nothing but must payout on twice the notional amount (i.e 10 cents on 10,000 bushels). TABLE 12.6 Payout from TARN collar.

Month

Average reference price (USD/bushel)

Client receives (Per bushel)

Cumulative client receipt (Per bushel)

Client pays (Per bushel)

1 2 3 4 5 6

3.20 2.90 2.80 2.30 1.90 2.75

0.55 0.25 0.15 0.00 0.00 0.05

0.55 0.80 0.95 0.95 0.95 1.00

0.00 0.00 0.00 0.00 0.20 0.00

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▪ If the price falls below the put strike, if they were to now purchase their corn at the prevailing market price of, say, USD 1.90/bushel, then after adding on the TARN payout their cost would be USD 2.10/bushel. A prevailing market price of USD 1.50/bushel would result in a TARN payout of USD 1.00/bushel, resulting in a physical purchase cost of USD 2.50/bushel. If prices were to fall steeply to say USD 1.00/bushel, the TARN payout would be USD 2.00/bushel and so the cost of buying the physical would be USD 3.00/bushel. ▪ In month six, the price of corn increases above the strike of the call by 10 cents. However, the client will only receive 5 cents, as the cumulative payout of USD 1.00 cannot be exceeded. This is sometimes referred to as ‘partial redemption’. Equally some transactions could be structured to have full redemption where the client would receive the full payout on the final day. A ‘no redemption’ structure would be one where if the final payout to the customer will result in the target being exceeded then there is no payment. If this condition were applied to our example, there would be no payment in month six and the client’s cumulative receipt would be USD 0.95.

CHAPTER

13

Commodity-Linked Financing

13.1

THE FINANCING NEED

The lifecycle of several commodity markets has been analysed in their respective chapters. For example, Figure 5.1 illustrated the supply chain for copper, which consisted of: ▪ ▪ ▪ ▪ ▪

Mining Smelting Refining Semi-fabrication Manufacture of final product

In this chapter we will consider some of the ways in which this production is financed. The first section provides a very high look at project finance, which is then followed by a discussion of the ‘asset conversion cycle’. The last part of the chapter looks at a variety of different financing examples, which may incorporate derivatives to achieve lower borrowing costs. It is common for institutions to use the term ‘structured commodity finance’ and although there is no single accepted definition it would typically represent transactions that involve more than a simple unsecured bilateral loan. For example, it may involve the bank taking security of the underlying commodity or perhaps a transaction whereby there is some form of embedded optionality. Traditionally, commercial banks were the providers of credit to commodity market participants. For example, large commodity traders such as Glencore would borrow substantial amounts of money to buy, sell, store, and ship their production. However, such traders can also act as creditors to other companies and countries. Since they are not formally categorised as banks, this type of credit extension has been described as ‘shadow banking’.

13.1.1

Loan structures

Although there are many different types of loan structure, there are perhaps two that are worthy of a brief mention. A ‘revolving facility’ will allow the borrower to access funds up to a certain limit. The agreed principal balance can be repaid and re-advanced as the

433

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

borrowing need evolves over time, but the borrower will be required to pay interest on an ongoing basis. A ‘term loan’ is where the lender forwards the entire principal amount at the start of the transaction and the borrower will repay interest and principal over an agreed period. The overall balance due to the lender will therefore gradually reduce to reach zero at maturity.

13.1.2

Definitions

This text is not designed to provide readers with a comprehensive coverage of trade finance, but there are some useful terms that deserve a brief definition and explanation. Readers who need a more comprehensive description of the topics are referred to Jones (2018). Ownership and possession Although each legal jurisdiction will differ, there are some general principles that are worth highlighting. In many financing agreements one important issue to understand is whether the lender of cash has ownership or possession of the underlying commodity if it is taken as security. An outright ‘true sale’ of the commodity would mean that the lender of cash would take legal title to the product and can do with it whatever it wishes. Possession describes a situation where a lender has control over the movement of the commodity but does not have the title rights and therefore cannot sell or transfer the item. It is also common to hear about goods being pledged to a lender in order to borrow money. In this situation the borrower will provide the lender with the ability to sell the commodity in the event of the borrower’s default. Providing the lender with the documents of title, or perhaps the goods themselves could do this. However, a pledge does not automatically confer ownership to the lender and so the borrower will retain the legal title. So, for the pledge to be effective, the lender must be able to exercise meaningful control over the underlying commodity to prevent access by the borrower. Bill of Lading Jones (2018) describes a Bill of Lading as a transport document that is used when a product is to be shipped by sea. He argues that it can perform three key functions: ▪ A receipt for the cargo ▪ A contract of carriage ▪ A document of title Trust receipt If a lender has received a pledge of the underlying commodity to secure some form of financing, it may become necessary at some point to release the goods to the borrower in order that they can be sold. To ensure that the bank does not lose complete control of

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435

the commodity it is possible for the borrower to issue a Trust Receipt (TR). The lender will either release the physical commodity or the associated documents of title (e.g. Bills of Lading, warehouse receipts) in exchange for the TR. The receipt requires that the borrower holds the goods and any associated sale proceeds ‘in trust’ for the lender. Letter of credit A letter of credit (LC) is a very popular trade finance instrument. One possible example of how the instrument could be used would be in a situation where a buyer and a seller of a particular commodity are based in different parts of the world and they have agreed to transport the commodity by ship. The buyer would be reluctant to pay until they have received and checked the goods, while the seller would be concerned that having shipped the goods they may never be paid. The buyer could approach its bank and ask them to issue a letter of credit (LC) in favour of the seller. Jones (2018) describes an LC as ‘a conditional undertaking usually given by a bank to make payment to the seller, known as the beneficiary, an amount up to a specified maximum value against presentation of documents, which appear ‘on their face’ to comply with the terms and conditions of the credit and applicable rules’. Metal warrants These were covered in Section 5.5.6 A warehouse receipt One way in which a market participant such as a producer or trader can borrow money on a secured basis is via a warehouse receipt. The participant seeking to borrow the funds would store their commodity within a designated warehouse, and the warehouse owner will issue a receipt, which acts as a document of title. This receipt could be delivered to the lending bank so they will have some degree of security until the goods have been sold and the monies received. The receipt would state: ▪ ▪ ▪ ▪

Location of warehouse. The name of the participant depositing the commodity. Date of deposit. Type, quantity, and quality of the commodity.

The warehouse owner is responsible for the safekeeping of the commodity during its time in the facility. Perhaps most importantly, the receipt should also state the process by which the goods will be released. Some possibilities include: ▪ Release of the commodity to the entity that originally deposited the goods. ▪ Release to a named party. ▪ Release based on the depositor’s written instructions.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Jones (2018) warns that, ‘There is no internationally agreed standard, practice or legal interpretation of a warehouse receipt and it should not therefore be automatically assumed that it is a negotiable document of title to the goods’. A person who owns a document of title such as a warehouse receipt can legally transfer the ownership of the underlying commodity by endorsing it (signing over) to another entity. So, title can transfer without the movement of the underlying product. A document of title becomes a negotiable instrument because it transfers legal ownership by endorsement and delivery to the intended recipient. However, the area of negotiability is complex and outside the scope of this text. As Jones (2018) cautions: ‘It is essential therefore that specialist legal advice is sought when a warehouse receipt is offered for the financing of goods held in a warehouse’.

13.1.3

Financing case studies

Scenario #1 Suppose a coffee trader is looking to borrow funds to support their business. They buy coffee beans from various exporting countries in Latin America and Africa before selling them to roasters in the USA and Europe. The bank agrees to a revolving facility of USD 10 million, which is secured by collateral comprising mainly of company assets. The parties agree that the following company assets will be used to support the collateral requirement: ▪ ▪ ▪ ▪ ▪

Original bills of lading. Warehouse receipts (negotiable or non-negotiable). Electronic warehouse receipts. Trust receipts. Accounts receivable, which will be assigned to the lender.

This collateral pool is revalued daily (marked to market) using observable futures prices as a benchmark and making necessary basis adjustments (e.g. different grades or quality, different locations). If this value falls below an agreed threshold, the coffee trader would be required to repay part of the loan to cover the shortfall. Scenario #2 In this example, the client is a Latin American coffee exporter who has clients around the world. They are looking to borrow money to cover the period from when the beans arrive in their domestic warehouse through to the final sale of the product in regions such as the US, Europe, and S.E. Asia. The facility will also cover the period where the coffee is in transit. The lender agrees to a loan with the following structure. The coffee is delivered into a warehouse that is acceptable to both parties. Title is evidenced by means of a warehouse receipt, which is held by the lender. The warehouse receipt states that

Commodity-Linked Financing

437

the beans can only be released with the express permission of the lender. The lender then agrees to forward 80% of the Free on Board (FOB) value of the beans based on the front month exchange traded futures price. The 20% ‘haircut’ was designed to mitigate three risks: ▪ The futures price is a delivered price to a variety of warehouses around the world, and the closest ports to the client would be Miami, New Orleans, or Houston. Part of the haircut reduces the value of the future to reflect the cost of transporting the beans from the borrower’s domestic warehouse to one of these locations. ▪ It also protects the lender against a sudden drop in value of the commodity relative to the amount lent. ▪ It would also act as a cushion in case the client defaulted, and beans were to be sold in a forced liquidation. While being held in the warehouse, the value of the beans will be marked to market on a daily basis against the relevant futures price and if the value of the inventory falls below the initial 80% ratio, the client is required to make a cash payment to the lender to restore the value. The next stage is the release of beans from the warehouse to be delivered to the domestic port ready for export. The lender agrees to the extension of the loan facility to cover the loading, shipping, and then delivery of the beans to the end-client. The lender is able to maintain a degree of control over the process by ensuring that they are assigned the underlying commercial sales contracts. The amount lent at this point of the supply chain is the lower of the sales value or the relevant futures price. The end-client will then make payment directly into the lender’s account.

13.2

PROJECT FINANCE

This text is not designed to be a definitive explanation of project finance but rather to convey a sense of how derivatives could be used within this context. One common application of commodity derivatives within project finance is to give the lender some reassurance that the borrower will be able to repay the loan. From a debt holder perspective, the issue of profitability is somewhat secondary in nature as their main concern is repayment of principal and interest, which is secured by the borrower’s ability to generate cash flow. Consider the following simplified example relating to the mining of nickel. A mining company seeking to borrow USD 70 million has approached a bank. The borrower has agreed to raise an additional USD 30 million in the form of equity so will have USD 100 million of funds in order to commence operations. A simplified cash flow projection is shown in Table 13.1. The mine is expected to take two years to construct and will be able to produce for about a five-year period.

TABLE 13.1 Hypothetical cash flow projections from a mining operation. Pre-production

PRODUCTION Nickel (MT)

Year-2

Year-1

0

0

PRICE Expected sale price ($ / MT)

N.A.

HEDGING Percentage hedged Amount hedged (MT) Forward price ($/MT)

Year 2

Year 3

Year 4

Year 5

5,000

10,000

10,000

10,000

10,000

N.A.

$12,000

$12,000

$12,000

$12,000

$12,000

N.A. N.A. N.A.

N.A. N.A. N.A.

40% 2,000 $12,500

40% 4,000 $12,600

40% 4,000 $12,700

40% 4,000 $12,800

40% 4,000 $12,900

0 0 0

0 0 0

Capital expenditures

(50,000,000)

(40,000,000)

Cash flow available to repay debt

(50,000,000)

Senior debt principal repayments Senior debt interest payments

CASH FLOW BREAKDOWN Revenues - unhedged production ($) Revenues - hedged production ($) Operating costs ($)

36,000,000 25,000,000 (30,000,000)

72,000,000 50,400,000 (70,000,000)

72,000,000 50,800,000 (72,000,000)

72,000,000 51,200,000 (75,000,000)

72,000,000 51,600,000 (75,000,000)

31,000,000

52,400,000

50,800,000

48,200,000

48,600,000

(5,000,000)

(3,000,000)

(3,000,000)

(3,000,000)

(3,000,000)

(40,000,000)

26,000,000

49,400,000

47,800,000

45,200,000

45,600,000

– (2,284,000)

– (4,734,000)

– (6,300,000)

(17,500,000) (5,513,000)

(17,500,000) (3,938,000)

(17,500,000) (2,363,000)

(17,500,000) 788,000

(52,284,000)

(44,734,000)

19,700,000

26,387,000

26,362,000

25,337,000

28,888,000

N.A.

N.A.

N.A.

2.15

2.23

2.28

2.73

Cash flow from operating activities

Cash flow after debt service DEBT SERVICE COVERAGE RATIO (DSCR)

438

Production Year 1

Commodity-Linked Financing

439

The different headings are defined as follows: Production – this is the amount of nickel in metric tons that is expected to be mined over the five years that the mine will operate. This is an estimate and the final value could be greater or less than this amount. Price – to estimate the revenues that will be generated by the company, this line shows an estimate of the sale price for the nickel. It may well be that a sales agreement has been made with a counterparty, but the vital component is the basis on which the metal is to be sold. Let us suppose that the parties agree to sell the metal at the LME cash price that prevails at the time of delivery. As a result, the likely revenue stream will require the lender to make some assumption as to how this price is expected to evolve. Hedging – the next step would be for the borrower and lender to agree what proportion of the output should be hedged. There is no right or wrong answer to this question. There is a simple method that can be adopted, which uses futures prices as a benchmark for likely future revenues. The expected sale price has been set at USD 12,000/MT for all future sales. If both parties agreed that this is a realistic assumption, then given the current series of forward prices, which range from USD 12,500 to USD 12,900/MT, arguably it would make sense to hedge 100% of production. Today’s forward sale prices are all above the future expected spot price and so if prices were to evolve in this manner, than selling all of the production forward would be the logical strategy. This would also be true if the market price for nickel were expected to fall over the period. If, however, both parties were convinced that prices would evolve faster than the current forward rate, there would be little point in selling the production forward as this would reduce the expected revenue. Cash flow breakdown – this section captures the cash generated from the operations of the firm. The figure shows the revenues collected from sales, which may or may not be hedged and then subtracts an assumed value that represents the miner’s operating costs. The result is termed ‘cash flow from operating activities’. Cash flow available to repay debt holders – this uses some assumed values to represent the capital expenditure required to build and maintain the infrastructure over the course of the project’s expected life. Since loan holders will be repaid before shareholders, the next step is to calculate the interest and principal repayment amounts. It is assumed that the principal on the loan will be repaid in four equal stages from year two to year five, but interest is due from the date the loan is made. The interest payable is based on the principal amount outstanding and would be based on an agreed floating interest rate index such as the Secured Overnight Financing Rate (SOFR) plus an adjustment to reflect the fact the index is virtually risk free but the borrower is not. Again, the evolution of the interest rate in this example is somewhat arbitrary as it is not the focus of the analysis. Cash flow after debt service – this is the amount that in theory would be available to pay the shareholders but is not the focus of this section.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

From the lenders’ perspective the key metric in this instance is the ‘Debt Service Coverage Ratio’ or DSCR. This measures how much cash flow the project generates relative to the monies required to repay the debt. DSCR is calculated as: Cash flow available to repay debt∕(principal + interest repayments) There is no ideal value for this value but the greater the number, the more comfort the lender should derive from extending credit to the company. This is the main reason for the use of forward sales within this structure – they will give the lender some assurance as to the cash flow certainty associated with the project. Some readers may be thinking about the applicability of an option-based structure instead of the futures approach presented here. There is no restriction on the use of options, and it would be perfectly possible to apply the structures suggested in Chapter 5.

13.3

WORKING CAPITAL AND THE ASSET CONVERSION CYCLE

When discussing short-term financing arrangements, reference is often made to the concept of working capital. It is often defined as current assets minus current liabilities, but this does not really convey the importance of the concept. Since it is something of an ambiguous term a more useful frame of reference is the concept of the asset conversion cycle (Figure 13.1). The first step is the purchase of the raw material, which will create an ‘account payable’ (i.e. a sum of money due to a supplier). This purchase may be done on some form of credit terms perhaps with the buyer not having to pay the supplier’s invoice for 30 days. The second step sees the raw materials being used in the production process as ‘work in progress’. This will create further costs as employees will need to be paid and energy will most likely be consumed to make the item. The third step sees the completion of the product, but may result in additional costs in the form of storage or transportation. Step four is the sale of the end product which creates an ‘account receivable’ (i.e. monies due to the producer). If the invoice allows for the payment within a time frame such as 30 days, it is likely that there could be a delay before funds are received. For example, a producer of copper in the Americas may agree to sell their metal to an overseas consumer but the buyer will only pay as and when it is delivered. Depending on the exact circumstance this could be several weeks where the asset is deemed ‘orphaned’. Since neither consumer nor producer really want to own it during this period, a bank may step in to provide finance to the producer. When the monies are eventually received (step five) then in theory they can be applied to restart the cycle. So throughout this process funds will be flowing in and out of the company and any shortfall would have to be covered by the company’s own funds or by some form of borrowing. The issue to bear in mind is that companies go bust primarily because they run out of cash, hence the need to borrow in the case of a shortfall.

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Commodity-Linked Financing

Part #1 Raw materials are purchased

Part #5 Funds are received from sales

Part #2 Materials are ‘work in progress’

Part #3 Production is completed Part #4 Products are sold on credit

FIGURE 13.1 Asset conversion cycle.

13.3.1

Monetising inventories using repurchase agreements

One very popular strategy used in commodity finance is a repurchase agreement, sometimes referred to as a ‘repo’. This type of instrument is used in many other asset classes including fixed income1 and equities, although each market will have its own subtle variations. It is based on the notion that a market participant (producer, processor/refiner, consumer) may have an inventory of a particular commodity in a particular form that they have paid for, but which has not yet been sold. To illustrate the concept, consider the following example based on a refinery that holds inventories of crude oil and refined products. The refiner will use this inventory as security for a long-term borrowing facility. The lender and the refinery would agree a long-term loan facility of, say, three years. The amount to be lent would be reset on a periodic basis such as every two weeks, which is termed the reset date. The lender would agree to buy a given volume of a specific grade of crude oil from the refinery for immediate delivery and simultaneously agree to resell back to the refinery the same volume of the same crude oil at the end of the two-week period. During the two-week period, the lender of cash will have full title to the inventory and so it is important that the product is segregated from the refinery’s other inventories. The basic structure of the transaction is shown in Figure 13.2. As part of the first leg of the transaction the lender will forward a sum of money to the refinery, which will be based on the spot value of the trade. If there is no observable price for this maturity, then it is common for the lender to remit the net present value of an observable forward price that coincides with the reset frequency. The interest rate payable on the implicit loan will be based on the lender’s own cost of funds plus an agreed fixed spread (‘facility margin’) to reflect the credit risk of lending to the refinery. 1

Strictly speaking the structure in this section, more closely resembles a fixed income ‘sell buyback’.

442

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS Start date Spot sale of crude oil

Initial proceeds

Refinery

Lender

End proceeds

Forward repurchase of crude oil

End date

FIGURE 13.2 Commodity repurchase agreement. Assume that the following terms were agreed: Facility arranger: Borrower: Underlying asset: Facility volume: Term of facility: Reset frequency: Facility margin: Floating rate index: Initial value of floating index: Prepayment: Initial payment:

Forward market price:

Commercial Bank Refinery Crude oil of a specified grade for delivery at an agreed location. 50,000 barrels Three years Two weeks 1.25% per annum An agreed interest rate index such as USD LIBOR, Federal Funds or SOFR (Secured Overnight Financing Rate). 1.5% per annum 10% Net present value of the forward market price applicable to the next reset date less the prepayment amount. The net present value is computed using the floating rate index plus the facility margin. The forward price for the metal computed by the facility arranger at each reset period.

443

Commodity-Linked Financing

We will say that there is no directly observable price that coincides with the start date of the transaction. However, it is assumed that for this grade of crude oil the value for delivery in two weeks’ time to coincide with the reset date is USD 50.00/bbl. The first step is to calculate the spot price as the discounted value of this forward amount. This value is USD 49.95. Forward price

Spot price = 1+

floating rate index + facility margin ×

Days Year basis

USD 50.00

USD 49.95 = 1+

0.015 + 0.0125 ×

14 360

The second step is to calculate the prepayment amount, sometimes referred to as the ‘haircut’. A common convention in many repo markets is that the lender of cash is allowed to forward a sum of money that is lower than the market value of the collateral. This is to protect the lender against a sudden unanticipated drop in market prices, which would reduce the value of their collateral. The prepayment amount may be expressed as a percentage of the market value of the underlying commodity and indicatively can vary from 5–15%. If the prepayment amount is specified as a percentage then theoretically this could be applied in one of two ways. Either: Initial payment amount∕(1 + prepayment percentage), which in our example, returns a value of USD 45.41 Or Initial payment amount x (100% − prepayment percentage), which in our example returns a value of USD 44.96 Since these types of repos are transacted OTC using bespoke documentation, both parties would need to agree to which procedure to apply. To avoid any misunderstanding, it is also possible for the transaction to state the prepayment amount in absolute terms (i.e. USD/bbl.). For the purposes of this example, we will use the first method which returns a value of USD 45.41/bbl. Since the transaction is based on 50,000 barrels, this means that the amount of money lent to the client is USD 2,270,500. From this we can calculate the absolute value of the prepayment amount as being USD 227,000 (50,000 × 49.95 − 45.41). The factors that influence the size of the prepayment are subject to negotiation between the two parties. The prepayment could be influenced by: ▪ ▪ ▪ ▪

The volatility of the underlying commodity. The liquidity of the underlying commodity. The quality of the underlying (e.g. LME metal vs. non-LME metal). Method of ownership transfer (e.g. warehouse receipt, bill of lading, metal warrant).

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

▪ The term of the transaction. ▪ Whether the currency of the loan differed from the currency in which the commodity is denominated (e.g. a EUR loan, where the collateral is crude oil denominated in USD). ▪ The credit quality of the counterparty. The amount that the client will repay at the end of the reset period will be the initial forward price of USD 50.00/bbl., which equates to USD 2,500,000 on the agreed volume. However, since the initial proceeds were reduced by a prepayment amount, the refiner can reduce the amount repaid by the same sum. So, at the end of the period, they will repay USD 2,273,000 (USD 2,500,000 − USD 227,000). From the refinery’s perspective they have borrowed a sum of money for two weeks on which they will have paid interest at 2.75% per annum. Depending on the wording of the agreement it may be possible for the lender of cash to deliver an ‘equivalent’ commodity back to the refinery. This means they may not get back the exact molecules they originally sold but would receive back something that was mutually considered to be equivalent. Typically, the refiner will be liable for any storage, shipping, and insurance costs as well as any duties or tax that may be incurred. In the event of one of the parties to the deal defaulting during the term of the transaction, the second leg of the deal would not take place. The non-defaulting counterparty would simply retain whatever asset they owned and would be free to dispose of it in any way they see fit. If the lender were to default, the refinery would retain the funds and could use them to buy back the oil in the open market. If the refinery were to default, then the lender would retain the oil and would be free to sell it in the market in order to recoup the amount that had been lent. From this, it follows that over time, the value of the commodity and the value of the funds lent may diverge. This is one of the reasons why the transaction is reset every two weeks. If the reset period was longer and the value of the two legs was to diverge significantly, it is typical for the two entities to agree to some form of ‘remargining’. So, if the price of crude oil were to fall significantly, then the lender may ask for some additional collateral or perhaps a partial repayment of cash. For the more adventurous client it is possible to construct what is sometimes referred to as a ‘structured repo’. Although there is no single definition of this phrase it is likely that the transaction will include some form of embedded optionality. The client may well agree to sell optionality back to the structuring institution in order to reduce their cost of borrowing. For example, the refinery may agree to sell a deeply out-of-the-money call option, which would require them to make a payment to the bank if the underlying commodity increased beyond a pre-agreed price. Although the structure contains an element of risk, if the price of the commodity increases, the client receives back an asset that has appreciated in value and so if the option is exercised they could sell part of the inventory to finance the payout. The benefit to the client is from the premium they would earn from selling the option. Instead of making direct cash payment to the client equal to the premium, one classic technique would be to reduce the repayment amount due at the end of the transaction.

445

Commodity-Linked Financing

Another possibility would be to make the structure extendible. Once again, the client would sell optionality to the lender over the entire structure. This would allow the lender to force the client to extend the length of the repo beyond the original maturity. The client would again most likely benefit from a lower forward repayment amount, but the extension would only exercised if it was beneficial to the lender, which in this case would be if interest rates were to decline. Extending the transaction would mean that the bank would be able to lend money at a higher than market rate for a longer period of time.

13.3.2

Tri-party agreements/margin financing

As the name suggests a tri-party agreement involves three entities. They are: ▪ A customer who is trading futures and has concerns about their ability to finance the margin payments. ▪ A lending bank. ▪ A futures broker. Suppose there is a corporate customer who has borrowed money to finance their asset conversion cycle, but as part of the agreement the lending bank insists that they hedge their underlying commodity exposures to ensure they have sufficient cash flow to repay the loan. The basic structure is shown in Figure 13.3. The lending bank will set up a loan facility with the customer to finance their working capital requirements. The customer then sets up an account with a futures broker (sometimes referred to as a ‘futures commission merchant’) in order to hedge their commodity exposure. The tri-party agreement (TPA) acts as a bridge between both of these agreements and is designed to protect the interests of all parties. This leg of the transaction sees the bank lending the customer the funds required to finance the margin calls to the broker. These additional funds are likely to be part of the original loan facility.

Customer

Futures hedging agreement

Futures broker

Lending facility

Margin payments

FIGURE 13.3 A tri-party agreement.

Lending bank

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

The terms of the TPA will need to address the following issues: ▪ Will the customer be required to grant some form of security to the lender? ▪ How will the margin calls be made? Will the bank lend the funds to the customer who will then be responsible for their payment to the broker, or will the margin payments be made directly to the broker from the lending bank? ▪ If the bank is not directly paying the margin calls to the broker, will they offer some form of guarantee that the payments would be made (e.g. a standby letter of credit in favour of the broker)? ▪ Will the futures account be segregated from any other futures activity undertaken by the customer? ▪ Who will determine the futures hedging strategy? ▪ What rights do the broker and lender have in relation to the termination of the futures account? The control over the hedging decisions would also need to include: ▪ ▪ ▪ ▪ ▪ ▪

Which contracts should be traded to hedge the underlying exposure? What strategy should be employed to hedge a commodity where no future exists? Which maturity of contract should be used? What percentage of the underlying exposure should be hedged? Whether the lender needs to pre-approve any trades? What controls exist over the withdrawal of cash from the margin account? This could prevent any monies being moved to cover losses on any unrelated futures transactions. This is important, as typically gains from any hedging strategy may be part of the lender’s security.

Although the focus has so far been on the client seeking to borrow funds, there is also the possibility that the futures broker and the bank may also experience financial difficulties. Accordingly, procedures would need to be put into place to address both of these eventualities.

13.3.3

Prepay structures

A traditional forward sale (purchase) would require a producer (consumer) to deliver (receive) a fixed amount of a specified commodity at a pre-agreed price at a future date agreed between the two parties. Suppose that a producer agrees to deliver one tonne of copper every year for the next three years at current market rates. The current forward price curve is: Year 1: Year 2: Year 3:

USD 6,000 USD 6,100 USD 6,200

447

Commodity-Linked Financing

The prepay structure accelerates the payments made to producer by paying the present value of all of these cash flows up front. This may be a useful financing mechanism for those companies who may face constraints in being able to borrow money using a formal loan mechanism. To illustrate this, let us assume that the appropriate zero-coupon interest rates for years one to three are 1%, 1.5%, and 2% respectively. The present value (rounded) of each of the cash flows would be: 6,000∕(1.01) = 5,941 6,100∕((1.015)2 ) = 5,921 6,200∕((1.02)3 ) = 5,842 TOTAL = USD 17,704 For ease of illustration, any facility margin imposed by the lender to cover their credit risk has not been included in the calculation. The inclusion of a margin would increase the value of the denominator and therefore lower the prepaid amount. The client would then be required to deliver the agreed amount of copper on each of the agreed future dates. Jenkins (2012) argues that there could be structural variations on this theme. For example, instead of paying the full present value up front, the client receives a partial initial payment followed by a series of ‘cash for commodity’ exchanges throughout the life of the deal.

13.3.4

Prepaid variable forwards

In the previous example, the producer was able to sell their production on a forward basis and receive payment up front. However, if the price of the underlying commodity were to subsequently increase, they would not be able to benefit. A prepaid variable forward allows the producer some upside benefit while ensuring a minimum price. The structure is created with the client entering two additional option transactions to create a zero-premium collar. Zero-premium collars were first considered in Section 5.8.111. As a quick recap, the producer buys an OTM put and sells an OTM call with the strikes set such that there is no initial premium. The following hypothetical term sheet illustrates the concepts: Seller: Buyer: Underlying commodity: Notional amount: Maturity: One-year forward price: Floor price: Ceiling price:

Producer Bank Thermal Coal 10,000 MT One year USD 60.00/MT USD 55.00/MT USD 67.00/MT

448 Purchase price: Bank receives:

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Bank will pay the producer 97.09% of the floor price multiplied by the notional amount. Either (a) an amount of coal determined by the settlement ratio multiplied by the notional amount or (b) the cash equivalent of such an amount. The settlement ratio is determined as follows: i) If the prompt futures price of coal at maturity is less than or equal to the floor price, the ratio will be one. ii) If the prompt futures price of coal at maturity is greater than the floor price of USD 55.00 but less than the ceiling price of USD 67.00, then the ratio will be (floor price/prompt futures price of coal at maturity). iii) If the prompt futures price of coal at maturity is greater than or equal to the ceiling price, the ratio will be 1 – ((ceiling price – floor price)/ prompt futures price of coal at maturity).

The floor price of USD 55.00/MT is the strike price of the long OTM put purchased by the client. The ceiling price of USD 67.00/MT is the strike price of the short OTM call such that the structure is zero premium. Recall that another name for the zero premium collar is a ‘min-max’ structure, meaning this combination of options sets the minimum and maximum sale prices achieved by the producer. As presented here the transaction allows the customer either to deliver physical coal or to settle the transaction in cash, as the economic impact is the same. The associated cash flows are shown in Table 13.2 and are done from the client’s perspective. Column (1) shows the amount that is forwarded to the client at the start of the transaction. This is usually the present value of the long put strike. Here a zero-coupon interest rate of 3% p.a. has been used [100/1.03 = 97.09]. Column (2) is the future value of column (1). This is not the sum to be repaid to the bank at maturity but is presented here in ‘at maturity’ terms so that all of the subsequent cash flows in the example can be compared. Column (3) is the price of coal at maturity that will be used to determine the settlement ratio (i.e the prompt futures price of coal at maturity). Column (4) is the settlement ratio calculated as per the term sheet. Column (5) Although the structure may allow for physical delivery, the author has found that illustrating the cash settlement process provides a greater insight into the economics of the transaction. However, the volume of coal that will determine the cash settlement amount needs to be calculated and is shown in this column. It is the agreed notional amount multiplied by the settlement ratio. Column (6) shows the cash amount that is payable by the producer at maturity if they choose this settlement method. Notice that from the bank’s perspective, at all prices lower than put strike they will receive back less than the amount paid to the client. Since the analysis is being done using ‘at maturity’ values, the correct comparison is column

TABLE 13.2 Prepaid variable forward cash flows.

Cash advanced to client (USD)

Maturity value of cash advance (USD)

Prompt futures price of coal at maturity (USD/MT)

(1) 533,981 533,981 533,981 533,981 533,981 533,981 533,981 533,981 533,981 533,981

(2) 550,000 550,000 550,000 550,000 550,000 550,000 550,000 550,000 550,000 550,000

(3) 40 45 50 55 60 65 70 75 80 85

Settlement ratio

Volume of coal to be settled (MT)

Cash equivalent of coal to be settled (USD)

Market value of coal retained at maturity (USD)

Net value of cash equivalent settled, and coal retained (USD)

Net future value of package

(4) 1.00000 1.00000 1.00000 1.00000 1.00000 0.92308 0.85714 0.84000 0.85000 0.85882

(5) = (4) x 10,000 10,000 10,000 10,000 10,000 10,000 9,231 8,571 8,400 8,500 8,588

(6) = (3) x (5) (400,000) (450,000) (500,000) (550,000) (600,000) (600,000) (600,000) (630,000) (680,000) (730,000)

(7) = (3) x 10,000 400,000 450,000 500,000 550,000 600,000 650,000 700,000 750,000 800,000 850,000

(8) = (6) + (7) 50,000 100,000 120,000 120,000 120,000

(9) = (2) + (8) 550,000 550,000 550,000 550,000 550,000 600,000 650,000 670,000 670,000 670,000

449

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(6) with column (2). The loss to the bank is due to the fact they have sold a put whose payout will increase as the price falls. If it is assumed that the producer retains the coal, column (7) shows the ‘at maturity’ market value of the commodity. This would also represent the amount that the producer would earn if they were to sell the product at the prevailing price. Column (8) shows the net of the cash that has been delivered to the bank at maturity (column (6)) and the market value of the coal they have retained (column (7)). Column (9) summarises the economics to the client. These values represent the ‘at maturity’ sale price the producer would achieve from selling the coal. Notice that as predicted the minimum sale value of USD 550,000 is set by the strike of the long put (10,000 MT x USD 55.00), while the maximum sale proceeds of USD 670,000 were set by the strike of the short call (10,000 MT x USD 67.00). For prices between the option strikes, since neither the call nor the put is exercised, the client realises the current market value for the sale of their coal.

13.3.5

Lending risks

Inevitably, any form of credit extension will expose the lender to several risks. In relation to commodity financing they include: Fraud risk – How well is the client known? If the warehouse of a shipping company is to be used, are they reputable? One of the big risks in this area is to ensure that the agreed physical product exists, and the safekeeping provisions are adequate. Counterparty credit risk – Credit risk relates to the ability and willingness of a borrower to repay monies lent. For example, if a producer offers extended payment terms to their end buyers this could create the potential for non-payment and possibly default. Suppose a producer has sold a commodity forward on a fixed price basis, but the buyer subsequently chooses not to fulfill the terms of the deal as they observe that prices have since fallen. They may decide that defaulting on the transaction and buying the product on the spot market is a more economic decision. Notice how a change in price (a market risk) can quickly morph into the possibility of non-payment (credit risk). Wrong way risk – Gregory (2020) describes ‘wrong way risk’ as ‘the phrase generally used to indicate an unfavourable dependence between exposure and counterparty credit quality, i.e. the exposure is high when the counterparty is more likely to default’. Although wrong way risk is not always obvious, perhaps one example would be a loan to a metal producer, where the collateral taken is their own output. If the price of the metal were to fall reducing the value of the collateral, it may also be associated with a decline of the company’s ability to repay their debts. Force majeure – A force majeure event is usually defined as acts, events or circumstance that are beyond the control of the contracting parties. If such a clause is inserted into a contract it may excuse one or both of the parties from having to complete its obligations under the contract. This became more prominent in early 2020 after the breakout of COVID-19 in China. Reports emerged that LNG and copper buyers had invoked the clause to avoid paying out for a commodity that would not be used for a considerable period of time.

Commodity-Linked Financing

451

Position risk – Some clients may enter into commodity hedging strategies merely to protect the value of a known exposure. However, some entities may have a mandate that allows them to take positions that are not directly linked to their underlying business and are therefore more speculative in nature. Although in itself this is not intrinsically wrong, if not properly controlled it could lead to substantial losses. Quality risk – The underlying commodity can sometimes spoil (e.g. agricultural goods) or not meet a certain pre-agreed specification (e.g. energy products such as crude oil or refined products). Typically, a lender would want to implement controls that would consider where the product is stored, how and when it is tested, and to ensure that quality is correctly assessed.

13.3.6

The commodity carry trade

One technique that was popular in China for a while was based on a well-established structure seen in the foreign exchange markets called the carry trade. A copper trader holding metal as inventory would use it as collateral to take out a US dollar loan. If USD interest rates were sufficiently low, then the associated borrowing cost would be relatively small. The proceeds of the loan would then be converted into local currency and invested in a higher yielding domestic asset or lent out in the ‘shadow banking’ sector to earn a more favourable return. At the end of the loan the transaction cash flows would then be reversed, ideally generating a profit. However, this strategy is not without risk. To illustrate the concept, let us assume some hypothetical values. Warehousing and insurance costs are ignored for ease of illustration. A copper trader holds 1,000 MT of the metal as inventory, which is assumed to be trading at USD 6,000/MT. They pledge the entire inventory as collateral and take out a 12-month loan to which the lender applies a haircut of USD 1 million. The resulting USD 5 million loan has an assumed annual interest rate of 1%. This is then converted into CNY and if the exchange rate is assumed to be USD 1.00 = CNY 7.00 this will translate into local proceeds of CNY 35 million. These monies are now invested at a higher domestic interest rate of, say, 5% also for 12 months. At the end of the term of the CNY investment the trader receives back principal and interest equal to CNY 36,750,000, which is then converted back into USD. If the exchange rate is unchanged this will return USD proceeds of 5,250,000. They will be required to repay 5,050,000 on the USD loan and so will make a profit of USD 200,000. Notice that inherent in this trade is the impact of the movements in the spot exchange rate, which was assumed to remain unchanged. If spot CNY appreciates (e.g. moves to USD 1.00 = CNY 6.00) then the CNY investment converts back into USD 6,125,000 increasing transaction’s profit to USD 1,075,000. However, a CNY depreciation would have the opposite impact reducing the overall profitability of the deal and possibly leading to a loss. At the time this trade was popular, domestic interest rates in China were relatively high and the USD/CNY exchange rate was fairly stable as it was ‘managed’ by People’s Bank of China (the central bank). Eventually, interest in this type of transaction dwindled when evidence of fraud was uncovered. Traders had apparently agreed to submit the same inventory of metal as collateral to several lenders. Anecdotally, this seems to have been done by photocopying

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the metal warrants and using them to borrow monies that were substantially greater than the value of the underlying collateral.

13.3.7

Supply and offtake agreements

Having outlined the principles of the asset conversion cycle, this section provides an example of the financing issues faced by a hypothetical crude oil refiner. Suppose a refiner processed 50,000 barrels per day at a cost of USD 50/bbl. resulting in an expense of USD 2.5 million. It is likely that the refiner would also hold inventories of both crude oil and refined products. These volumes may well have been paid for but not yet processed or sold and so the company will have to finance this inventory either from their own resources or by means of a borrowing facility. One solution is for an intermediary such as a bank or trading house to eliminate a significant proportion of the working capital requirement by means of a supply and offtake agreement. The intermediary: ▪ Buys the existing inventory of crude oil and refined products from the refiner. ▪ Buys any new crude oil required by the refiner. ▪ Stores the crude oil on site at the refinery where normal refining operations can continue. ▪ Owns the finished refined products, which can then be sold to an end user. ▪ Will pay to the refiner on a periodic basis (e.g. daily, weekly, monthly) the difference between the cost of buying the crude oil and the income from the finished products, i.e. the crack spread plus any location premium. ▪ Charges the refiner a fee on a per barrel basis which would be set at a level that is more attractive than if they had borrowed funds using an alternative source. The overall result is a reduction of the refinery’s operating expenses and the generation of fee income for the bank based on the number of barrels processed. To convey a sense of how such an agreement would work, consider the following simplified example. The first part compares the cost to the refinery of having to finance the crude oil supplies against the terms agreed under the supply and offtake agreement. Suppose the oil refinery processes 50,000 barrels of crude oil each day. Under the terms of a commercial contract with their normal supplier they are required to prepay for their supply of crude oil. In this example we will assume that the refiner will have to pay for the oil two weeks (14 days) before it is delivered into their inventory. The refinery may well finance this purchase using a mix of their own funds and some external borrowing and so as such it is reasonable to assume their weighted average cost of capital (WACC) would be representative of their borrowing costs. WACC is an interest rate that reflects the cost of the different debt components used to finance the company, weighted by their proportion within the funding mix. So, if crude oil is trading at USD 50.00/bbl. and their WACC is assumed to be 10%, their borrowing cost for the 14-day period between paying for the commodity and receiving it into their inventory would be: USD 50.00 x 10% x 14∕360 = USD 0.19∕bbl.

453

Commodity-Linked Financing

It is assumed that the refiner will have an ongoing need to buy crude oil since they are refining a certain amount each day. Over a one-month period there will be 30 purchases from their supplier, each of which will be prepaid two weeks prior. So, their cost of borrowing over the month would be: 50,000 barrels a day x 30 days x USD 0.19 borrowing cost = USD 285,000 In comparison, suppose their supply and offtake intermediary has been able to negotiate favourable credit terms with a supplier for the same grade of crude oil. Under the terms of their purchases, the intermediary can defer payment for the crude oil until 30 days after delivery to the refinery. If the intermediary’s cost of funds is assumed to be 2% then they are able to achieve an ‘opportunity benefit’; that is they will have use of the funds required to make the purchase for about one month which they could perhaps invest or use to repay a debt. The benefit to the intermediary for each barrel purchased would be: USD 50.00 x 2% x 30∕360 = 0.08∕bbl. Again, if 50,000 barrels were delivered each day over a one-month (30 day) period the total monetary benefit would be: 50,000 barrels a day x 30 days x USD 0.08 = USD 120,000 So, the introduction of the intermediary benefits both participants. Since the refiner is no longer required to buy their crude oil, their borrowing cost will reduce, and the intermediary will have use of funds for about 30 days before being required to pay for the crude oil. The second step is to consider the financing of the refinery’s inventory, the sale of the refined products, and the overall profitability. Once the crude oil is received into the inventory, there will be an ongoing borrowing cost until it is sold. The intention is for the intermediary to purchase this inventory so the refinery can further reduce their borrowing costs. We will make some assumptions to illustrate the economics: ▪ The refinery always maintains an average inventory of 750,000 barrels of crude oil (about 15 days’ worth of production). ▪ On an ongoing basis they also hold an average inventory of 500,000 barrels of gasoline. ▪ If the average price of crude oil and gasoline is USD 50.00 and USD 60.00/bbl., respectively then the individual value of the two inventories is USD 37.5 million and USD 30 million to give a total of USD 67.5 million. The first question to ask is what would be the borrowing cost associated with holding the inventory without the supply and offtake agreement? For ease of illustration let us suppose that we apply the WACC value of 10% shown earlier. The cost of financing the inventory on an annual basis from the refinery’s perspective would be: USD 67.5 m x 10% = USD 6,750,000

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Now let us consider how much it would cost the intermediary to finance the inventory. In these types of transaction, it is very possible that the intermediary will finance 100% of the inventory. If we assume their own borrowing cost is 2% then the intermediary’s cost of funding the inventory would be: USD 67.5 m x 2% = USD 1,350,000 The third and final part of the transaction is the sale of the refined products and the ‘crack spread’ payment to the refinery. As mentioned previously, the intermediary will be responsible for selling the refined products and passing back the refining margin to their client. From this refining margin, a per-barrel charge will be subtracted which will be related to the costs incurred by the intermediary. For example, the USD 1.35 million expense relating to the funding of the inventory will be passed onto the refinery. But since the intermediary will wish to make some profit from the transaction it is likely they will add a margin to this sum. However, the refinery’s borrowing costs relating to the inventory are reduced by USD 5.4 million (USD 6,750,000 − USD 1,350,000), so if the intermediary’s profit margin is less than this amount both sides will benefit. Note that at the end of the maturity of the transaction, the refiner will be required to repurchase their inventory from the intermediary. This means that they will have a price risk. To hedge this transaction the refinery could consider a variety of structures: ▪ Buy a cash-settled futures contract. If the price of repurchasing their physical inventories has increased, the long futures position should show an offsetting profit. As ever though, the refiner could be faced with basis risk in that the specification of the future may not match the underlying exposure in terms of maturity, quality, or location. If this were the cash, then arguably a forward transaction would be more appropriate. ▪ Enter a cash-settled option structure. The purchase of an OTM call option may be a possibility but it is unlikely that the refiner would be comfortable with paying a premium. They may decide that a zero premium structure is more appropriate, where they would sell an additional OTM put to finance the call. Since both options are economically equivalent to buying the underlying, this structure (also referred to as a ‘min-max’ solution) would set the minimum and maximum purchase price. These are only two indicative structures and readers interested in other option structures (exotic and vanilla) are referred to earlier sections in the text, with perhaps Section 5.8 illustrating a range of possible solutions.

13.4

LONGER-TERM DEBT FUNDING SOLUTIONS

The previous two sections on project finance and working capital focused on two opposite ends of the debt maturity spectrum. This section considers solutions for debt that is raised for ‘general corporate purposes’.

Commodity-Linked Financing

455

The common theme in this section is the reduction in borrowing costs by the embedding of some form of optionality into the debt structure. However, this is not without risk, as reducing interest expense would usually involve the sale of optionality. However, if structured correctly, there is an argument to say that if commodity prices move in favour of the market participant they may be willing and able to incur a higher than normal borrowing cost.

13.4.1

Embedding vanilla optionality into a loan

Suppose there is a corporate client whose income and expense is intrinsically linked to the price of crude oil, perhaps an airline. They are considering borrowing money for three years, with interest payable on a quarterly basis, perhaps referencing some interest rate index such as the Secured Overnight Financing Rate (SOFR) plus some form of spread that is reflective of their credit risk relative to this benchmark. Although SOFR will vary over time, the credit spread will remain fixed and so it is the variable interest rate component that the company is seeking to reduce. As part of the transaction they enter a series of option trades, one transaction for each of the 12 quarterly interest payments. The option transaction that is executed in each quarter is referred to as a ‘bull spread’ in that the maximum benefit is realised when prices rise, but the strategy loses money if prices fall. A bull spread can be structured using either call options, when it incurs a premium, or with put options, when it will be cash generative. The required options are: ▪ Bull spread with calls: Buy a low strike call with a relatively high premium; sell a high strike call with a relatively low premium. On a net basis a premium is incurred. ▪ Bull spread with puts: Buy a low strike put with a relatively low premium; sell a high strike put with a relatively high premium. On a net basis this will generate a premium. Although something of an aside it might be tempting to think that the put structure is always ‘better’ but it can be shown that the risk-return profile differs between the two variants. When using put options, although the transaction will generate a premium, the maximum profit will be lower, and the maximum loss will be higher than the call equivalent. The proof is outside the scope of the text. Since the bull spread constructed with put options would be cash generative, this money could be paid to the airline up front that could use the funds to subsidise their interest costs. Structured in this manner the option component of the transaction would incur maximum losses at lower crude oil prices but all other things being equal, the airline’s profitability should therefore increase, as their fuel cost would decline. The increased borrowing cost occurs in an environment where the airline can absorb the additional expense.

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To illustrate the structure, suppose that the following market conditions apply: Underlying commodity: Current prompt futures price: Three-year futures price: Notional amount: Details of option trade: Maturity of option trade: Number of option trades: Reference settlement price: Payout on option trade:

Crude oil USD 25.00 USD 20.00 (i.e, the market is in backwardation) 40,000 barrels per quarter Client sells USD 20.00 put and buys USD 16.00 put Each option trade will have a three-month maturity. One option trade for each separate, three-month maturity. The average, over each three-month period, of the daily settlement price of the front month crude oil futures. If the reference settlement price over each three-month period is: (a) Greater than USD 20.00, there is no payment (b) Between USD 16.00–20.00, the airline pays the bank the difference between USD 20.00 and the reference settlement price multiplied by the notional amount. (c) Less than USD 16.00, the airline pays the bank the difference between the two option strikes multiplied by the notional amount.

To understand the mechanics of the payout, consider the following three scenarios: ▪ Crude oil settles at USD 25.00 – in this case the short, higher strike option is not exercised against the airline, as it is more advantageous for the option buyer to sell in the open market. The low strike option is also not exercised. The airline’s profit is the initial premium, which can be used to subsidise their interest payments. ▪ Crude oil settles at USD 18.00 – the low strike put is not exercised but the holder of the high strike option does exercise. The airline’s payout on the option combination is USD 2.00/bbl., as this represents the amount by which the short option is ITM. The airline’s profit or loss would be the initial premium income less the option payout. All other things being equal, their interest payments would increase. ▪ Crude oil settles at USD 12.0/bbl. – the holder of the high strike option exercises requiring the airline to make a USD 8.00/bbl. payout on the short put. But the airline now exercises their long, low strike option and receives a payout of USD 4.00. There is a net payout by the airline equal to USD 4.00, which is also the difference between the two strikes. The airline is effectively buying the underlying at USD 20.00 and selling at USD 16.00, so once the underlying price goes through the lower strike their payout will be fixed at USD 4.00/bbl. All other things being equal, their interest payments would increase.

457

Commodity-Linked Financing

The worst-case scenario for the airline would be for the oil price to fall and stay below the lower strike for the entire duration of the loan thereby increasing their interest expense. It is important not to lose sight of the fact that if the option structure is unprofitable, this is likely to be associated with low jet fuel prices, which will be an offsetting benefit to the airline. The structuring of this transaction highlights some interesting aspects of commodity options. Take the first option combination with a three-month maturity. The USD 16.00/USD 20.00 strike combination will be valued relative to the applicable futures price, which will be slightly lower than the current front-month futures price of USD 25.00. This will make both options deeply out-of-the-money and so the premium on this specific combination will be relatively low. However, now consider the same combination of options that will become effective for the final there-month period towards the end of the three-year contract. Since the market is deeply in backwardation, then this combination of options will be valued relative to the three-year futures price, which is assumed to be USD 20.00. This means the ‘moneyness’ of the options is greater and so will attract a greater premium. If the market were in contango, the premiums on these lower strikes would become increasingly OTM with respect to maturity. Set against this is the fact that the term structure of volatility may well be downward sloping if the forward curve is in backwardation. This means each combination of options will be revalued at progressively lower levels of volatility. Since the option strikes are different as well, the shape of the volatility skew will also have an impact on their value.

13.4.2

Commodity-linked interest rate hybrids

A typical hybrid funding structure is shown in Figure 13.4. Instead of entering into a vanilla interest rate swap, which pays fixed against a floating rate such as LIBOR a producer can enter into a swap where one of the cash flows references commodity prices in order to achieve a lower cost of borrowing. LIBOR Client

Bank Commodity-linked payment

LIBOR + spread

Debt proceeds

Underlying Loan

FIGURE 13.4 Generic commodity-linked swap.

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13.4.2.1

Overview of interest rate derivatives

Interest rate swaps In its most basic form, an interest rate swap consists of a series of periodic cash flow exchanges. One of the cash flows references a fixed rate of interest while the other references a floating rate of interest. The floating rate has traditionally been a benchmark index such as the London InterBank Offered Rate (LIBOR) but this is now being superseded by so-called ‘risk free rates’ (RFRs) such as: ▪ USD – Secured Overnight Financing Rate (SOFR). ▪ GBP– Sterling Overnight Index Average (SONIA). ▪ EUR – Euro short term rate (ESTER). Interest rate swaps are traded based on a notional monetary amount, which is usually fixed. The notional amount of a swap is merely a reference value and does not represent an actual monetary cash flow. It will simply determine the magnitude of any subsequent cash flow that is exchanged. Interest rate swaps are typically long-term with maturities that may extend out to 30 or even 50 years. Although the deals have a long-term maturity, the exchange of cash flows will take place on a more frequent basis (e.g. every six months). Traditionally, swap cash flow payments were fixed at the start of the period and paid in arrears. This convention works if the floating interest rate has a developed term structure. So, if the floating index were set to reference six-month LIBOR, then at the start of the period, the value applied to the notional amount can be quantified and paid in arrears. At the time of writing, some of the newer RFRs do not have defined term structures as, by design, they represent short-term interest rates for overnight borrowing and lending transactions. As a result, when applied to an interest rate swap, it is necessary to record each value daily and then at the end of the period, derive a single compounded value. To illustrate the principles involved, let us assume that fixed and floating are paid semi-annually, with the rates for the period being 2.5% and 2.0%, respectively. We will assume that the cash flows are denominated in GBP, the notional amount is £10 million and that in the six-month period there are 182 days. The fixed cash flows will therefore be: £10,000, 000 x 2.5% x 182∕365 = £124, 657.53 The floating cash flows will be: £10,000, 000 x 2.5% x 182∕365 = £99, 726.03 Since the two payments coincide there will be a net payment of £24,931.50 in favour of the receiver of fixed. Interest rate caps and floors A cap structure is a strip of OTC interest rate call options on a series of forward rate interest rates, all traded with a single strike. The cap gives the buyer protection

459

Commodity-Linked Financing

against an agreed index or reference rate such as LIBOR of a stated maturity rising above the pre-agreed strike rate. The term ‘cap’ is the collective name for the component options, which are individually referred to as caplets. A three-year cap with semi-annual settlement referencing six-month LIBOR will comprise of six periods but only five options (‘caplets’) as there is no option for the first period. This is because LIBOR for the first period is known on the trade date and so there is little need for any option protection. The premium payable on a cap structure is simply the sum of the individual caplet premia. This premium can be paid as a lump sum up front or amortised over the life of the transaction. The payoff on a cap for any single period is: Max ((Reference rate − strike rate) x notional x days∕day basis, 0)) A floor gives the holder the protection again an agreed reference rate of interest falling below a pre-agreed strike. Again, a floor is a collective name for the component options, which individually are referred to as floorlets. The mechanics of the floor are the same as the cap but the payoff to a holder would only occur if the reference interest rate were less than the strike rate. A floor can be thought of as a collection of individual put options on a series of forward interest rates. The payoff on a floor for any single period is: Max ((Strike rate − reference rate) x notional x days∕day basis, 0)) 13.4.2.2

Zero premium knock-in collar

Suppose there is a producer of copper who has some outstanding debt, which references a floating rate of interest. The debt has three years until maturity and the client is seeking to limit the magnitude of their interest rate payments. As a point of reference, the current three-year interest rate swap rate is 2.62%. If the client were convinced that interest rates were going to rise, the simplest and most inexpensive solution would be to pay this fixed rate on a swap and receive the floating index in return. The floating receipt could then be used to finance the payment on their underlying debt and so on a net basis they would be left paying a fixed rate courtesy of the swap. If the client was not sure about the future direction of interest rates, then a collar may be an attractive solution. This would work in the same way as the ‘min-max’ solution considered in Section 5.8.11.1. The client’s bank quotes the following combination of strikes that would result in a zero premium: Purchase of a cap

Sale of a floor

4.00% 3.50% 3.00% 2.66%

2.00% 2.21% 2.46% 2.66%

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From this it follows that: ▪ The higher the cap strike, the lower the floor strike. Increasing the cap strike makes the option more OTM, and so the strike of the floor can be set a lower value as the premium required to achieve an initial zero cash outflow is smaller. ▪ The lower the cap strike, the higher the floor strike. Lowering the cap to gain increased interest rate protection increases the cost of these options, and so requires a higher floor strike to finance the premium. For a client seeking to borrow money this will limit the benefit they will receive from falling interest rates. ▪ There is one set of rates where the strike of the cap and the floor are identical to achieve zero premium. This is an extension of the concept of put-call parity introduced in Chapter 2. ‘Cap-floor’ parity says that buying (selling) a cap and selling (buying) a floor is economically equal to paying (receiving) fixed in a forward-starting interest rate swap. Some sharp-eyed readers may note that the two strikes of 2.66% are not the same as the current swap rate of 2.62%. The pricing model used to construct this example was based on caps and floors that reference LIBOR. As mentioned earlier, where this is the case there are no options for the first payment period. That is because on trade date LIBOR for the first period is already known and so there is little point in having any optionality. The caplets and floorlets embedded in this structure will only become effective once the second period starts. As a result, the comparable swap maturity for our example is 2.75 years, effective in three months’ time with a fixed rate of 2.66%. The bank suggests to the client that a more attractive risk-return profile could be obtained by: ▪ Adding a knock-in barrier feature to the cap and, ▪ Referencing the knock-in condition to the price of copper, rather than to an interest rate. This should reduce the premium for two reasons: ▪ A barrier option will always have a lower premium than a non-barrier equivalent (see Chapter 1). ▪ Referencing the knock-in condition to another asset class introduces an element of correlation, which should further reduce the premium. Suppose that the bank structures the transaction with the cap at 3.50% but adds a knock-in feature that says the option will not be activated unless the ‘cash’ LME copper future trades below USD 5,000/MT. The barrier is monitored only on one day and that is the quarterly date when the interest rate is reset. Note that each caplet within the structure has its own barrier so if the cap is activated in one period, it may not be activated in the next. Due to the lower premium on the cap, the bank is willing to improve the strike on the floor by lowering it from 2.21% to 1.90%. This would allow the producer to benefit to a greater extent from falling interest rates. There is an element of flexibility

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available to the client when structuring this product. The original level of the floor could be retained at 2.21% and the cap strike lowered or perhaps a transaction with a lower cap and lower floor. What are the practical implications of this? If the price of copper remains high and above the barrier the cap is not triggered and the producer has no protection over rising rates. Arguably though, with high prices for the product they are selling, they are better placed to meet this increased interest expense. If copper prices were low resulting in activation of the cap, any rise in interest rates would now be limited to the strike of 3.5%. This is a favourable situation for the producer as an environment with low copper prices and high interest rates would likely place a strain on cash flow. However, it is worth considering the likelihood of this scenario occurring and therefore whether the structure offers genuine value. High interest rates are normally associated with an economy experiencing significant growth and are used by Central Banks as a way of restraining potential inflation. So arguably, high interest rates are more likely to be associated with high copper prices meaning that the cap is unlikely to be activated. The shape of the forward commodity curve and how prices are expected to evolve relative to this will also have an impact on the value of the cap. Suppose that the copper market is experiencing a very significant element of backwardation with most forward prices below the USD 5,000 trigger. This would increase the likelihood that the knock-in barrier would be activated making the option relatively more expensive. This would increase the cost of the barrier removing some aspects of the relative attractiveness of the structure mentioned earlier. The opposite would also apply. A market in contango means all that current forward prices are likely to be above the barrier, meaning there is a smaller chance it will be activated. This reduces the likelihood that the seller will need to make a payout and so the cost of the option would fall. 13.4.2.3

Interest rate swap with commodity-linked digital payout

Consider the following hypothetical term sheet. Client: Notional amount: Maturity: Client receives: Client pays: Special provision:

Copper producer USD 10 million Three years Three-month USD LIBOR Three-month LIBOR − 1.25%, subject to special provision If on each interest payment date, the ‘cash’ LME futures price for copper is at or above USD 6,000 then the client pays Three-month LIBOR + 1.5%, otherwise client pays Three-month USD LIBOR − 1.25%.

If copper trades at lower prices, interest rate costs are lower; higher copper prices attract a higher interest rate cost. This is again based on the notion that in a high metal price environment, the producer would be more able to finance higher interest costs. In a low metal price environment, where cash flows may be lower, interest costs would also be lower.

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Note that the coupon ‘steps up’ if copper prices are at USD 6,000 or higher. Below this ‘barrier’ the client benefits by a fixed amount but above it, they will pay substantially more. The embedded optionality could be modeled from the client’s perspective as a series of short, three-month digital copper options with a strike rate of USD 6,000. If copper settles at less than the strike rate then the client retains the premium and enjoys a subsidised interest rate; above the strike the digital call cash-settles and the client will pay out a relatively larger fixed amount, which will result in a higher interest cost. 13.4.2.4

Interest rate swap with a range accrual

This structure is designed to reduce interest rate costs when commodity prices are low. However, the opposite will also apply; the client will be faced with higher borrowing costs in a higher price environment. The following hypothetical term sheet illustrates: Reference commodity: Client: Notional amount: Maturity: Settlement: Client pays:

Client receives: Reference sugar price: Strike level: Current front month futures price: Vanilla interest rate swap:

Raw sugar Producer USD 5 m Three years Quarterly 1.5% + (5% x N/D) N = number of days in each quarter that reference sugar price settles above the strike D = number of days in each quarter Floating ICE sugar; front month price USD 0.10/lb USD 0.12/lb 3%

This range accrual structure consists of a series of ITM digital call options each with a maturity of one day. They are structured to have the same strike (USD 0.10/lb.) and the same digital payout (5% of the notional). In this case the fixed component of the swap has an interest rate of 1.5%, which is half of the current vanilla equivalent. The producer is selling the strip of digitals and so rather than receive a discrete premium payment the option proceeds are amortised over the life of the transaction to subsidise the fixed rate. For every day that the price of sugar is above the strike, the digital pays out a fixed amount. However, this is accumulated and paid at the end of each quarter. The client will benefit if the commodity price stays below the strike price, as the daily payout will be zero.

CHAPTER

14

Commodity Investing

14.1

COMMODITY INVESTORS

There is a broad range of potential commodity investors which includes the following participants: ▪ Investment banks and hedge funds – also sometimes referred to as ‘leveraged’ accounts in that they are typically allowed to borrow to finance their activities. ▪ Private bank and retail sector – the most popular choice of instrument would either be a mutual fund/unit trust or an exchange traded product (ETP). ▪ Real money accounts – this sector encompasses institutional investors (e.g. mutual fund/unit trust fund managers, insurance companies, and pension funds) who have restrictions on their ability to borrow. Their investment activities are longer-term in nature and are characterised as being one of ‘buy and hold’. ▪ Commodity trading advisors – these investors typically use futures to gain exposure to a particular sector of the commodities market. Their investment activities may not be restricted to just commodities and may include exposures to other asset classes. ▪ Sovereign wealth funds – Perhaps seeking to diversify their holdings into long-term strategic investments. Figure 14.1 conveys a sense of the different investment horizons for each of the main participants. In terms of typical strategies and popular investment structures it may be possible to make some generalisations: Up to one year ▪ This would capture tactical trades or strategies that arise opportunistically. For example, if an investor believes that a particular commodity displays some form of mean reversion, then a very low or high price might represent a short-term buying or selling opportunity.

463

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Pension funds and insurance companies

Sovereign wealth funds

Private bank and retail sector Asset managers Hedge funds

1 year

5 years

FIGURE 14.1 Commodity investors and their respective investment horizons.

▪ However, a quick Internet search would also suggest that risky bets made by commodity participants are not a rare event. The example of Amaranth Advisors was outlined in Chapter 3. ▪ Relative value trades are usually characterised as the purchase of one asset and the sale of another. Typically, this may be due to some fundamental economic reason (e.g. platinum vs. palladium, gold vs. silver) or could be as a result of a perceived correlation that does not reflect a fundamental relationship (e.g. crude oil vs. gold). ▪ Another popular strategy that covers several different time frames would be for the investor to track a benchmark commodity index. Between one and five years ▪ One of the features of commodity investments is that they offer a form of diversification. ▪ Another popular motivation (certainly true at the time of the first edition of this text) is that commodities do offer the potential for significant growth. The asset class can also display significant volatility, whose value could be captured using options. ▪ One of the main ways of investing in commodities has been exchange traded products (ETPs). Arguably, one of the key drivers for their popularity is the fact that they are traded on an organised exchange and so are relatively easier to value. ▪ Structured products such as capital protected or yield enhanced notes can be popular with retail and high net worth investors and would also appear in this time frame. Over five years ▪ Again, the issue of diversification is important in this segment of the market. ▪ Investors would also be interested in a long-term allocation of funds into a commodity index that captures the returns from a wide number of different commodities.

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14.2

465

PREFERRED INSTRUMENTS

Subsequent sections of this chapter will consider the different ways in which investors can take exposure to commodities. By way of an overview these can be broken down into three main categories: ▪ Total return swaps (TRS) referencing an index – a total return swap is a bilateral agreement, which allows participants to exchange cash flows that refer to different sources of return. A commodity TRS would typically reference a commodity index such as the S&P GSCI A common swap structure would involve the exchange of a cash flow that references the total return on the index for one that references a risk-free yield. ▪ Exchange traded products (ETPs) – an ETP is a security that trades on a stock exchange and references either a single commodity (e.g. gold) or a basket of commodities (e.g. a commodity index). ETPs break down into three main types. An exchange traded commodity (ETC) is where the security is backed by a physical holding in the underlying asset. An exchange traded fund (ETF) is where the return generated by the security is achieved using derivatives such as futures and swaps. Given the way in which ETCs and ETFs are designed it is unlikely that the issuer will default as they are structured to be bankruptcy remote. An exchange traded note (ETN) is similar to an ETF in the way that it generates returns except it represents debt of a non-bankruptcy remote issuer such as a bank, so an investor will have counterparty risk. ▪ Medium term notes (MTNs) – these are sometimes referred to as ‘structured products’ and would traditionally be issued by banks perhaps aimed at the retail and private banking sector.

14.3

MARKET SIZE

Apart from the exchange traded structures, the remaining components identified in Section 14.2 are typically traded on a bilateral, over-the-counter basis. However, it is possible to gauge the size and structure of the market based on research (see for example, Barclays, 2018a). Figure 14.2 shows the evolution of assets under management for three separate years. Some characteristics of commodity investments include: ▪ Estimates suggest that AUM in 2001 were USD 15 billion. They reached a peak of USD 418 billion in 2012 falling to USD 311 billion by 2017. ▪ Figure 14.2. illustrates that initially TRS and ETPs are the most popular way in which investors take exposure to commodities. Structured notes represent a small proportion of the amount outstanding. ▪ The most popular sector referenced by commodity investments is precious metals, followed by energy, agriculture, and then base metals. ETPs have been traditionally dominated by precious metal structures.

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450 400 81 350 7

300 250

204

148

133

156

200 150 6

100

9

50

75

0 2005

2012

Total Return Swaps (bottom)

2017

Exchange Traded Products (middle)

Structured Products (top)

FIGURE 14.2 Commodity assets under management (AUM) in USD billions. Source: Barclays Bank

14.4 14.4.1

RATIONALE FOR INVESTING IN COMMODITIES Return enhancement and diversification

In the first edition of this text, which was written on the back of a surge in commodity prices, the asset class was characterised as a high return but highly volatile asset class. Based the IMF’s Global Price Index of all commodities with January 1992 set as the base index value of 100, commodities reached a peak value of just over 400 index points by July 2008. To place this into some context, if the S&P 500 index had been rebased to 100 for the same start date, then by the same end date its value would have been 309. However, within six months (January 2009) the commodity index had lost half its value. Thereafter, prices did display significant volatility: April 2011: February 2016: October 2018: April 2020:

388 index points 174 index points 265 index points 168 index points

One of the main benefits of commodities is that they are negatively correlated with financial assets and therefore act as a powerful portfolio diversifier. Modern portfolio theory argues that the variability of a portfolio’s returns (i.e. the risk or volatility) is calculated as the weighted sum of the individual volatilities adjusted by the degree to which they are correlated. Provided that the assets in the portfolio are not perfectly positively correlated the volatility of the portfolio will be less than the weighted sum of the volatilities of the constituent assets that form that portfolio. Equation 14.1 shows the composite volatility for a two-asset portfolio. 𝜎basket =

√( ) ( ) ( ) w2 x1 𝜎x21 + w2 x2 𝜎x22 + 2 × wx1 wx2 𝜌x1 x2 𝜎x1 𝜎x2

(14.1)

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where: 𝜎x21 = Variance of asset 1 𝜎x22 = Variance of asset 2 𝜌x1 x2 = Correlation between asset 1 and asset 2 𝜎x1 = Volatility of asset 1 𝜎x2 = Volatility of asset 2 wx1 = Proportion of asset 1 wx2 = Proportion of asset 2 In the first edition of the text, the following correlation coefficients between commodities and some popular financial assets for the period 1970–2005 were presented as: Equities Bonds Treasury Bills

−0.28 −0.10 −0.01

However, for the period 2006–2016, the correlations were: Equities Bonds Treasury Bills

+0.40 +0.28 +0.10

Morgan Stanley (2009) provides one explanation for this change in correlations: ‘Correlations between commodity and equity returns are most strongly negative when the global economy is running closest to capacity and highest when the global economy experiences its greatest slack. When capacity utilisation is high (the peak in the business cycle) commodities are usually scarce relative to demand and being bid up while companies struggle to push through higher costs to the customers, negatively affecting earning and thus equity valuations. By contrast, at the trough of the cycle, when the global economy has significant slack, any rise in demand lifts both commodity and equity prices and any fall in demand lowers both’. The research suggested four possible growth-inflation scenarios, which illustrates the correlation between equities and commodities (Figure 14.3).

14.4.2

Inflation hedge

Commodity prices are generally positively correlated with realised inflation. However, this is not surprising in that many inflation indices have a commodity component. Why is this important? For a fixed income investor, the real return on a fixed coupon bond will be eroded in a high inflation scenario. Although real returns are somewhat casually thought of as a ‘rate of interest adjusted for inflation’ a more useful definition is that

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• High economic growth

• High economic growth

• Low inflation

• High inflation

Equities

Equities

Commodoties

Commodoties

Equities

Equities

Commodoties

Commodoties

• Low economic growth

• Low economic growth

• Low inflation

• High inflation

FIGURE 14.3 Growth and inflation scenarios – commodity and equity correlations. Source: Morgan Stanley, 2009. they signal how much today’s savings are worth in terms of future consumption. So, if a one-year bond has a coupon of 2% but inflation is 3%, then the additional amount of goods and services an investor would be able to afford at the end of the period will fall by about 1%. An investor who is concerned about the impact of inflation could allocate some of their portfolio to commodities in the expectation that it would generate an offsetting gain.

14.4.3

Hedge against US dollar

One of the themes discussed on several occasions within this text is the relationship between commodities and the US dollar. The theory suggests that if the USD weakens against another currency it will make the domestic currency price for a USD-denominated commodity lower. This will increase demand so therefore push up the USD cost of the commodity. If an investor holds a portfolio of USD-denominated financial assets (equities, bonds) then a weakening of the USD will result in a fall in value of their investments in domestic currency terms. But an allocation towards commodities should have an offsetting impact. 14.4.3.1

Risk premia strategies

What is a risk premium? Barclays (2011b) defines a risk premium as ‘an excess return potentially available to an investor willing to assume some identified risk. A risk

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469

premium strategy is a simple systematic (i.e. non-discretionary) strategy designed to capture that risk premium, accepting the potential for losses, should the “risk” materialize’. They identify a number of strategies that could be applied within a commodities context: Curve – this type of transaction is sometimes referred to as a ‘term premium’ strategy whereby an investor takes opposite positions at different maturities along the forward curve. These strategies aim to provide additional return for taking on the greater uncertainty associated with longer maturity risk versus shorter maturity risk. The risk is that the curve will move in way that makes the combination of transactions unprofitable. Within commodities this is often implemented by going long, longer-dated futures, and short, shorter-dated futures. Value – these strategies seek additional compensation by going long undervalued assets and shorting overvalued assets in anticipation that they will converge over some (unspecified) future period. The risk is that it may take a long period of time for the ‘correction’ to occur. In the meantime, it is possible that the asset (considered to be overvalued) increases in price, while the undervalued asset decreases in price. If a particular commodity market were to move into a steep backwardation, due to a relative scarcity of a commodity it could suggest that near-dated futures are overvalued while longer-dated futures are undervalued. The appropriate strategy would be to sell the near-dated contract and buy the longer-dated contract. Momentum – these strategies go long past winners and short past losers. The risk is that the chosen assets move in an opposite direction than anticipated making the transaction unprofitable. Arbitrage – an arbitrage strategy involves taking a position in assets whose prices should converge at some future date. The possible risk with such strategies includes: ▪ The time it takes for the prices to converge. ▪ The risk that the model used to determine the relationship is incorrect. ▪ That the cost of financing the position may become uneconomical. ▪ That the position may experience liquidity issues making it difficult to unwind without adversely impacting the profitability. Volatility – these strategies seek to earn the premium between implied and realized volatility in the options market. In most asset classes, implied volatility will tend to trade higher than realised volatility as option sellers (i.e. sellers of implied volatility) will demand a risk premium for taking on substantial risk. The danger is that realized volatility may ‘spike’ upwards, resulting in significant losses.

14.5

COMMODITY INDICES

Instead of linking the payout on an investment to a single commodity, a popular technique has been to reference the instrument to a commodity index. Although there are many different indices with different methodologies, arguably the most popular index

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

for investment purposes is the S&P GSCI. The index was launched in 1991 and was the first major commodity index designed to meet investor demand for commodities as an asset class. The aim of the index is to include as many commodities as possible, but the rules prevent the inclusion of many items as they may not be considered liquid and there is no easily accessible way in which an investor can take exposure (e.g. there is no futures contract). The S&P GSCI is a beta index in the sense that it provides an investor with a return that reflects the overall market.

14.5.1

Construction

At the time of writing the index contains 24 commodities from the main commodity sectors: ▪ ▪ ▪ ▪ ▪

Six energy products Five industrial metals Eight agricultural products Three livestock products Two precious metals

Although the index includes a diverse range of commodities, there is a very large concentration in energy-related products (over 60%). The weights of the constituent commodities are determined annually by committee and driven by the US dollar value of global production over a five-year period. The different commodities and their proportions within the index are illustrated in Figure 14.4. The index is also quoted as a series of sub-indices, which include (amongst others): ▪ Energy ▪ Non-Energy 30.00%

25.00%

20.00%

15.00%

10.00%

5.00%

®

FIGURE 14.4 Components of the S&P GSCI . Source: Standard and Poor’s, www.goldmansachs.com/gsci/insert.html

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Industrial Metals Precious metals Agriculture Livestock Agriculture and livestock

One of the key features of the S&P GSCI is that it does not reference the physical commodity but rather the relevant futures contract. The index provider (Standard and Poor’s) does not actually trade any futures, as the index is just designed to generate a value that replicates the hypothetical effect of doing so. It was designed to be a tradable index in that a market participant could replicate the return by trading the underlying future. Since it would be impractical for many market participants to take possession of the physical commodity then it makes more sense to reference the return to a tradable futures contract. One of the consequences of referencing futures means the index provider would need to decide as to appropriate contract maturity; for the S&P GSCI this is the front-month contract. Some futures contracts such as energy have monthly expiries, while agricultural contracts such as coffee and cocoa, may only have five maturities in a year. This also implies that at some point each reference future will expire, meaning that in order to maintain the exposure, the contract will need to be rolled to the next maturity. The rolling process requires the investor to simultaneously sell their existing contract and buy the following maturity. The S&P GSCI methodology assumes that the futures are rolled on the fifth to the ninth business day of the month in which they expire. The portfolio is shifted from the first to the next month at a rate of 20% per day for the five days of the roll period.

14.5.2

Quoting conventions

By design, the S&P GSCI (and the various sub-indices) replicates the return from a ‘long only’ portfolio of commodity futures and is published in three forms: ▪ Spot index – which is based on price levels of the futures contracts included within the S&P GSCI. ▪ Excess return (ER) index – incorporates the returns of the spot index as well as the discount or premium obtained by rolling hypothetical positions in such contract forward as they approach maturity. The return from this rolling process is sometimes referred to as the ‘roll yield’. ▪ Total return (TR) index – incorporates the returns of the ER index and interest earned on hypothetical, fully collateralised contract positions on the commodities included in the index. Recall that the purchase of a future only requires the buyer to pay a small initial margin relative to the contract’s exposure. If the futures contract has an exposure of USD 100,000 the investor may only be required to place, say, a USD 5,000 margin with the clearing house. A fully collateralised strategy acknowledges that certain investors may not have a mandate to trade such ‘leveraged’ positions and so assumes the investor places the balance (USD 95,000 in this example) into a short-term, risk-free investment such as US Treasury Bills.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

The calculation of the index is somewhat involved, but it is worth noting that adding the excess return index to the interest on the short-term investment does not give a number equal to the published total return index. The TR index calculation reflects both the interest earned on the short-term investment, which can be reinvested into the futures position, and the change in the monetary value of the futures position, which in turn affects the size of the short-term investment.

14.5.3

Evolution of index construction

Indices such as the S&P GSCI were the first iteration of index investing and were sometimes referred to as ‘passive long only’ or ‘beta’ indices. The next evolution in indices was termed ‘enhanced beta’ structures. These indices took the basic idea of traditional beta indices but tweaked the features to provide an alternative source of return. For example: ▪ The commodities included within the index may be different than the beta version. ▪ The weightings of the index may be based on a methodology different to other offerings. ▪ The assumed position in the underlying futures could be a combination of both long and short positions. ▪ The maturities of the futures could reference longer- rather than shorter-dated contracts. ▪ The date on which the futures contracts are assumed to roll will differ from the traditional fifth to the ninth business day of the month. Both ‘pre-roll’ and ‘post-roll’ strategies have been used. ▪ Where the capital that is not invested in the futures should be allocated. The next step was to look at ‘active alpha’ strategies that would use some form of proprietary strategy to seek out excess returns above beta. This might involve: ▪ Active management of the underlying futures, perhaps incorporating some form of momentum strategy. ▪ Trading futures with differing liquidity profiles. ▪ Incorporating some form of optionality that might exploit the difference between implied and realised volatility.

14.5.4

The myth of the roll yield

The worst thing about being an author is coming to realise that something that you had previously written could be wrong. For me, this applies to the concept of the ‘roll yield’, within the context of commodity index returns. In the first edition of the book, I had described the intuition behind the concepts of spot, excess, and total returns. I had based these definitions on discussions with market practitioners combined with a lot of reading. The inaccuracy relates to the way in which roll yield is defined but in my defence, I can now see that there is a significant and ongoing misunderstanding among market participants.

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Traditionally, most literature (both academic and practitioner) defines the roll yield as the profit or loss from rolling a futures contract. Within the context of commodities, the assumption is that an investor seeking to replicate the returns of a particular index would buy a nearby future and then continually roll the position to maintain their exposure and this process would generate a profit or loss. Suppose an investor who is long a future in a backwardated market decides to close the position to avoid physical delivery and so rolls into the following maturity. The prevailing price of the existing long position is USD 100.00 while the future with the next maturity is trading at USD 90.00. To roll the position, the investor sells their existing long position at USD 100.00 and buys the next maturity at USD 90.00 to make a USD 10.00 profit. If the market were in contango and the prices were USD 90.00 for the front month and USD 100.00 for the following contract, rolling the position would incur a loss of USD 10.00. I started to feel somewhat uncomfortable with this approach while attempting to develop a simple numerical example to further illustrate the concept. As part of my research for this second edition, I first came across a piece by Till (2007) who illustrates the effect with a simple numerical example. However, another reference, Frankfurter and Accomazzo (2010) reconsider Till’s methodology as well as some earlier work by Shimko and Masters (1994). In essence they argue that their calculations reflect a process that cannot be traded in a real-world scenario. They state, ‘We therefore surmise that empirical studies which calculate the roll return . . . (in this way) . . . reflect flawed conclusions”. In their overall conclusion they go on to say, ‘our investigation suggests that the pricing theories we examined have inherent shortcomings when analyzing the commodity futures market. As a result, such models, which are conventionally regarded as validation for persistent and replicable sources of return in the commodity futures markets, may be widely misunderstood’. Another paper, Campbell and Company (2014) add further fuel to the fire and argue, ‘In spite of the importance of roll yield in futures markets and associated investments, misconceptions abound regarding its nature, measurement, and relevance’. They argue that the roll yield is not the result of rolling positions from one contract to another: ‘one of the most pervasive misconceptions is that roll yield represents a realized gain or loss generated on the day of the contract roll, as a long investor sells the expiring contract and buys the new active contract’. Their main assertion is that ‘roll yield represents the net benefit or cost of owning the underlying asset beyond moves in the spot price itself. Therefore, the spot return and roll yield together comprise the total return experienced by an investor (net of financing costs)’. Much of what follows is based on their paper, although the figures have been reworked to make it commodity specific. The underlying commodity used to illustrate the concept will be gold and the values used are hypothetical. It is possible for a commodity investor to buy physical gold as an investment, although there are a number of associated issues that would need to be considered: ▪ ▪ ▪ ▪ ▪

Where will it be stored? Are there any transportation costs involved? How much will it cost to insure? How much will it cost to borrow the money needed to buy the asset? How much could I earn from lending out the gold?

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For these reasons, when the spot price of gold moves this does not reflect the actual return that any investor would earn. However, when tracking the performance of a gold future, these additional costs and benefits should be reflected in the traded price. Recall from Chapter 5, the value of a gold forward or future could be determined by the following relationship: Forward price = Spot price + Financing Rate − Lease Rate

(14.2)

Where the combination of the financing rate and the lease rate is the ‘net carry’. For readers familiar with the fixed income market this is the same concept as positive and negative carry. If a position ‘carries negatively’ it means that the expense of financing a long position is higher than the income earned and so it costs money to hold the position. The forward price will be higher than spot and so the market would be in contango. ‘Positive carry’ is the opposite; the income earned from holding the position is greater than the borrowing expense and so the forward price is lower than spot. The market is therefore in backwardation. Campbell and Company (2014) state the relationship in a similar way as: Futures return = Spot return + excess benefit or cost of owning the underlying asset (14.3) Their main argument is that the conventional definition of roll yield needs to be restated. They define the roll yield as the difference between the futures return and the spot return. Futures return = spot return + roll yield (14.4) Rearranging: Roll yield = futures return − spot return

(14.5)

By rearranging their two formulas, they argue that roll yield ‘is simply the excess benefit or cost of owning the underlying asset’ so in essence this relates to the net carry of the asset. To give a sense of why the conventional description of the roll yield is incorrect, consider the following simplified example (Table 14.1). The aim of this example is to illustrate the difference between a spot return and a futures return using hypothetical values but based broadly on market practice. The underlying asset is gold and prices are expressed in USD/oz. The basis of the calculations is as follows: ▪ The spot price is assumed to increase steadily over a 10-day period by an arbitrary USD 5.00/oz. per day. ▪ The values used to calculate the carry component of the futures calculation are assumed to be 3% p.a. for the financing rate and 1% p.a. for the leasing rate. It is assumed that both term structures are flat, implying that both these rates have been used to calculate each futures price even though they have slightly different maturities.

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TABLE 14.1 Returns from a spot strategy versus a futures strategy. Date Spot price Futures #1 Futures #2 Futures #1 profit Futures #2 profit

1

2

3

4

5

6

7

8

9

10

1000 1005 1010 1015 1020 1025 1030 1035 1040 1045 1000.22 1005.17 1010.11 1015.05 1020 1001.89 1006.84 1011.79 1016.75 1021.70 1026.65 1031.60 1036.55 1041.50 1046.45 4.95 4.94 4.94 4.95

4.95

4.95

4.95

4.95

4.95

▪ Futures #1 is assumed to have an initial residual maturity of 5 days. Although both the spot and futures prices rise, notice that for futures #1 on the maturity date the prices have converged as net carry will be zero. ▪ Futures #2 is assumed to have an initial residual maturity of 35 days. When futures #1 matures, futures #2 will have a month to run until expiry. ▪ All the futures prices are assumed to be the closing prices. All positions are opened and closed at these prices to avoid any complicating profit and loss effect. ▪ Interest on margins is ignored. Let us now compare a ‘spot’ investment with a futures investment over this 10-day horizon. Again, for simplicity the analysis is on a single ounce basis. Spot investment The dollar return from a 10-day spot investment would be the difference between the final price (USD 1,045) and the initial price (USD 1,000), in this case USD 45.00. Recall the earlier point that this increase in value is not actually what the investor would earn as it does not take into account the associated benefits (leasing the gold out) and the costs (borrowing costs) of holding the position. Futures investment The investor goes long futures #1 at a price of USD 1,000.22 and holds the position until shortly before maturity. They decide to roll the exposure the day before expiry to avoid any issues of physical delivery, and do so at the closing price of USD 1,015.05. The profit from this strategy on a per ounce basis would be the sum of the variation margin payments received over the period, which are calculated from the ‘close-to-close’ price. These payments are shown in the fifth line of the table. There is no profit and loss effect for day one, as it is assumed that the position is initially taken out at the closing price. The investor earns three lots of variation margin from futures #1 totaling USD 14.83. When rolling the position on day 4, notice that there is no profit and loss effect from the roll itself. The profit of USD 14.83 from futures #1 is unrelated to the futures #2 contract as it was a function of how the price moved over the first 4-day period. When the futures #2 position is initiated at USD 1,016.75 it is done so at its closing price so

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there is no profit and loss for that contract for that day. The futures #2 position is then held for another 6 days and over this period the investor receives an additional USD 29.70 in variation margin payments. Adding together all the margin payments from both futures positions, the total profit over the 10-day period is USD 44.53. Spot return versus Futures return So, the spot return generates a profit USD 45.00, while the futures strategy underperforms returning USD 44.54. The difference between these two returns is the ‘roll yield’ using the revised definition, which is a negative value of USD 0.46. Notice that the conventional definition of roll yield would have been calculated on day 4 as the sale of futures #1 (USD 1,015.05) minus the purchase of futures #2 (USD 1,016.75) which would return a loss of USD 1.70. If this loss had been subtracted from the spot profit of USD 45.00 it would imply a futures profit of just USD 43.30. However, this approach is clearly incorrect as the futures strategy generated a profit of USD 44.54. This is the core of the argument made by those practitioners who point out that the conventional definition of roll yield as the profit from rolling a futures contract is incorrect and does not reflect market practice. Repeating the exercise for a backwardated market, where the evolution of the spot price is as before, the financing rate is 1% and the lease rate is 3%, the following results are generated: Spot return: Futures return: Roll yield:

USD 45.00 USD 45.47 USD 0.47 (positive value)

So, in this case the futures position has outperformed the spot return. In this example, it was because the benefits (i.e. the lease rate) were greater than the costs (i.e. the borrowing costs). The results shown in this reworked example do conform to the conventional wisdom. In a backwardated market a futures position will outperform a spot position and that in a contango market the futures position will underperform. So how can all the previous information be summarised? ▪ The spot return, calculated as the difference between two spot prices, is not a reflection of the ‘true’ return earned by a ‘long’ investor as it does not take into account the costs and benefits of owning the asset. Arguably it is more of a conceptual return. ▪ The futures price does reflect the net cost and benefits, i.e. the carry benefits. ▪ The act of rolling a long futures position does not in itself generate a profit or loss. ▪ The under- or over-performance of the futures return relative to the spot return is a function of whether the market is in contango or backwardation, respectively. ▪ The profit or loss of the future relative to the spot is down to whether a long physical position carries positively or negatively. Since a future must mimic the

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performance of the underlying, a contango market means that a long position will display negative carry; every day the position is held it will incur a net cost. A backwardated market is beneficial to the long physical position; every day the position is held it will generate more income than expense. ▪ The roll yield is more accurately defined as the futures return minus the spot return. Campbell and Company (2014) suggest a method that links the conventional definition of roll yield with their revised version. The following is a summary and readers requiring the full derivation are referred to their paper. They introduce two concepts into the discussion. Firstly, they discuss the difference between spot and forward prices, which they refer to as the ‘basis’. Secondly they discuss the ‘roll adjustment’, which is the difference between the front and deferred contract prices on the roll date. The starting point is equation 14.5, restated below Roll yield = futures return − spot return

(14.5)

With some manipulation, they argue that over a given period: Roll yield = Basis return + cumulative roll adjustment

(14.6)

This can be illustrated using the figures stated in Table 14.1. ▪ The basis between spot and future on day 1 is USD 0.22 (USD 1,000.22 − USD 1,000) ▪ The basis on the final day of analysis, i.e. day 10 is USD 1.45 (USD 1,046.45 − USD 1,045.00) ▪ The basis return is therefore USD 1.23 (USD 1.45 − USD 0.22) ▪ The roll adjustment is calculated using the futures values on the day the position is rolled (day 4). It is the difference between the price of future 1 (USD 1,015.05) and futures 2 (USD 1,106.75) and equals −USD 1.70. This is the conventional way of measuring roll yield and it was noted earlier that if it were applied as per the conventional understanding it would not return an accurate profit or loss based on actual trading activity. ▪ Based on equation 14.6 the revised method of calculating roll yield is 1.23 + (−1.70) = −0.47. This is the same as the futures return (USD 44.53) minus the spot return (USD 45.00). As a side note, if the analysis were covering multiple roll periods, this cumulative value of the roll adjustment would be needed. But how does this help our understanding? The Campbell paper argues, ‘Since the basis is bounded by the shape of the term structure, the basis return will also be bounded. Thus, over long periods of time the cumulative roll adjustment will dominate.’ From this they argue that the roll yield is approximately equal to the cumulative roll yield. This means that the conventional understanding that roll yield works against a long futures position when the market is in contango and in favour of the long futures position when the market is backwardated still holds, even though the conventional understanding of roll yield on which it is based is flawed.

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14.6

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

TOTAL RETURN SWAPS

With a total return swap (TRS) the investor will receive a cash flow that takes its value from the movement of a particular index. In return, a variable cash flow will be paid that could be referenced to a variety of sources. If an investor wishes to express a bullish view on the commodity market, they will receive the index return. On the other hand, if the investor wished to express a bearish view on the market, they would pay the index return. One of the features of a TRS is that the instrument does not require an initial outlay of cash. An instrument that does not require an upfront investment is sometimes referred to as being ‘unfunded’. However, for investors who cannot enter these types of product, as technically they represent a situation of infinite leverage, they are often redesigned as bond-like structures where the client is required to make an initial investment. In this case it would be termed a ‘funded’ structure and may perhaps be referred to as a ‘note’.

Sample term sheet The following terms would be typical of a total return swap referenced to the S&P GSCI commodity index.

Notional quantity × (

Maturity: Commodity index: Notional quantity: Index amount payer: Calculation period: Index amount:

Indexm − Indexm−1 − fee) Indexstart

One year S&P GSCI total return index USD 100 million Bank Monthly On each monthly payment date the index amount payer shall pay an amount calculated in accordance with the following formula: If the index amount is a negative amount, then the floating amount payer shall pay to the index amount payer the absolute value of the negative amount. For the purposes of settlement ‘m’ means the applicable index reset date in each calculation period, which is defined as the first trading day of each calendar month. ‘Indexm ’ means the closing settlement price of the Index for the applicable index reset date. ‘Indexm-1 ’ means the closing settlement price of the Index for the immediately preceding index reset date.

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Floating payer: Floating amount:

‘Indexstart ’ means 2922.42 ‘Fee’ means 0.25% per annum (actual/365 basis) of the notional amount, calculated over the actual number of calendar days in each calculation period. The client On each monthly payment date the floating amount payer shall pay an amount calculated in accordance with the following formula: ( ) ) −1 ∏( 91 Rd 91 − 1] 1− ANQ × [ d

360

Where ANQ means the ‘adjusted notional quantity’ determined by the following expression: Notional quantity × (

Indexm−1 Indexstart

)

‘Rd ’ means the T-Bill Auction High Rate for day d. ‘d’ means each calendar day in the applicable calculation period. ‘T-Bill Auction High Rate’ on a particular day means the auction high rate for three-month US Treasury Bills published on the most recent auction date prior to that day.

Settlement of cash flows To illustrate the mechanics of the product, consider the following example, which will be assumed to be the first period covering 31 days. We will assume that the index at the end of the month is 2,955.33. The cash flow referenced to the index is calculated as the percentage change in its value less the agreed fee. The percentage increase in the index equates to a monetary payment of USD 2,252,243. This is calculated as USD 200,000,000 × [(2,955.33 − 2,922.42)∕2,922.42]. The agreed fee is 0.25% of the notional amount, which is equal to USD 42,465.75 (USD 200 million × 0.25%× 31∕365). For ease of illustration let us assume that throughout the period the yield on the US Treasury Bills was 0.5%, which returns a floating payment equal to USD 86,184. 31

−1 ⎡⎛ ⎤ 91 ⎞ 91 USD 200 million × ⎢⎜(1 − × 0.5%) ⎟ − 1⎥ = 86,184 ⎢ ⎥ 360 ⎠ ⎣⎝ ⎦

480

COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS Index total return

Investor

Futures profit/loss

Futures markets

Bank Fee T-bill interest

Futures hedge

FIGURE 14.5 Total return swap.

Where the payment dates for the two legs coincide the market, convention is to settle a net amount. The net amount payable to the client at the end of this period is therefore USD 2,123,593.25. This is calculated as: Index amount: Less floating amount: Less fee: Equals:

USD 2,252,243 USD 86,184 USD 42,465.75 USD 2,123,593.25

Diagrammatically the total return swap is shown in Figure 14.5. In the next period the cash flows will be calculated in a similar manner. Payments due under the floating side of the swap, however, will now be calculated on a different notional amount (‘the adjusted notional quantity’). The notional amount is adjusted up or down by the change in the index relative to its original value. So, the value for the second period would be USD 202,252,243 (USD 200,000,000 × 2,955.33/2,922.42). The rationale for adjusting the notional amount in this manner is to replicate the profits or losses that would be incurred if the investor had bought the underlying commodities. The bank will hedge their exposure by entering a series of futures trades to replicate the return on the index. This is done by buying the relevant commodity futures in the proportion specified by the current weightings of the index. The total return swap incurs a cost of 0.25% to the client that in effect covers any hedging costs as well as providing a return. The structure is not without risk to the client. A client who is receiving the index leg is exposed to a decline in its value and is also exposed to the credit risk of the structuring bank. Typically, the structure is unsecured and so if the structuring bank were to default, the investor would no longer receive their cash flows. There are several different ways in which the deal could be structured: ▪ The swap could structure a sub-index (e.g. industrial metals). ▪ The swap could be in zero-coupon form with only one set of cash flows being paid at maturity. ▪ Another alternative would be to link the index cashflows to the excess return component of the S&P GSCI with the client only paying the hedge management fees.

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Commodity Investing

14.7

EXCHANGE TRADED PRODUCTS (ETPS)

In Section 14.1 ETPs were defined as a security that trades on a stock exchange and references either a single commodity (e.g. gold) or a basket of commodities (e.g. a certain commodity index). ETPs break down into three main types. An exchange traded commodity (ETC) is where the security is backed by a physical holding in the underlying commodity. An exchange traded fund (ETF) is where the return generated by the security is achieved using derivatives such as futures and swaps. Given the way in which ETCs and ETFs are designed it is unlikely that the issuer will default as they are structured to be bankruptcy remote. An exchange traded note (ETN) is like an ETF in the way that it generates returns except it represents the debt of a non-bankruptcy remote issuer. Although regulations and structures will inevitably differ between regions and providers, the following examples are designed to convey the key principles.

14.7.1

Exchange traded commodities

Gold Bullion Securities was issued originally in 2004 and has the following features: Issuer: Currency: Currency Hedged: Management fee: Domicile: Replication method: Assets: Trustee: Gold custodian: Vault location: Legal form:

Gold Bullion Securities USD No 0.40% Jersey Physically backed by bullion Physically backed by allocated metal subject to LBMA good delivery rules Law Debenture Trust Corporation, PLC HSBC Bank, PLC London Debt security

This ETC was issued in the form of an undated debt security, fully secured by physical gold. The aim was to offer investors the opportunity to invest in gold without the need for buying and holding the physical metal. It is a more direct way of investing in the metal rather than, say, investing in the shares of a gold producer, which would give rise to a series of non-gold related risks. The issuing company (Gold Bullion Securities) is a public limited company (PLC) structured as a special purpose vehicle (SPV). Gorton and Souleles (2007) highlight some of the more common characteristics of an SPV: ▪ It is a legal entity set up by another firm to carry out some specific purpose. Typically, they have no other purpose other than the transaction for which they were created. ▪ The rules governing their operation are set down in advance and specify the nature of their activities.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

▪ It has no employees and no physical location (although they will have a registered address). ▪ The legal form of the SPV can vary and could include a limited partnership, a limited liability company, a trust, or a corporation. ▪ They are structured in such a way that as a practical matter they cannot become bankrupt. Indeed, Gorton and Souleles describe them as ‘essentially robot firms’. As a result, any required management and administration services are outsourced to a third party entity. GBS is owned by a holding company (i.e. a company that is set up to own other companies), which in turn is owned by WisdomTree Investments Inc. It is quite common to set up such companies in an attractive tax location such as Jersey as it minimises the amount of tax that is payable by the corporation on its activities. This in turn will be beneficial to the end investor. When buying or selling any form of ETP, an investor is buying or selling a security issued by a legal entity of some form, but the return on the instrument should predominantly reflect the value of the underlying, which in this case is physical gold. To facilitate the issuance and trading of the securities, the issuing company usually appoints several financial market participants (e.g. BNP Paribas) who are referred to as ‘approved participants’ (AP). To take delivery of any newly created securities the AP must forward an agreed sum of money to the issuer, who will then use the proceeds to buy the required physical gold. In return for the cash payment, the APs are issued with new securities, which can then be traded either on an organised exchange or on an OTC basis. Another responsibility associated with the approved participants is that they act as a market maker for the security ensuring that investors can readily trade the asset. The gold is deposited in a vault owned by HSBC. The trustee legally owns the physical gold, which is an independent company whose role is to act in the best interests of the end investor. If an investor wishes to subsequently sell their holding, they could simply dispose of the asset on the relevant exchange where the security is listed (e.g. London Stock Exchange). Another possibility is that investors can also exchange their securities for the physical gold using a redemption process, which is essentially the opposite of the creation process noted above. The security is denominated in the same currency as the underlying commodity, so a non-USD investor has an exposure not only to the price of gold but also to the exchange rate. One of the more involved concepts associated with such a structure are the fees associated with the product. In addition to any stockbroker-dealing fee that may be charged, the product incurs additional fees. According to the prospectus: ‘Each Gold Bullion Security has an effective entitlement to physical gold and that Per Security Entitlement to gold reduces every day to reflect the accrual of the fees payable in respect of that Gold Bullion Security . . . most security holders will buy and sell their Gold Bullion Securities on a stock exchange in return for cash. The cash value at which (they) will trade on exchange is expected to be close to the value of the per security entitlement to gold’. Suppose an investor bought four thousand securities on the first day of issue (1 July 2005), when the price of gold was USD 427.30/oz. According to the prospectus on that

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Commodity Investing

day each individual security carried an entitlement to gold of 99.550959% of one tenth of an ounce. So, one tenth of an ounce would be worth USD 42.73 but the investor would only pay USD 42.54 for each security and therefore USD 170,160 for their entire holding. Assuming no other transactions on that day the amount of gold required to support this position would be about equal to a London good delivery bar, which is 400 troy ounces. Suppose that on an intra-day basis the gold price increased. The value of their security would also increase given that the per security entitlement is unchanged. Equally an intra-day fall in the gold price will lower the value of the security. Now consider just the impact of time on the value of the security if the price of gold does not change. The following day, the per security entitlement will decrease by the equivalent of the annual 0.4% fee. So, the following day the entitlement would be: 99.550959% − 0.40%∕365 = 99.549863% Although the amount of physical gold held in the vault would remain unchanged, the investor’s entitlement to this would slowly decrease over time. In essence, the issuers are paying themselves in gold rather than extracting a supplemental cash fee from the investor. At the time of writing in mid-2020, the spot gold price was USD 1,7202.21, the per security entitlement was 93.599% returning a value for each security of USD 161.01.

14.7.2

Exchange traded fund

The ‘Gold 2 X Daily Leveraged’ is an ETF that was originally issued in 2008 and has the following features: Issuer: Currency: Currency Hedged: Management fee: Domicile: Replication method: Reference index: Trustee: Collateral administrator Legal form:

WisdomTree Commodity Securities Limited USD No 0.98% Jersey Synthetic – fully funded collateralised swap Bloomberg Commodity Index TM – Gold Subindex Total Return Law Debenture Trust Corporation, PLC Bank of New York Mellon Debt security

This ETF is also part of the WisdomTree investment universe and shares some similarities with the ETC analysed in Section 14.7.1. Namely: ▪ ▪ ▪ ▪ ▪

The issuer is an SPV and is incorporated in Jersey. The administration and management of the issuer is outsourced to a third party. The security is in the form of debt. The security is denominated in USD and any currency exposure is not hedged. The security can be traded on an exchange or on an over-the-counter basis.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

Instead of referencing the spot price of gold like the ETC, this ETF references a sub-index of the Bloomberg Commodity Index TM. This index references the value of a gold future quoted on the CME. Therefore, the issues noted in Section 14.5 on index investing and the difference between spot and futures returns is relevant in this context. The next key difference is the way in which the value of the security is generated. In this structure there is no physical holding and so the value of the security is derived from a portfolio of derivatives. Different ETF structures will use different types of derivative. Since this structure takes its value from a future, it would be possible to construct a fund comprising of futures. However, according to the prospectus, this transaction uses a ‘fully funded collateralised swap’. Although the structure is somewhat complex a simplified version is shown in Figure 14.6. Like the ETC, (1) the issuer agrees with the approved participant (AP) to create new securities. In this instance the securities are assumed to have a total value of USD 100,000. (2) The AP sells the securities to an investor either via an exchange or over the counter. (3) In return the investor delivers the requisite amount of cash. (4) This cash is forwarded to the derivative counterparty who deposits the money (5) into a collateral account managed by a third party. (6) These monies are used to support a derivative contract (in this case a total return swap) with a notional twice that of the investment, which is entered into between the issuer and the derivative counterparty. It is this derivative that will generate the required percentage return of the underlying asset. The existence of the swap transaction with the derivative counterparty gives rise to counterparty credit risk. This is mitigated by the existence of the collateral account maintained at the third party. Recall that credit risk only exists on money due to a derivative counterparty and so if the price of gold evolves in such a way that the market value of the swap increases in favour of the ETF issuer, the derivatives counterparty will be

Management company

Trustee

Trust deed

Investor 2 $100,000 securities

1 $100,000 securities created

Management contract

ETF issuer 6 Derivative contract

3 $100,000 cash

Collateral account

5 $100,000 cash Authorised participant

4 $100,000 cash

FIGURE 14.6 Structure of ETF using synthetic replication.

Derivative counterparty

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Commodity Investing

required to deposit additional collateral. Under the terms of the agreement, a default by the derivative counterparty would allow the issuer to take control of the collateral and sell it to recoup any losses. However, if these proceeds are less than the amount owed to the ETF investors, they will not be repaid in full. Given the importance of this account to the structure, there are controls in place that will govern the type of eligible collateral that can be held. There is an additional risk in that the derivative counterparty can terminate the swap ‘if for any reason it is unable to maintain (its) hedging position. This problem arose in May 2020 when WisdomTree had to terminate several oil ETFs when a swap counterparty exercised this right to terminate their swaps after crude oil prices turned negative for a short period. The valuation of this ETF security is based on the following formula: Price of security at time ‘t’ = Price of security at time ‘t − 1’ × [1 + (capital adjustment + (leverage factor × % change in the reference commodity index))] The capital adjustment value reflects several the transaction’s components: ▪ ▪ ▪ ▪

An interest return on the value of the associated collateral. Fees payable to the issuer and their management company (0.98% p.a.). Fees payable to the commodity counterparty (1.3% p.a. in this transaction). Fees payable to the provider of the reference index (0.05% p.a.).

Notice that like the ETC, these fees are separate from any transaction fees charged by the investor’s broker. To illustrate how the security takes its value, consider the following example. ▪ ▪ ▪ ▪

The initial value of the security is taken to be USD 50.00. The reference index increases by 5%. The value of the capital adjustment is −0.0001. The leverage factor is 2. The value of the security will be: = USD 50.00 × [1 + (−0.0001 + (2 × 0.05))] = USD 50.00 × 1.0999 = USD 54.995

Note that a 5% increase in the underlying index has resulted in a 10% increase in the value of the security (less the capital adjustment components). The formula also illustrates that once the price of index has fallen by 50% the value of the investor’s security will be zero and the investor’s initial investment will be lost. In this transaction the losses cannot exceed the initial investment.

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14.7.3

Exchange traded note (ETN)

Consider the following term sheet: Issuer: Currency: Currency Hedged: Issue size: Issue date: Maturity: Principal amount per ETN Listing: Reference index: Index return: Legal form: Interest payments: Principal protection: Issuer call: Investor put:

Barclays Bank, PLC USD No USD 200,000,000 October 2019 October 2049 USD 25.00 NYSE Arca Barclays Gold Three-month index Total return Unsecured debt security; a liability of the issuer. None None, investor can lose up to their entire investment. Yes Yes

The key features of the note are as follows: ▪ The amount issued is fixed whereas with the ETC and ETF considered earlier, the creation and redemption process will mean that the amount outstanding could vary over time. ▪ This note represents a direct liability of Barclays Bank and so the investor is taking credit risk on the issuer in addition to the market risk associated with the investment’s return. ▪ The return on the note is based on a commodity index designed by Barclays, which takes it value from gold futures ‘that will become the first liquid nearby futures contracts three months in the future’. This futures contract will be rolled to ensure that the exposure to the underlying future is maintained. ▪ The investor also earns a return that corresponds to the weekly-announced interest rate for three-month US Treasury Bills. ▪ The note is traded on a regulated exchange and so in theory the instrument could be bought and sold throughout its lifetime on a secondary market basis. There is no guarantee however, that there will be sufficient liquidity at any single point in time. ▪ Although the note was issued at USD 25.00 its value will change every day. Its daily value is: Previous day’s value × daily index factor ▪ The daily index factor is calculated as: The closing level of the current day’s reference index divided by the closing level of the previous day’s index

Commodity Investing

487

To illustrate how the investment may perform, suppose that in the first year the index increases by 5%. The value of the security at the end of the period would be USD 26.25. If the index in the second year were to increase by 2% then the value of the security would increase to USD 26.775 (i.e. 2% on USD 26.25). However, since the instrument is traded on an organised market the actual price paid may differ from these calculated values. This could be due to an imbalance between demand and supply, which may impact liquidity or perhaps a credit ratings downgrade of the issuer which might bring into question their ability to repay their debts. ▪ If the note is held to maturity, then on the final redemption date the investor will receive from the issuer whatever the daily value is on that date. ▪ The bond allows the issuer to redeem the note early (‘issuer call’) as well as an early redemption feature for the investor (‘investor put’).

14.8

STRUCTURED PRODUCTS

What is a structured product? Although there is no standard definition, it can be thought of as a product whose risk-return profile could not be easily replicated by the end investor. They can be structured with several different characteristics: ▪ Increased upside participation – depending on the underlying commodity and prevailing market conditions it may be possible to offer the investor an upside return in excess of 100%; so if the underlying commodity were to increase by USD 1.00, the investor would, say, earn a profit of USD 1.50 − a participation rate of 150%. ▪ Reduced downside exposure – the notes could be structured to offer: ▪ Full capital protection, ▪ Some limited downside risk, or, ▪ Losses that start to accrue once a particular price level trades. ▪ Expressing a bearish view – one of the characteristics of many (but not all) physical commodity markets is the inability to express a negative view on price movements by ‘short selling’ the product in the same way as equities. Structured products could offer a way for investors to achieve this objective. In the very early days structured products could be engineered by adding together different components to yield a result. However, a significant proportion of current offerings are constructed using a modeling approach. So, although some components of a product are recognizable it is not always possible to reverse engineer the structure.

14.8.1

Capital protected notes

The most basic form of structured product usually consists of two components: a zero-coupon bond and some form of embedded optionality. Like the ETN discussed in Section 14.7.3 the zero-coupon bond will represent the liability of the product issuer so the end investor will have some form of counterparty credit risk.

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COMMODITY DERIVATIVES: MARKETS AND APPLICATIONS

The classic structured product will offer the investor some form of capital protection. It is important to note that this is not a guarantee mainly because of the counterparty risk. The investor will pay a certain amount of money to the issuer who will split the proceeds into two parts. One part of the proceeds will be used to buy a zero-coupon bond (ZCB). This ZCB will cost less than 100% of the investment proceeds as they are issued at a discount and will gradually accrete to their par value over the life of the investment. It is the ZCB component that ensures the investor’s capital is protected. The balance of the proceeds is used to buy a call option on the underlying asset. Take for example a five-year note linked to the spot price of gold. The return to the investor at maturity is expressed as: Notional × [100% + Participation rate × max (0%, GoldFinal )] where: ( ) Goldfinal = Pfinal − Pinitial − 1 Pinitial = Spot price of gold at inception Pfinal = Spot price of gold at maturity. This means that the investor will at least have his capital returned at maturity, plus a fixed percentage (the participation rate) of any increase in the underlying commodity. If gold falls below its initial value, the investor will have the initial value of his investment returned. The constituent parts of the structure and the end payoff are shown in Figure 14.7. The note is constructed as follows. Let us say that the minimum investment is USD 100,000. The structuring institution deposits a sum of money today that will, on maturity, repay the initial investment. If we assume that a five-year, zero-coupon investment yields 5% p.a., the amount deposited today to earn USD 100,000 in five years is USD 78,353 (100,000/(1.05)5 ). The balance of the proceeds (USD 21,647) is then used to buy a call option that will generate the upside return.

Option profit / loss

Zero-coupon profit / loss

Redemption payout

100% 100%

Commodity performance 100%

Commodity 100% performance 100%

100%

Commodity performance

FIGURE 14.7 Construction and payoff of capital protected note. Left-hand panel is a long ATM call option; middle panel is the return from a zero-coupon investment; right-hand panel is the net payoff at maturity. For comparison purposes the hashed line represents the profit and loss from a long position in the underlying commodity entered at the current price.

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489

Let us assume that gold is initially trading at a spot price of USD 1,500/oz. and a five-year call option on the commodity is priced at USD 433.00. The parameters used to value the option were: ▪ Implied volatility of 25% ▪ Interest rates of 5% ▪ A lease rate of 1% Expressing the option in this manner implies a notional amount of USD 1,500 but the structured product pays out on a larger notional of USD 100,000 and so the premium needs to be scaled accordingly. A useful technique in this respect is to express the premium as a percentage of the strike rate. This returns a value of 28.87%, (433/1,500), which represents the percentage cost of the initial investment of an option whose payout is equal to 100% of any increase in the underlying. Applied to the investment notional of USD 100,000 this returns an option cost of USD 28,870. Since the investor has USD 21,647 available to buy call options, this allows them to earn 75% (the participation rate) of the appreciation of gold over the period (USD 21,647/USD 28,870). To illustrate the ‘at maturity’ pay off consider the following three scenarios: ▪ Gold price increases by 10% to USD 1,650. The note will pay the client USD 107,500 [100,000 × (100% + (75% × 10%))]; 75% of the 10% price increase. ▪ Gold price is unchanged. The note will pay the client USD 100,000. ▪ Gold price falls by 10% to USD 1,350. The note will pay the client USD 100,000 From this analysis, it follows that the main determinants of the participation rate are zero-coupon rates and implied volatility. If zero-coupon interest rates are high, the present value of the amount required to generate the principal will be lower, releasing more funds to buy call options. The options will also incur a lower cost if implied volatility is low.

14.8.2

Structuring considerations

There are several techniques that the structurer could use to improve this participation rate (see Schofield, 2017 for a more detailed discussion). The structurer could: ▪ Alter the initial level from which the note return is measured – this could be set higher than the current market price meaning the call option would be struck slightly out-of-the-money. ▪ Increase the maturity of the transaction – although the cost of option increases, the zero-coupon component declines by a greater amount increasing the participation rate. ▪ Change the degree of capital protection – this will reduce the cost of the option. ▪ Pick a commodity with a lower implied volatility – this will also reduce the cost of the option. ▪ Cap the investor upside – this could be done by either incorporating some type of barrier option or requiring the investor to sell OTM optionality.

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▪ Remove the capital protection at low strike rates. ▪ Change the nature of the embedded optionality – perhaps from a European-style option to an Asian-style payoff or an option that is correlation dependent. These options will have lower premiums than the European equivalent. ▪ Sell the note above par – this increases the proceeds available to the issuer. There are a few characteristics unique to commodities that allow a structurer to create products with risk-return features different to those of traditional financial assets. Shape of the forward curve – in the previous example of gold; the five-year option was valued at USD 433.00. If the option is assumed to be European in style, then the relative ‘moneyness’ is determined by the position of the strike in relation to the five-year forward rather than the current spot rate. So, although the call option would be ATM in relation to the spot price, it is deeply in-the-money relative to the forward price, which would be USD 1,832. This was because the market was in contango based on the relationship between interest rates and lease rates. Had the opposite situation applied (interest rates at 1%, lease rates at 5%), then the implied forward price would have been USD 1,228 making the option OTM and pushing the premium down to USD 174.00. Reworking the participation rate for our simple gold note would return a value of 187%! Note that the investor’s payout at maturity is based on the final spot price. Term structure of implied volatility – for conventional financial assets such as equities, the term structure of implied volatility increases with respect to maturity. However, for commodities, it is common that the term structure of volatility is downward sloping reflecting greater uncertainty associated with shorter maturities. This will mean that the participation rate for those commodities that display this inverted volatility term structure will be greater than those that display a positively sloped curve. Implied correlation – one of the motivations for investing in commodities is that the asset class offers portfolio diversification by virtue of low or negative correlation with other financial asset classes. However, within the asset class, intra-commodity can also be very low. For example, there is no fundamental reason why the price of gold and crude oil should display any relationship, as they are different products, with different supply chains and different end users.

14.8.3

Basket notes

The low correlation between different commodities allows structurers to create products that are based on a variety of commodity baskets. Consider the following term sheet: Tenor: Currency: Commodity basket: Annual coupon: Redemption payout: Participation rate:

Four years USD Equally weighted basket of: WTI and Cocoa None 100% + Participation rate * Max (0%, Basket value at maturity − 1) 100%

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Basket options were introduced in chapter 5 so the analysis here is somewhat high level to avoid repetition. The embedded option is a basket call with the following at-maturity value: ∑ pricek final (Wk × ( )) pricek initial Where: Wk = the weight of commodity (k) in the basket Pk initial = the initial price of commodity k Pk final = the final price of commodity k Buying basket options results in a ‘long correlation’ exposure for the buyer. Phrased another way, if the two options display negative correlation, the initial premium will be lower, allowing the structurer to offer a higher participation rate. To illustrate how the product works, consider the following scenarios illustrated in Table 14.2: ▪ The initial price of WTI and Cocoa are assumed to be USD 50.00/bbl. and USD 2,400 per metric ton. ▪ The basket is equally weighted. ▪ Scenario #1: in this case both asset prices rise and so the value of the basket shows an increase of 22%. At maturity, the bond pays out 100% of this increase. ▪ Scenario #2: both prices fall and so the value of the basket declines by about 12%. The capital protected element of the bond ensures the investor is repaid 100% of the principal. ▪ Scenario #3: oil increases, while cocoa falls, which suggests negative correlation. However, the basket still has a positive value at maturity, which earns the investor an 18% return. Although both scenarios #1 and #2 are examples of positive correlation, it is in one of these (scenario #1) that the investor earns the highest returns. In this example, only two commodities were included in the basket, but it is quite common for these structures to have 4–6 different reference assets. TABLE 14.2 Various scenarios to illustrate payout of basket option note.

WTI Cocoa Basket value at maturity Redemption payout (rounded)

Scenario #1 – both prices rise

Scenario #2 – both prices fall

Scenario #3 – prices diverge

70 2500 1.2208 122%

40 2300 0.87917 100%

70 2300 1.17916 118%

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14.8.4

Income structures

One of the issues faced by investors since the financial crisis of 2008 has been the low yield offered by traditional savings products because of low interest rates. As a result, structures that offer either regular income or some form of enhanced yield have proved to be popular. The following is a hypothetical term sheet for an income related structure: Tenor: Currency: Reference index: Annual coupon:

Redemption amount:

Three years USD Baltic Dry Index Every year, the note will payout to the investor according to the following formula: Max (0%, Min (5%, ((BDI at end of year ‘t’ / Initial strike level of BDI) − 1)) 100%

Figure 14.8 illustrates the different components of the transaction and the final payoff. The key characteristics of the structure are as follows: ▪ The note offers capital protection as the investor’s initial proceeds are placed into a zero-coupon deposit, which grows to repay par at maturity. The balance of the proceeds is used to fund the purchase of the option component. ▪ The option component of the transaction is an embedded ‘bull spread’ constructed using call options. This option position is sometimes referred to as a ‘call spread’ and was introduced in Chapter 5. This is a debit strategy, which consists of being long an ATM call (here struck at 100% of the initial index value) and short an OTM call (here struck at 105% of the initial index value). ▪ There are three bull spreads embedded in the structure each with a one-year maturity and identical strike rates based on the initial levels of the index.

Option profit / loss

Zero-coupon profit / loss

Option profit / loss

Commodity 100% performance

100% 100%

Commodity performance

Commodity 100% performance 100%

100%

105%

FIGURE 14.8 Baltic Dry Index note. Left-hand panel is a bull spread. Middle panel is the return from a zero-coupon investment. Right-hand panel is the net of the deal components. For comparison purposes the hashed line represents the profit and loss from a long position in the underlying commodity entered at the current price.

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▪ If the value of the index falls below its initial level, the note will not pay out to the investor. If the note increases by 5%, the combined impact of the long and short option positions will limit the investor payout. For example, if the initial value of the index was, say, 100 and it increased by 10% at the end of the first year, the long call struck at 100 pays out 10% to the investor but the short call requires the investor to payout 5%; the net effect is that the investor cannot earn more than the difference between the two strikes. If the index settles between the two strikes, only the long call option will pay out as the short call is not exercised.

14.8.5

Reverse convertible

Yield-enhanced structures are related to income structures and some may argue the difference is minimal. Income structures are perhaps more bond like in nature where they may offer a regular cash flow to the investor whereas yield-enhanced structures offer a return that is more likely to be paid at a single point in time and may also carry some degree of market risk. One popular structure that illustrates yield enhancement is the ‘reverse convertible’. A conventional convertible bond is an equity-linked instrument, where a borrower issues a bond that allows the holder to convert the instrument into the borrower’s equity. At a very simple level, the investor is essentially long a bond and long an equity call option. As a starting point for the analysis, a reverse convertible can be thought of from the investors’ perspective as comprising a long bond position combined with a short a put option on the underlying commodity. Recall that a short put position if exercised will leave the investor with a long position in the underlying. The following term sheet illustrates the principles: Maturity: Currency: Underlying commodity: Coupon: Barrier: Redemption proceeds:

12 months USD Crude oil 8%, payable at maturity 80% of initial crude oil price If the barrier has never been breached then the note pays 100% of investment plus coupon If the barrier has been breached then the note pays 100% + coupon − MAX (0%, P (final) / P (initial) − 1)

Where: P (final) = price of crude oil at maturity P (initial) = initial price of crude Diagrammatically, the at maturity pay off will look as shown in Figure 14.9. The key characteristics of this product are: ▪ The structure is cash-settled to avoid issues with physical delivery. ▪ The product is typically short-term in nature.

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80%

Commodity performance

100% 100%

FIGURE 14.9 Reverse convertible. For comparison purposes the hashed line represents the profit and loss from a long position in the underlying commodity entered into at the current price. ▪ The investor is long an interest-bearing deposit rather than a zero-coupon deposit and is short a ‘down and in’ barrier option that has a strike equal to 100% of the initial commodity price and a barrier set at 80%. The barrier option is monitored on an ongoing basis. ▪ It is the sale of the barrier option combined with interest earned on the deposit that generates the investor’s return. ▪ In one sense the barrier option offers the investor greater protection than a short vanilla put. The vanilla put would become a drag on the investor’s return as soon as the price of the commodity falls below 100%. Here, the investor’s coupon is fully protected until the commodity has breached the barrier. ▪ If the structure contains a barrier option, then the enhanced return earned by the investor will be lower than the conventional vanilla put option. This is because the premium on the barrier is lower than a European equivalent.

14.8.6

Autocallable structures

Another popular structure that offers an enhanced return is an autocallable. Although a single definition of an autocallable is tricky, it is perhaps best described by its characteristics. Consider the following ‘worst of’ autocallable term sheet: Maturity: Currency: Underlying assets: Knock in barrier level:

Six months USD ICE Brent futures & LBMA silver price 85% of the initial prices of both underlying assets

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Early redemption:

Coupon payments: Coupon calculation:

Redemption at maturity:

The note will be redeemed at par if after three months both underlying assets are greater than 100% of their initial value. Three months and six months Unless the note has already been redeemed the investor will receive a coupon of: Principal invested × N × 3% Where N is the number of underlying assets whose price is greater than 100% of their spot value. Unless the note has already been redeemed, the investor will receive: 1. If the final price of the worst performing asset closes at or above the 85% knock in barrier level: Principal invested × 100% 2. If the final price of the worst performing asset closes below the 85% knock-in barrier level: Principal invested × (final price of worst performing asset/initial price of worst performing asset)

The key characteristics are: ▪ The instrument is relatively short term in nature. ▪ The investor is paid an enhanced coupon (assume here that the general level of interest rates was less than the annual 3% coupon). ▪ The second coupon is not guaranteed and will not be paid if the note terminates early. ▪ Although directional autocallables have been seen, they were initially designed to perform well in neutral or bearish market conditions. ▪ They offer some degree of capital protection. Autocallables are an excellent example of how it can be tricky to reverse engineer the structure into a series of individual components, as the investor’s return will usually be modeled. However, there are some general structuring principles that can be observed. ▪ From the investors’ perspective the coupon payments are structured as a series of long digital options. However, the second digital will be knocked out if the note is redeemed at the three-month point. ▪ The investor finances the purchase of these digital options through the sale of a ‘down and in’ put option with a barrier set at 85% of the initial price. This places the investor’s principal at risk below this level. However, note that the barrier option will only be activated when one of the assets hits the 85% threshold. This is termed a ‘worst of’ structure, which is considered in a little more detail in Section 14.8.8. ▪ The early redemption feature is structured as an ‘up and out’ put option. This put has a strike of 0% and a knockout barrier of 100%. If knocked out the structure

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rebates 100% of its value to finance the investor repayment. If the put option is structured with a 0% strike it will never have to payout (assuming prices do not turn negative!), which would suggest it has no value. However, since it offers a rebate this needs to be paid for and so some premium is payable. The investor is long the option, and so this is also financed by the short ‘down and in’ put mentioned in the last point.

14.8.7

Outperformance note

Consider the following outperformance note, which is based on the belief that gold will outperform oil over a five-year period. Maturity: Currency: Reference commodities: Redemption payment:

Five years USD WTI crude oil and Gold 100% of the amount invested + 300% × MAX (oil return − gold return, 0) Oil return = Oil (final)/Oil (initial) Gold return = Gold (final)/Gold (initial) Oil (initial), Gold (initial) = price of WTI and gold respectively at issue date Oil (final), Gold (final) = price of WTI and gold respectively on valuation date

To illustrate the possible payoffs at maturity, consider the following scenarios (Table 14.3). We will assume that: ▪ The initial price of WTI is USD 50.00/bbl. ▪ The initial price of Gold is USD 1,500/oz. Scenario #1 In this case, oil has increased by 40% and gold has increased by 3% and so the relative outperformance of WTI relative to the precious metal was 37%. The investor receives TABLE 14.3 Potential payouts from an outperformance note.

WTI Gold Oil return Gold return Redemption payout

Scenario #1 – both prices rise

Scenario #2 – both prices fall

Scenario #3 – prices diverge

70 1,550 1.40 1.03 211%

45 1,300 0.90 0.87 109%

40 1,550 0.80 1.03 100%

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Commodity Investing

three times this outperformance (111%), which is added onto the initial amount invested so that the investor receives 211% of their principal. Scenario #2 Although both prices have fallen, note that oil has fallen less than gold and as such is deemed to have outperformed. Here the investor will also receive more than just their initial investment earning a payout of 109%. Scenario #3 In this case gold has outperformed WTI and so the note returns only the initial principal to the investor.

14.8.8

‘Worst of’ structures

These types of options can also be thought of as an outperformance structure, as it allows the investor to express a view on the relative performance of two or more assets in a particular direction. The following example is a ‘worst of’ call structure. In this structure the investor is long a call on the worst performing asset in the basket. To illustrate this, consider the following structure: Maturity: Currency: Underlying commodities: Option type: Redemption at maturity: Strike: Worst (final): Worst (initial):

Three years USD Coal and Baltic Dry Index (BDI) ‘Worst of’ call option 100% + MAX (0%, Worst (final) / Worst (initial) − Strike) 100% of initial price of either commodity Price of the worst performing commodity at maturity Initial price of the worst performing commodity

Again, a simple numerical example helps illustrate the main principles (Table 14.4). The following table considers four different scenarios and details the percentage change in both assets over the period.

TABLE 14.4 ‘Worst of’ call option outcome scenarios.’

Scenario #1 Scenario #2 Scenario #3 Scenario #4

Coal

BDI

+10% +10% −10% −10%

+5% −5% 5% −5%

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▪ Scenario #1: both prices increase but the BDI increases by the least and so is the worst performing asset. It has increased by 5% over its original strike price and so the note pays out 105% ▪ Scenario #2: coal increases, BDI decreases. Again, the BDI is the worst performing asset, but because its price has fallen below its initial strike, the call option does not pay out, so the note redeems at 100% of the principal. ▪ Scenario #3: coal decreases, BDI increases. This is a similar situation to scenario #2. The note will pay out only the initial principal of 100%. ▪ Scenario #4: both coal and the BDI decrease. The embedded option will only payout if both assets perform positively and then only in relation to the worse performing asset. The investor receives back 100% of principal. From these scenarios we can see that for the note to pay out, the investor must be bullish on both assets and expects them to perform positively albeit the performance of one to be worse than the other.

Glossary

AAU Assigned amount units. Under the terms of the Kyoto agreement, an AAU allows the holder the right to emit 1 tonne of carbon dioxide. Allocated gold Gold that is stored on an allocated basis means that ownership of individual bars is clearly identified. The opposite is unallocated gold, where the metal is kept in a vault and ownership of a particular bar is not identified. American option An option that allows the holder to exercise their right to buy or sell at anytime prior to expiry. Annex B country Under the terms of the Kyoto agreement, annex B countries represented those nations who were willing to commit to legally binding targets to reduce emissions. API The density of crude oil is often expressed in terms of an API value. The scale was devised by the American Petroleum Institute and the lower the value the denser the crude oil and vice versa. Arbitrage This describes a situation where an asset is trading at two different prices in the same market. This would allow a participant to buy and sell quickly to make a risk-free profit net of any costs. Asian Petroleum Pricing Index Asian markets.

This is a popular benchmark for pricing crude oils from

Assay An analysis to determine the presence of a particular substance or component. Within the context of gold an assay will determine the percentage of the metal within a particular bar. In the crude oil market, the process is used to determine the proportion of each refined product that can be made from a particular type of crude oil. At-the-money An at-the-money option is an option where the strike rate is equal to the current underlying market rate. Average price option An average price option is an option where the payout at expiry is linked to an average of market prices. An alternative averaging structure is where the strike is not fixed until maturity and is based on a pre-agreed series of market values. Backwardation prices.

A situation where longer dated forward prices are lower than shorter dated

Balancing Within the power and gas markets, the process of ensuring that the amount of the commodity entering the system equals the amount exiting the system. Barrier option A barrier option has all the features of a conventional option with the addition of a trigger or barrier. The trigger is placed in either the in-the-money or out-of-the money region and if it trades will activate (‘knock in’) or deactivate (‘knock out’) the option. Basket option A basket option is an option where the expiry payoff is linked to the performance of a number of different underlying assets. Bermudan option An option is described as being Bermudan in style if it can be exercised on one of a number of pre-agreed dates.

499

500

GLOSSARY

BFOET Within the oil market this acronym stands for Brent Fortes Oseberg Ekofisk Troll. It reflects the fact that North Sea Crude oil is made up of a series of different crude oils despite being often referred to simply as ‘Brent’. Binary option A binary option is an option where the payoff, if exercised, is a fixed amount irrespective of how deeply the instrument is in-the-money. Borrow Within the context of the base metals market, a borrow is a single transaction comprising two legs with different maturities. The first leg is a purchase and the second is a sale. The first leg could either be a spot or forward deal while the second leg matures at a later date. The party executing the transaction therefore has use of the metal for a specific period of time. Biofuels A range of fuels whose production and consumption are relatively ‘environmentally friendly’ (e.g. ethanol). British thermal unit A common measure of energy content used in the US natural gas markets. Defined as the amount of heat that is required to raise the temperature of one pound of water by one degree Fahrenheit. Call option exercised.

A call option allows the holder the to buy the underlying asset if the option is

Cap and trade system Within the context of emissions trading, a cap and trade system places a maximum amount on the amount of carbon dioxide to be emitted and allows market participants to negotiate the transfer of allowances at a market-determined price. Capital guaranteed structures A capital guaranteed investment ensures that the buyer will always receive back their principal at maturity. This is usually achieved by diverting part of the investors’ proceeds into a zero-coupon bond that repays par at maturity. However, there is no third-party guaranteeing repayment so it is more accurate to describe them as offering capital protection. Carbon cycle The carbon cycle describes the possible pathways a carbon atom takes through the different components of the ecosystem. Clean development mechanism Under the terms of the Kyoto agreement the clean development mechanism represented one of the mechanisms to achieve a reduction in greenhouse gases. The mechanism encourages the investment in developing country projects which will be rewarded by the issuance of credits which could be used in order to comply with the Kyoto emission targets. CERs Certified emission reductions. These are credits issued under the clean development mechanism. Contango A contango market describes a situation where the price of a commodity for forward delivery is greater than the price for spot delivery. Cost of carry When holding a position in an asset, the cost of carry is the amount of income generated by the instrument less any expense incurred. If gold is purchased and held, the initial cost has to be financed by borrowing money. This borrowing cost can be offset by lending out the gold to earn a leasing fee. The cost of carry is the difference between the interest cost and the leasing income. If the cost is greater than the income there is a negative cost of carry and vice versa. CBOT Chicago Board of Trade – a futures exchange. Merged with the Chicago Mercantile Exchange in July 2007 to become known as the CME Group. Clearing house In a futures market the clearing house is the entity that is the ultimate counterparty to any transaction. Ensures that all purchases and sales are matched and that all margins are collected.

501

Glossary

Commitment of traders report This is a report produced by the commodity futures trading commission that shows the position in the US markets for ‘commercial’ and ‘non-commercial’ users of futures. Commodity Futures Trading Commission

The US regulator for exchange traded futures.

Commodity trading advisors This is a group of investors who typically use futures as a means of gaining exposure to a particular market. Their activities may not be restricted to commodities and may encompass a wider set of asset classes. Contract for difference A contract for difference is a transaction that pays out at maturity a sum of money based on the current price of an asset relative to a value established at the trade date. Neither party to the contract is required to deliver the underlying asset. Sometimes referred to as a ‘cash settled forward’ or a ‘swap’. Convenience yield This is the premium that a consumer is willing to pay to be able to consume a commodity now rather than in the future. Correlation A statistical measure that indicates the tendency of two asset prices to move in the same or opposite direction. Correlation vega When pricing basket options, the correlation between the underlying assets is accounted for within the implied volatility input. Correlation vega measures how much the price of the option will change by for a small change in the correlation between the assets. CIF

A price quoted as CIF, will include the Cost (of the product), Insurance, and Freight.

Clean dark spread Cracking ones.

The dark spread adjusted for the cost of emitting carbon dioxide.

The process of taking heavy hydrocarbon molecules and breaking them into lighter

Crack spread The crack spread measures the difference between the cost of crude oil and the income generated from the sale of the refined products. Dark spread The dark spread measures the difference between the cost of coal and income generated from the sale of electricity. Delta Delta measures the amount by which the premium of an option will change for a small change in the underlying price. Density

Density is a measure of the number of molecules within a defined volume.

Derivative A class of instruments that derive their value from an underlying asset price or index value. The derivative building blocks comprise futures/forwards, swaps, and options. Digital option Discount factor future date.

See binary option. A discount factor can be used to present value any cash flow occurring at a

Downstream In the context of crude oil markets this refers to a series of activities at the end of the physical supply chain such as the distribution of refined products to end consumers. Electricity forward agreement A series of market conventions (e.g. calendar dates) that are used in the UK electricity market; also an agreement that fixes the price of electricity at some future date. Elspot This is the physical spot market for Nordic electricity, sometimes referred to as the Elspot market. Emissions trading schemes between market participants.

A market where allowances to emit carbon dioxide are traded

Energy Reliability Organisation In 2005, the US government introduced the Energy Policy Act, which will lead to the creation of the Electric Reliability Organization (ERO). The ERO will

502

GLOSSARY

have the authority to develop and enforce mandatory standards for the reliable operation and planning of the wholesale electricity system in the North American region. European option An option where the holder can only exercise their right to buy and sell at expiry of the contract. European Union transaction log The central registry where all the certified emission reductions generated from the clean development mechanism will be recorded. EUAs

European Union Allowances. These are emission allowances traded within the EU ETS.

EUAA European Union Aviation Allowances. These are emission allowances traded within the EU ETS. EU ETS

The Emission Trading Scheme operated within the European Union.

Exchange delivery settlement price Exchange for physicals futures market.

The final price of a futures contract.

This is a technique used to price a physical commodity by using the

Exotic option An option where the payoff does not resemble that of a European or American style option. Exotic options comprise a number of different products of which average rate (‘Asians’) and barriers are examples. FERC In the USA, the overall direction for the electricity industry is determined by the passage of Federal law. The Federal Energy Regulatory Commission (FERC) regulates the industry at the wholesale level. Fineness

A measure of the quality of gold. The greater the fineness, the purer the metal.

Forward curve A diagrammatical representation of the different prices for delivery of a commodity at different time periods. Forward

An agreement to fix the price for delivery of an asset at a pre-agreed date in the future.

Forward rate agreement

See contract for difference.

FOB A price quoted on a ‘free on board’ basis covers the delivery to a particular port and onto a ship although it is acknowledged that the buyer has responsibility for the goods once they pass over the ship’s rail. Funded/unfunded In the context of investments, a funded structure requires an initial investment. An unfunded structure does not require any upfront investment. Futures

A forward-style agreement traded on an organised exchange.

Gamma

The rate of change of delta with respect to the spot price.

GOFO

The gold forward offered rate.

Gold swap An agreement that involves the sale (purchase) of gold for spot value and the simultaneous purchase (sale) of the gold for a forward maturity. Heavy crude oil ICIS Heren ISO

A heavy crude oil has a high density, expressed as an API gravity.

A publisher of market information for the gas, power, and carbon markets.

An Independent System Operator manages the transmission of power over a given area.

Hydrocarbons

Molecules consisting of hydrogen and carbon atoms.

Implied volatility In-the-money Interconnector

The volatility implied by an observed option price.

An option where the strike rate is more favourable than the underlying price. A pipeline or transmission wire that links two different countries or regions.

Intercontinental exchange

A futures exchange.

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Glossary

IPCC Intergovernmental Panel on Climate Change was formed in 1988. Reviews published research on the issue of climate change and issues summary reports every five to six years. ISDA International Swaps and Derivatives Association; professional market body for the derivatives industry. Joint implementation Under the terms of the Kyoto agreement the joint implementation mechanism represents the investment in an emission reduction project by one annex B country in another. Knock out/knock in Within the context of barrier options a knocks-out option is a contract that includes a barrier/trigger that if traded will deactivate the option; if a trigger leads an option to be activated it is referred to as a knock-in option. Kyoto agreement The Kyoto agreement, which was signed in 1997, established legally binding emission targets for the signatories. It was eventually ratified in 2005. Lease rate

The rate at which gold can be lent or borrowed.

Lease rate swaps A bilateral agreement to exchange cash flows where each leg is calculated on a different basis. Typically, one of the legs will be a fixed rate and the other will be floating. Both legs derive their value from gold lease rates. Lend Within the context of the base metals market, this a single transaction with two legs, whereby the metal is sold for spot value with an agreement to repurchase it at some future date. The economic affect of the transaction is equivalent to the loan of the metal over the same period. Leverage

The ability to use a small amount of capital to control a much larger exposure.

Light crude oil

Crude oil that has a low density.

Liquefied Natural Gas In liquefied form natural gas occupies 1/600 of the space it would in gaseous form making it more viable to transport over longer distances. To create LNG, it is cooled below its freezing point of −161∘ C/−260∘ F and other constituents such as oxygen and carbon dioxide are removed to leave a gas that is virtually pure methane. Load Load describes how much electricity will be consumed by an electrical device at a given time. A baseload contract provides for the delivery of a constant volume of power. A peak load contract covers the period of highest demand. Off peak covers all other periods outside of the peak load definition, typically nights, weekends, and holidays. Loco London Literally, ‘location’ London. The price for gold is typically quote in terms of a certain level of quality for delivery in a particular location. The loco London price is the price for delivery of the metal in London. London Bullion Market Association market.

The professional market body for the London gold

London Good Delivery These are a set of standards that define the exact nature of the gold that will be exchanged for delivery in London. London Metals Exchange traded. Long

An organised exchange where base metals and plastics can be

Can be used to describe either the purchase or existing holding of an asset.

Margin – initial and variation Margins are incurred when executing futures transactions on an organised exchange. Initial margin is collected when a position is first opened and returned when the position is closed. Variation margin is based on the change in the value of the contract and is collected according to the terms set out by the individual exchange. Marker crudes Crude oil prices are often expressed as a spread to some benchmark or ‘marker’ crude. The two key marker crudes are Brent and West Texas Intermediate.

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GLOSSARY

Mean reversion average value. Methane

The tendency for the price of a particular asset to revert towards a long-term

Another name for natural gas.

Midstream Within the context of crude oil this relates to a series of activities along the physical supply chain. Typically, they include all the refining related activities. Min-max This is an option structure, which is constructed as the combination of the purchase (sale) of a call and the sale (purchase) of a put option with the strikes set at a level that result in a zero premium. Has the effect of setting the minimum or maximum values at which an asset could be bought or sold. Monomer

A building block used in the production of plastic.

Naphthenic flammability.

A crude oil that has naphthenic properties is one that has a high viscosity but low

Natural gas liquids When natural gas is extracted from the ground it will usually comprise of a series of different gases, which are then separated into their component parts. Collectively they are referred to as natural gas liquids. NERC North American Electric Reliability Council is responsible for ensuring the reliability, security, and adequacy of the bulk power system in the USA, Canada, and parts of Mexico. Nord Pool

A Scandinavian Energy Exchange.

Notional amount A value used to calculate the cash flows associated with a derivative transaction. Does not represent an actual cash flow itself. NYMEX

New York Mercantile Exchange; a futures exchange.

Organisation for Petroleum Exporting Countries ducing countries.

An organisation of eleven crude oil pro-

Options An instrument that gives the holder the right but not the obligation to buy or sell an underlying asset at a pre-agreed price at a date in the future. Since the holder is acquiring a right, they will be required to pay a fee which is called a premium. OTC

Over-the-counter is a transaction that is executed outside of an organised exchange.

Out-of-the-money market price. Paraffinic Platts

An option where the strike rate is less favourable than the underlying

A chemical property of crude oil, which literally means ‘like paraffin’.

A provider of information for the energy and metals markets.

Plain vanilla Put option asset.

A jargon phrase used to describe a very simple version of a particular structure. An option that gives the holder the right but not the obligation to sell an underlying

Polymer A polymer (poly is Latin for many) is a number of individual monomers chemically joined by a bond to form a single structure. Pour point A measure of the lowest temperature at which either crude oil or a particular refined product flows as a liquid under a given set of conditions. Premium – 1

The fee payable when buying an option.

Premium – 2 In some market’s commodities are traded as a spread to some benchmark. For products that have a higher quality their price is expressed as a premium to the benchmark. Prompt date

The date for delivery of an asset.

505

Glossary

Put-call parity This concept links options to their underlying markets by creating an equality between puts, calls and the underlying asset. In a simplified form it states that the purchase of a call and the sale of a put with the same strike and same maturity will be economically equivalent to a long position in the underlying market. Olefins/polyolefins Because there are thousands of different hydrocarbons, it is often convenient to divide them into categories. One such category is alkenes of which ethylene is an example. Alkenes generally have a simple chemical structure, are cheap to make and are relatively easy to polymerise. Alkenes are also sometimes referred to as ‘olefins’ and their polymers (such as polythene and polypropylene) ‘polyolefins’. Quanto The return from a quanto structure is based on an asset denominated in a foreign currency, however the actual cash flow that is paid to the holder is denominated in the investor’s local currency removing all of the currency risk. Ring

The part of the London Metal Exchange where physical trading of metal takes place.

Regional transmission organisations responsibilities.

An Independent System Operator with regional

Rolling Rolling is the process whereby an investor sells a maturing future, but to ensure their exposure is maintained, simultaneously buys a future with a later maturity. Roll yield Roll yield represents the net benefit or cost of owning the underlying asset beyond moves in the spot price. If one were to own gold, the costs of financing the purchase and storage would need to be added less any income derived from leasing the gold.

®

Previously known as the Goldman Sachs Commodity Index but was sold to StanS&P GSCI dard and Poor’s in early 2007. Widely acknowledged to be the most widely used measure for index-linked investment structures. Shippers Shippers are wholesale participants in the natural gas market who will be responsible for the movement of natural gas through the pipeline. Short The sale of an asset; can also be used to denote the need to buy something at a future date that is currently not owned. Sour

Crude oil with a high sulfur content.

Spot ‘Immediate’ delivery of an asset. Depending the asset concerned this could be anything from the same day to several days in the future. Generally spot means delivery in two days time. Strike

The price at which an asset is bought or sold if an option contract is exercised.

Swap A bilateral, multi-period agreement to exchange cash flows whose magnitudes are calculated or different bases. When the contract covers a single exchange, it may be referred to as a ‘contract for difference’ or a ‘cash settled forward transaction’. Swaptions Sweet

An option on a swap.

Crude oil with a low sulfur content.

Synthetic Within the context of derivative theory, it is often possible to combine instruments so that on a net basis they will possess the economic properties of another. For example, by buying a call and selling a put with the same strike and maturity the resultant position is economically equivalent to being long the underlying asset. That is, it is a synthetic long position. Total return swap A transaction whereby an investor will receive a set of cash flows based on the return of a given asset or index. The transaction allows an investor to take exposure to the asset or index without having to actually buy it. Therm

A measure of energy used in the UK natural gas market.

506

GLOSSARY

Thermal efficiency content of the input.

Thermal efficiency relates the electrical energy produced to the energy

Theta Measures by how much an option premium will change with respect to the passage of time, typically one day. Upstream Upstream describes a series of activities at the start of the physical supply chain and includes exploration and extraction. Utilities

A company that provides a range of household services such as power and water.

Vega Measures by how much an option premium will change with respect to a 1% change in implied volatility. Viscosity pouring.

A measure of the ability of crude oil or a refined product to flow or its resistance to

Volatility

A measure of price variability.

Volt

Measures the force being used to push electrons around a circuit.

Warrant Within the context of the base metals market, a warrant will denote ownership of metal stored within a warehouse. Washington Agreement This was an agreement between Central Banks detailing their planned future gold sales. First signed in 1999 and revised in 2004, 2009, and 2014. Watt

Unit of measurement of electrical power.

Watt hour watt-hours.

The amount of electricity generated or used over a period of time is measured in

Zero-coupon rate A zero-coupon instrument has only two cash flows; the initial outlay and the final repayment. A zero-coupon rate measures the rate of return implied by these two values.

Bibliography

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Biography

Neil C. Schofield is the principal of Financial Markets Training Ltd., a UK-based company offering training services in the areas of treasury, derivatives, capital markets, and risk management to financial institutions, central banks, and corporations worldwide. Neil was global head of Financial Markets training at Barclays Capital from 2001 to 2008. He teaches primarily on the rates business, covering all of the major asset classes and their respective derivative products from foreign exchange through to commodities. Before joining Barclays Capital, he was a director at Chisholm-Roth Training for four years, where he was responsible for provision of training services for a number of blue-chip global investment banks. Clients included Citigroup, Deutsche Bank, Goldman Sachs, and JP Morgan Chase. He started his training career at Chase Manhattan Bank (now J.P. Morgan Chase), where he was originally employed as an internal auditor. Over a period of nine years, he conducted numerous internal and external training seminars including the Bank of England and the Federal Reserve System in the USA. He has also held positions with Security Pacific Hoare Govett (now trading as Bank of America) and Lloyds TSB. Neil holds a B.Sc. in Economics from Loughborough University and an MBA from Manchester Business School. He was elected as a Fellow of the IFS School of Finance (formerly the Chartered Institute of Bankers) in 1999.

510

Index

A AAU. See Assigned amount units Accomazzo, D., 472 Account payable, 439 Act of God clause, 60 AFRA. See Average freight rate assessment Agricultural products, 1, 394–432 cocoa, 408–409 futures, 423–426 coffee, 1, 20, 403–408 corn, 396–398, 399 derivatives, 418, 421–426 ethanol, 409–412, 414–415, 421–426 futures, 418, 422, 423–426 FX, 417 options, 427–429 OTC, 426–432 palm oil, 398–401 price drivers, 412–421 soybeans, 401–403 speculation, 418 spread options, 422, 427–429 sugar, 403 supply chain, 395–402 swaps, 426–427 TARNs, 429–432 vanilla swaps, 427 wheat, 396, 397 Alaska North Slope, 207 Alpha crude oil, 183 jet fuel hedging, 234 Aluminium, 1, 30 basket options, 151–154 electricity, 319–322 forward price, 139–140 hedging, automotive sector, 139 Amajaro, 421–426 Amaranth Advisors LLC, 72–74 American barrier reset swap crude oil hedging, 224 gold, 100–102 American Sour Crude Index (ASCI), 207–208 American style option, 12 Annual contracts coal, 350

LNG, 255 natural gas exchange traded futures, 263 Anthracite, 342 AP. See Approved participant AP12, 349 API4, 349 Approved participant (AP), ETC, 483 Arabica coffee, 404 Arbitrage crude oil, 197–198 fair value, 24 forward price curve, 24, 28 quality, 31 time, 29–30 geographic emissions, 388 forward price curve, 28–29 natural gas, 260 price, 6 risk premium, 468 Argus Media, 207–208 ASCI. See American Sour Crude Index Asian style put options, 103–104 Asset conversion cycle, financing, 439–453 Asset price basket options, 490 options volatility term structure, 54 spread options, 16 veta options, 50 Assigned amount units (AAU), 375 At-the-money (ATM) base metal basket options, 154 income structures, 491 options, 12, 40, 42 non-constant volatility, 51 risk management trading, 69 vega, 50 volatility skew, 52 volatility term structure, 54 Authers, John, 82 Autocallable structures, 493–495 Automotive sector. See also Electric vehicles hedging aluminium, 139 Average freight rate assessment (AFRA), crude oil, 164 Average rate options (avros), 16–17

511

512

B Bachelier model, options, 41–42 Backwardation (contango) forward price curve, 21–29 longer dated maturities, 61 Baltic Dry Index (BDI), 496–497 Baltic Exchange, iron ore, 356–358 Banks, E., 62 Barclays, 19, 27, 90, 131, 399–400 on risk premium strategies, 467–468 Barley, 418 Barrier options, 14–15, 104–105 two asset, 105–106, 220–223 Base metals, 1, 114–157. See also specific metals backwardation, 25 carry trades, 141 commodity trading houses, 6 EV, 133–134 forward price, 135–136 curves, 28–29 FX, 154–157 swaps, 156–157 hedging, 141 inventories, 19 investment banks, 5 LME, 122–130 LME futures, 123 long-term prices, 134 marginal cost, 136–137 options combination, 146–149 volatility term structure, 56 premiums, 137–139 price drivers, 130–132 risk management, 74–75 short options, 144–146 spot price, 7–8 spreads, 68 structured options, 149–154 swaps, 10 swaptions, 146 synthetic long put, 142–144 vanilla options, 141–142 Baseload, electricity, 303 Basic oxygen furnace (BOF), 120, 121 Basket options, 489–491 base metal structured options, 151–154 BBQ spread, 421 BDI. See Baltic Dry Index BEIS. See Department for Business, Energy, and Industrial Strategy, UK Benchmarks, 7–8 coal, 349 commodity index, 463 crude oil, 169, 191–193 gold price, 80 iron ore, 7

INDEX freight, 357 LME, 126 plastics, 336 project finance, 438 Bermudan options, 12 natural gas, 277–278 Beta crude oil, 183 jet fuel hedging, 234 BFOET. See Brent Blend, Forties, Oseberg, and Ekofisk and Troll Bid-offer spread forward price curve, 22 swaps, 11 Bilateral markets, electricity, 286–287 Bill of Lading crude oil, 194 financing, 434 Binary options (digital options), 14 Biobutanol, 410 Biodiesel, 410 Biofuels, 410, 415 Biomass to liquids, 410 Bituminous coal, 342 Black, Scholes and Merton (BSM), options, 39–43, 54 Black model, options, 41 Black products, 164 Blow moulding, plastics, 335 Blumsack, S., 311–312 BOF. See Basic oxygen furnace Bowler, T., 324 Brand loyalty, commodity valuation, 20 Brass, 117 Brent, 169, 191 CFDs, 201–205 complex, 198 contract summary, 208 exchange traded futures, 201, 205 forward contracts, 199–201 futures, 205 ICE, 34 swaps, 218 price relationship, 196 Brent Blend, Forties, Oseberg, and Ekofisk and Troll (BFOET), 198, 200 British Thermal Unit (BTU), 238 BSM. See Black, Scholes and Merton BTU. See British Thermal Unit Buffett, Warren, 81 Bull spread income structures, 491 three way basement options, 147–148 vanilla options, 454 Business cycle (economic cycle), 466 base metal price, 132 commodity prices, 18–19 plastic price, 337

Index Butane, 334 Butler, Willem, 81

C Caffeine, coffee, 405 Calendar spread options crude oil, 227–230 natural gas exchange traded futures, 265 Call options, 15 avros, 16, 17 fixed rate, 461 gamma, 48 gold yield enhancement, 111 interest rates, 457–458 longer dated maturities, 61 options, 11–12 OTM, supply and offtake agreements, 453 put-call parity, 43–44 spread options, 16 underlying price, 44–45 vanilla options, 454 weather, 392 Call spread. See Bull spread Calorific value coal, 348 natural gas, 238 Campbell and Company, 472 Capesize, iron ore freight, 355 Capital assets, 18 Capital protected notes, 91, 463, 486–488 Carbon cycle, climate change, 369–370 Carbon dioxide climate change, 368–375 coal, 300–301, 347–348 ethanol, 410 EU ETS, 381 LNG, 249 Carry over, 394, 415 Carry trades base metals, 141 copper, 450–451 Cash and carry, forward price curve, 29 Cash flow avros, 17 floating, 32–33, 37 FXD, 35, 36, 37 prepay structures, 446 project finance, 438 PV, 446 swaps, 10, 32–33 volatility, longer dated maturities, 61 Cash price base metals, 149, 151 crude oil, 213–215 forward price curve, 30–31 LME, 140 Cash settlement base metal, 130, 140

513 crude oil, 205, 206, 208 futures, supply and offtake agreements, 453 gold, 103, 105 natural gas, 275 options, 11–12 supply and offtake agreements, 453 CAT. See Cumulative Average Temperature CCGT. See Combined Cycle Gas Turbine CDD. See Cooling Degree Days CDM. See Clean Development Mechanism Cellulosic ethanol, 410 Certified emission reductions (CERs), 375 CFDs. See Contracts for difference CFR. See Cost and freight CFTC. See Commodity Futures Trading Commission Charterers, iron ore freight, 356 China agricultural products, 421 base metal price, 130 crude oil, 176 plastic price, 338 sugar, 403 wheat, 396 Chinamax, iron ore freight, 355 Chocfinger, 421–426 Choke points, iron ore freight, 361 Chooser swaps, natural gas-274, 273 CHP. See Combined Heat and Power Christian, J. M., 401, 422 CIF. See Cost, Insurance, and Freight Clean Development Mechanism (CDM), 374–375 EU ETS, 383 Clearinghouse, 127–128 forward risk management, 64 TR, 470 Climate change agricultural products, 412–413 argument against, 372–373 carbon cycle, 369–370 consequences, 371–372 feedback loops, 370–371 GHG, 368–369 human action against, 373–376 CME Group agricultural products, 421–426 crude oil, 182, 193, 208–209 electricity, 302 futures, 8, 9 natural gas, 252 swaps, 271 weather exchange traded futures, 389–390 WTI negative prices, 211 Coal, 341–353 caloric value, 348 dark spreads, 347 demand and supply, 343–346 derivatives, 349–353

514 Coal (Continued) electricity, 281–282, 297, 349 exchange traded futures, 350 exporting, 350 liquefaction, 349 NPPs, 349 price, 350 proved reserves, 343 supply chain, 346–349 swaps, 349, 351–352 swaptions, 352–353 vanilla options, 349 Cobalt, 123 EV, 133, 134 Cocoa, 408–409 futures, 423–426 Coffee, 1, 20, 403–408 Coking coal, 342 Combined Cycle Gas Turbine (CCGT), 282 Combined Heat and Power (CHP), 282 Commitment of Traders (COT), 418–421 Commodities. See also specific topics financing, 433–461 fundamentals, 1–57 investing, 462–497 markets commodity trading houses, 5–6 exotic options, 14–17 forward contracts, 8 futures, 8–9 hedge funds, 6 investment banks, 5 nonhomogeneity of, 2 options, 11–13 overview, 2–3 participants, 3–6 PRAs, 4–5 real money accounts, 6 supply chain, 3–4 swaps, 10–11 time, 60–61 transportation for, 3 traded vs. non-traded, 6–8 valuation, 19–21 Commodity Futures Trading Commission (CFTC), 418–421 Commodity indices, investing, 468–477 Commodity pool operators (CPOs), 419 Commodity risk, 59 base metal swaps, 157 natural gas NPPs, 242 Common Agricultural Policy, EU, 417 Conference of Parties (COP), 376 Consumable/transformable assets (C/T), 18 Contango (backwardation) forward price curve, 21–29 longer dated maturities, 61 Contracts for difference (CFDs)

INDEX Brent crude oil, 201–205 electricity, 313, 317–318 Convenience yield, forward price curve, 25, 26, 27 Convertible forward, gold forward contracts, 97 Cooling Degree Days (CDD), 294 weather call options, 392 weather exchange traded futures, 389–390 COP. See Conference of Parties Copper, 1 automotive sector, 139 basket options, 151–154 brass and, 117 carry trades, 450–451 futures, 125 FX swaps, 156–157 lifecycle, 115–119 options, 126 resources, 115 scrap, 117 supply chain, 116–117 trading, 117–119 uses, 116 Corn, 396–398, 399 ethanol, 409–412 Correlation risk, 65 Cost, Insurance, and Freight (CIF), 191, 194 coal, 349 LNF, 255 Cost and freight (CFR), iron ore, 354 COT. See Commitment of Traders Counterparty credit risk, 449 ETF, 484 forward risk management, 64 gold, 483–484 OSI discounting, 37 LME, 127 Covered call strategy coal swaptions, 353 gold yield enhancement, 111–112 COVID-19 force majeure, 449 legal risk, 60 WTI negative prices, 211 CPOs. See Commodity pool operators Crack spreads, 68 crude oil, 197 refiner hedging, 224–227 supply and offtake agreements, 453 Credit risk, 59–60 case study, 65–66 counterparty, 449 ETF, 484 forward risk management, 64 gold, 483–484 OSI discounting, 37 crude oil, 440 ETF, 483

515

Index Credit Support Annex (CSA), LME, 128 Cross, Jessica, 96 Cross market trading, electricity, 315 Crude oil, 1. See also Brent; Refined products; West Texas Intermediate acidity, 161 arbitrage, 197–198 avros, 16–17 backwardation, 25 benchmarks, 169, 191–193 chemistry, 160–161 commodity trading houses, 6 consumption, 176, 177 crack spreads, 197 credit risk, 440 delivered price, 190–191 density, 161 EFP, 194, 206–207 electricity, 281–282 ETF, 484 examples, 162–163 exchange traded futures, 193, 196 producer hedging, 212–215 forward contracts, 199–201 forward price curve, 21, 27, 189, 196 freight, 31, 186, 196 futures, 197, 208 jet fuel hedging, 233–234 geopolitics, 187–189 GPW, 169 hedging producers, 212–223 refined products, 230–236 refiners, 223–230 internal unrest, 187 investment banks, 5 market risk, 196 monomers, 334 nationalism, 187 nonhomogeneity of, 2 options crack spread heading, 226–227 volatility term structure, 55–56 plastics options, 340 pour point, 162 PRAs, 4 price, 189–195 calculating, 209–211 coal, 350 drivers, 179–189 LNG, 256 natural gas, 253–255 plastics, 337 product substitution, 172, 181 production, 174–175 costs, 184 price driver, 180 profitability, 169–172

proved reserves, 172, 173 price driver, 180 proxy hedge, 212 quality, 187 refining, 165–172 demand, 177–178 price driver, 184–185 repurchase agreement, 440–443 R/P, 172–174 spread trades, 197–198 storage, 31 sulfur content, 161 supply and demand, 172–179 security, 179 supply and offtake agreements, 451–452 supply chain, 163–164 price driver, 184–187 price risk, 212–236 swaps, 10, 32, 35, 216–218 crack spread OTC hedging, 225–226, 227 futures, 219–220 trading, 176–177, 195–212 two asset barrier options, 220–223 USD, 183 value, 159–163 vanilla options, 454–455 viscosity, 162 volatility skew, 51–52 weather, 183–184 Crude oil refiner hedging, crack spreads, 224–227 Crush spread, 422 CSA. See Credit Support Annex C/T. See Consumable/transformable assets Cumulative Average Temperature (CAT), 390 Currency markets. See also Foreign exchange gold price, 90

D Daily Composite Indicator, coffee, 408 Daily volume, electricity, 304 Dark spreads coal, 347 electricity, 299–301 Dated Brent (North Sea Dated), 194, 198–199 crude oil swaps, 217–218 forward contracts, 199–201 Debt Service Coverage Ratio (DSCR), 439 Deferred margin accounts, gold, 109–110 Delivered price crude oil, 190–191 futures, 437 Delta options, 44–47 hedging, risk management trading, 69 plastics, 340 Department for Business, Energy, and Industrial Strategy, UK (BEIS), 244 Department of Agriculture, US, 416

516 Derivatives. See also Forward price; Futures; Hedging; Options; Swaps agricultural products, 418, 421–426 asset characteristics, 18 coal, 349–353 commodity prices and economic cycle, 18–19 electricity, 313–331 emissions, 384–388 ethanol, 421–426 forward price curve, 21–31 freight, iron ore, 362–367 fundamentals, 1–57 gold price, 80 heat rate, electricity, 326–331 interest rate, 457–463 iron ore, 354–355 LNG, 279 natural gas, 263–279 options, 12 valuation, 18–57 weather, 388–393 Diesel, 165 applications, 231 ULSD, 197 Digital options (binary options), 14 Directional changes, forward price curve, 135 Discounts forward price curve, 26 gold flat forwards, 97 LME, 124–125 swaps, 33, 34–39 Diversification, investing, 463 DMT. See Dry metric tonne Double down swaps, natural gas, 274 Dry metric tonne (DMT), 125 DSCR. See Debt Service Coverage Ratio Dunn, R., 62

E E10 fuel, 411 EAF. See Electric arc furnace Earth Summit, 374 ECMWF. See European Centre for Medium Range Weather forecasts Economic cycle. See Business cycle The Economist, 259, 421 EDSP. See Exchange delivery settlement price EEX. See European Energy Exchange EFA. See Electricity Forward Agreement EFP. See Exchange for physicals EIA. See Energy Information Administration El Niño Southern Oscillation (ENSO), 413 Electric arc furnace (EAF), 120, 121 Electric vehicles (EVs), 133–134 crude oil price, 182 electricity, 295 Electricity

INDEX aluminium, 319–322 bilateral markets, 286–287 CFD, 313, 317–318 coal, 281–282, 297, 349 commercial production, 282–283 consumers, 302 contract volumes, 303–304 cross market trading, 315 dark spreads, 299–301 defined, 280 demand, 294–295 derivatives, 313–331 emission markets, 378 EU, 287–288 forward price, 297–298 curve, 313–315 fuels, 281–282 generators, 284 heat rate, 301 derivatives, 326–331 options, 328–331 interconnectors, 296 intermediaries, 303 load, 291–292 shapes, 303 maturity, 298 measuring, 283 natural gas, 259, 281–282, 296–297, 349 negative prices, 298–299 options, 321 pools, 285–286 price, 321 drivers, 291–295 formation, 304–307 producers, 302 production optimisation, 307–308 spark spreads, 299–301 spot price, 297–298 spread options, 319 suppliers, 302 supply, 295–297 supply chain, 283–285 swaps, 315–317 swaptions, 318–319, 323–325 system imbalances, 308–309 timing mismatches, 309 trading, 301–313 UK, 284, 288 trading conventions, 309–310 US, 288–289 traded markets, 310–313 wholesale markets, 290 weather, 294, 393 Electricity Forward Agreement (EFA), 309–310 Emission Trading Schemes (ETS), 374–375 Emissions market, 1 derivatives, 384–388 options, 388

517

Index price drivers, 376–379 swaps, 386–387 Emissions Trading System (ETS), 379–384 Energy Information Administration (EIA), 166, 185 electricity, 283 WTI negative prices, 211 ENSO. See El Niño Southern Oscillation EONIA. See European Overnight Index Average Equilibrium price, base metals, 134 Equity index, forward price curve, 21 Equity risk, 59 ER. See Excess return index ESTER. See Euro short term rate ETC. See Exchange Traded Commodity ETF. See Exchange Traded Fund Ethane, 165, 334 Ethanol, 409–412, 414–415 derivatives, 421–426 Ethylene, 332–334 ETN. See Exchange Traded Note ETP. See Exchange traded products ETS. See Emission Trading Schemes; Emissions Trading System EU. See European Union EU Commission, 298 EUAs. See European Union Allowances Euro short term rate (ESTER), 457 European Centre for Medium Range Weather forecasts (ECMWF), 390 European Energy Exchange (EEX) electricity, 302 EU ETS, 381 European Overnight Index Average (EONIA), 38 European Union (EU) Common Agricultural Policy, 417 electricity, 287–288 natural gas, 244 sugar, 403 wheat, 396 European Union Allowances (EUAs), 375, 381, 384, 385, 387, 388 European Union Transaction Log (EUTL), 382 EVs. See Electric vehicles Excess return (ER) index, 470 Exchange delivery settlement price (EDSP), LME, 127 Exchange for physicals (EFP) crude oil, 194, 206–207 natural gas exchange traded futures, 265–266 Exchange Traded Commodity (ETC), 464, 483 Exchange Traded Fund (ETF), 464, 483–484 Exchange traded futures Brent, 201, 205 coal, 350 crude oil, 193, 196 crack spread hedging, 224–225 producer hedging, 212–215 forward contract risk management, 64

natural gas, 263–266 spot price, 7 weather, 389–390 WTI, 213–215 Exchange Traded Note (ETN), 464, 485–486 Exchange traded products (ETP), 462, 463, 464, 480–486 gold price, 85, 88, 91 Exotic options, commodity markets, 14–17 Exotic swaps, iron ore freight, 366–367 Extrusion, plastics, 335

F Facility margin, 440 Fair value arbitrage, 24 crude oil, 183 emissions, 384, 385 forward price, 22, 23 LIBOR, 24 options, 41, 104 speculation, 183 Federal Energy Regulatory Commission (FERC), 289 Feedback loops, climate change, 370–371 FERC. See Federal Energy Regulatory Commission FFAs. See Forward freight agreements Financial Times, 5, 60, 388, 416 Financial Transmission Rights (FTRs), electricity, 313 Financing asset conversion cycle, 439–453 Bill of Lading, 434 case studies, 436–437 ETP, 462, 480–486 interest rate hybrids, 456–461 LC, 435 loan structures, 433–434 longer term debt funding, 453–461 margin, 444–445 ownership, 434 possession, 434 prepaid variable forwards, 446–449 prepay structures, 445–446 project, 437–439 risk management, 449–450 structured products, 486–497 supply and offtake agreements, 451–453 TPA, 444–445 TR, 434 vanilla options, 454–456 warehouse receipt, 435–436 working capital, 439–453 Fine art, store of value assets, 18 Fixed cash flows (FXD), LIBOR discounting, 35, 36, 37 Fixed price crude oil, 193

518 Fixed price (Continued) swaps, 32, 217 electricity, 302 jet fuel, 65 jet fuel hedging, 234 options, 11 plastics swaps, 339 Fixed rate American barrier reset swap, 101 call options, 461 floating price, 32 jet fuel, 232 natural gas, 277–278 swaps, 10–11, 32–33, 36, 223–224, 226 Fixed value coffee, 408 gold price, 80 Flat rates, gold forward contracts, 97 Floating cash flow, swaps, 32–33, 37 Floating leg, swaps, 10 Floating price fixed rate, 32 forward contract electricity, 315 natural gas, 267–268 Floating rate forward, gold forward contracts, 97 FOB. See Free on Board Force majeure, 449 Foreign exchange (FX) agricultural products, 417 base metals, 154–157 price, 130 crude oil two asset barrier options, 220–223 gold price, 93 swaps, 99 swaps base metals, 156–157 gold, 106–109 Foreign exchange (FX) risk, 59 Forest products, 1 Forward contracts Brent, 199–201 commodity markets, 8 crude oil, 199–201 emissions, 385 floating price electricity, 315 natural gas, 267–268 futures, 9 gold, 8, 96–99 knock-out, base metal structured options, 149–150 natural gas, 267–269 options, 11 plastics, 338–340 prepaid variable, 446–449

INDEX Forward freight agreements (FFAs), iron ore, 362–366 Forward plus, base metal structured options, 150–151 Forward price aluminium, 139–140 base metals, 135–136 electricity, 297–298 fair value, 22, 23 gold FX swaps, 108 gold price, 92–94 project finance, 438 risk management trading, 67–68 Forward price curve, 21–31 base metals, 134, 135 crude oil, 189, 196 electricity, 313–315 natural gas, 73 options, 40 volatility term structure, 55–56 prepay structures, 445 structured products, 489 Forward risk management, 64 Fracking (hydraulic fracturing), natural gas, 237, 247 Frankfurter, M., 472 Fraud risk, 449 Free on Board (FOB) coal, 349 crude oil, 191, 194 crude oil swaps, 217 LNF, 255 Freight (shipping), 1 crude oil, 31, 186, 196 derivatives, iron ore, 362–367 futures, LNG, 366 iron ore, 355–362 exotic swaps, 366–367 options, 367 price drivers, 360 swaps, 366–367 Worldscale System, 359–360, 365 natural gas, 239 steel, 121 FTRs. See Financial Transmission Rights Fuel cost coal, 348 electricity, 300, 305 iron ore, 362 Fuel oils, 165, 168, 177 applications, 231 Futures. See also Exchange traded futures agricultural products, 418, 422, 423–426 Brent, 205 crude oil swaps, 218 ICE, 34 cash settlement, supply and offtake agreements, 453

519

Index coffee, 408 commodity market, 8–9 copper, 125 crude oil, 194, 197, 208 jet fuel hedging, 233–234 swaps, 219–220 delivered price, 437 forward price curve, 26 freight, LNG, 366 gas oil, jet fuel hedging, 232–233 hedging, 92n13 iron ore, 354–355 LME, 123–124 LNG, 279 plastics, LME, 336 project finance, 438 roll yield, 471–476 FX. See Foreign exchange FXD. See Fixed cash flows

G Galitz, L., 34, 39 Gamma options, 48 electricity, 321 risk management trading, 71 GAR. See Gross as received Gas formula swaps, natural gas, 273 Gas oil, 165, 167, 168 futures, jet fuel hedging, 232–235 put options, 428 Gasolines, 74, 165, 168 applications, 231 Gas-on-gas pricing, 253 GDP. See Gross Domestic Product Geman, H., 39 Geographic arbitrage emissions, 388 forward price curve, 28–29 Geopolitics, crude oil, 187–189 GFS. See Global Forecast System GHG. See Greenhouse gases Glencore Xstrata, 5 Global Forecast System (GFS), 390 Global Warming Potential (GWP), 369 GlobalCoal NEWC index, 349 GOFO. See Gold forward offered rate Gold, 1, 76–113 binary options, 14 counterparty credit risk, 483–484 deferred margin accounts, 109–110 delta options, 44–46 fineness, 79 forward contracts, 8, 96–99 forward price curve, 23–24 futures, 8–9 FX swaps, 106–109 hedging, 96–106 intermediaries, 77

inventories, 19 leasing, 91–96 lending and borrowing, 94–96 LME, 78–81 marks, 79 NDFs, 108–109 options, 13, 40, 102–106 risk management trading, 70–71 volatility skew, 53–54 volatility term structure, 56 outperformance, 495–496 price demand, 85–88 drivers, 81–91 forward contracts, 98 forward price, 92–94 inflation, 88–90 LBMA, 79–81 modeling, 90–91 supply, 82–85 US dollar and, 90, 92–93 yield enhancement, 111–112 purity, 79 roll yield, 472–473 spot price, 91, 487–488 storage, 79 supply chain, 76 swaps, 10, 98–102, 106–109 trading, 106–110 underlying price, 13 weight, 78 yield enhancement, 111–112 Gold forward offered rate (GOFO), 81 Gorton, Gary B., 480 GPW. See Gross product worth Grains, 1 Greek measures, options risk management, 65, 69 Greenhouse gases (GHG) climate change, 368–369 Paris Agreement, 376 Greer, R. J., 18, 26 Gregory, R. J., 449 Gross as received (GAR), coal, 348 Gross Domestic Product (GDP), crude oil, 179 Gross product worth (GPW), crude oil, 169 GWP. See Global Warming Potential

H Handymax, iron ore freight, 355 Handysize, iron ore freight, 355 HDD. See Heating Degree Days HDPE. See High density polyethylene Heat rate derivatives, electricity, 326–331 electricity, 301 options, electricity, 328–331 Heating Degree Days (HDD), 294 weather call options, 392

520 Heating Degree Days (HDD) (Continued) weather exchange traded futures, 389–390 Heating oil (HO), 74, 209 applications, 231 crack spread, 170 seasonality, 19 Heavy and sour oil, 162–163 Hedge funds, 462 agricultural products, 416 cocoa, 424 commodity markets, 6 crude oil, 183 electricity, 315–316 natural gas, 72–74, 270 risk management, 72–74 short dated maturities, 60 Hedge ratio crude oil futures, 234 delta options, 44, 47 Hedging. See also specific types aluminium, automotive sector, 139 base metals, 141 crude oil producers, 212–223 refined products, 230–236 refiners, 223–230 electricity swaps, 316 ETF, 484 forward price curve, 23 futures, 92n13 gold, 96–106 inflation, 466–467 jet fuel, 232–236 natural gas exchange traded futures, 264–265 options, 13, 40 project finance, 438 repurchase agreements, 71 risk management corporations, 61–63 customers, 63–66 USD, 467–468 Henry Hub (HH), 253, 256, 261, 263 LNG futures, 279 swaps, 271 Heren European Spot Gas Markets (HESGM), 252 HFCs. See Hydrofluorocarbons HH. See Henry Hub High density polyethylene (HDPE), 335 Historical volatility, vega options, 49 HO. See Heating oil Hog crush trade, 421 Holidays, agricultural products, 416 Horizontal drilling, natural gas, 237 Hubbert’s peak, 180 Hydraulic fracturing (fracking), natural gas, 237, 247

INDEX Hydroelectric energy, 281 Hydrofluorocarbons (HFCs), 369

I ICE. See Intercontinental Exchange ICIS Heren, 267, 270 ICO. See International Coffee Organisation ICSG. See International Copper Study Group IEA. See International Energy Agency IHS Markit, 336 Implied volatility avros, 16, 17 base metal basket options, 153 capital protected notes, 488 coal, 350 correlation risk, 65 crude oil price, 197 delta options, 47 gold yield enhancement, 112 options, 13, 40, 41 risk management, 65, 69–75 volatility term structure, 55 plastics options, 340 structured products, 489 vega options, 49–51 Incentive price, base metals, 134 Income structures, 491–492 The Independent, 337 Independent System Operators (ISOs), electricity, 289 Index points contango, 21–23 investing, 465 weather, 390 Index price Brent futures, 205 coal, 351 crude oil swaps, 217–218 electricity, 315 forward price curve, 22–23 jet fuel, 65 Index swaps. See also Overnight Index Swap natural gas, 272 India agricultural products, 421 base metal price, 130 plastic price, 338 sugar, 403 wheat, 396 Inflation gold price, 88–90 hedging, 466–467 risk, 59 Infrastructure base metal price, 131 crude oil price, 185, 186 iron ore freight, 362 natural gas, 258

521

Index Injection moulding, plastics, 335 Interbank, options, 50 Interconnectors electricity, 296 natural gas, 240–241 Intercontinental Exchange (ICE) Brent futures, 34, 205 coal, 350 coffee, 408 crude oil, 193 electricity, 302 EU ETS, 381 gold price, 80 iron ore, 354 natural gas, 252, 261 exchange traded futures, 263–264 Interest rate. See also London InterBank Offered Rate call options, 457–458 capital protected notes, 488 caps and floors, 457–458 derivatives, 457–462 forward price curve, 31 hybrids, 456–461 options risk management trading, 69 risk, 59 swaps, 34–35, 460–461 zero premium knock-in collars, 458–460 Intergovernmental Panel on Climate Change (IPCC), 369, 371–372, 373–374 Intermediaries. See also Investment banks; Trading houses electricity, 303 gold, 77 supply and offtake agreements, 452, 453 Intermediate crude oil, 162 International Cocoa Organisation, 408 International Coffee Organisation (ICO), 403, 404, 405–406 International Copper Study Group (ICSG), 115 International Energy Agency (IEA), 341–342, 344 International Maritime Bureau, 361 International Sugar Organisation, 403, 410 International Swaps and Derivatives Association (ISDA), 128 In-the-money (ITM) barrier options, two asset, 106 coal swaptions, 353 credit risk, 66 options, 12 vega options, 50 Intrinsic value options, 40 vega options, 51 Inventories agricultural products, 415

commodity valuation, 19 crude oil price, 185 plastic price, 337 repurchase agreements, 439–444 Inventory, base metal price, 130 Investing, 462–497 diversification, 463 market size, 464–465 one to five years, 463 one year, 462–463 over five years, 463 preferred instruments, 464 rationale for, 465–466 Investment banks, 462 commodity markets, 5 forward price curve, 21 gold, 84 gold forward contracts, 96 longer dated maturities, 61 swaps, 10 IOSCO, 4 IPCC. See Intergovernmental Panel on Climate Change Iron ore, 353–367 benchmarks, 7 derivatives, 354–355 freight, 355–362 exotic swaps, 366–367 options, 367 price drivers, 360 swaps, 366–367 Worldscale System, 359–360, 365 futures, 354–355 options, 354–355 price evolution, 354 steel, 7, 120–122, 341 swaps, 8, 354–355 ISDA. See International Swaps and Derivatives Association ISOs. See Independent System Operators ITM. See In-the-money

J Japan Airlines, 65–66 Japan Customs-cleared Crude (JCC), 256 Jenkins, E., 446 Jet fuel, 165, 168 applications, 231 fixed price, 65 fixed rate, 232 hedging crude oil futures, 233–234 gas oil futures, 232–235 options, 235–236 index price, 65 Joint Implementation (JI), 374–375 EU ETS, 383 Jones, S. A., 434, 435, 436

522

K Kaminski, V., 327 Kerb sessions, copper, 126 Kerosene, 165 Knock-in, 14 barrier options, 104–105 two asset, 105 zero premium collars, 458–460 Knock-out, 14, 15 forward contracts, base metal structured options, 149–150 gold American barrier swap, 101–102 Kyoto Protocol, 374–375

L La Niña, 413 LBMA. See London Bullion Markets Association LC. See Letter of Credit LDC. See Local distribution company LDPE. See Low density polyethylene Lead, 123 automotive sector, 139 Leasing capital protected notes, 488 gold, 91–96 LEBA. See London Energy Brokers Association Legal risk, 60 Letter of Credit (LC), 435 Lewis, 26, 27 LIBOR. See London InterBank Offered Rate Light and sweet crude oil, 162–163 Light distillates, 177 Light Louisiana Sweet, 207 Liquefied natural gas (LNG), 1, 237, 245, 249–250, 252 coal, 349 derivatives, 279 electricity, 281 force majeure, 449 freight futures, 366 futures, 279 price, 255–257 drivers, 259–260 storage, 241 Liquidity risk, 59 Lithium, EV, 133–134 Livestock, 1 LME. See London Metal Exchange LMP. See Locational Marginal Pricing LNG. See Liquefied natural gas Load, electricity, 291–292 Load shapes, electricity, 303 Local distribution company (LDC), natural gas, 239 Locational Marginal Pricing (LMP), electricity, 312–313 Locational swaps, gold, 99–100

INDEX Locational trades, OCM, 263 Loco London Price, 79 London Bullion Markets Association (LBMA), 78, 79–81 London Energy Brokers Association (LEBA), 315–316 London Good Delivery Bars, 79 London InterBank Offered Rate (LIBOR), 25 discounts, 35–37, 38–39 fair value, 24 gold FX swaps, 108 price, 92–93 spot deferred forward contracts, 97 yield enhancement, 111 interest rate derivatives, 457–458 swaps, 457 options, 40 London Metal Exchange (LME), 28–29 aluminium, 140 base metals, 122–130 clearinghouse, 127–128 delivery, 128–130 futures, 123–124 gold, 78–81 NASAAC, 139 options, 124 plastics futures, 336 premiums, 137–139 price and contract specification, 124–125 steel, 122 trading, 125–127 London Platinum and Palladium Market (LPPM), 78 London Precious Metals Clearing Limited (LPMCL), 78, 79 Long digital call, 14 Long digital put, 14 Long position worst of structures, 496–497 WTI negative prices, 211 Long-term prices, base-metals, 134 Low density polyethylene (LDPE), 335, 336 LPMCL. See London Precious Metals Clearing Limited LPPM. See London Platinum and Palladium Market

M Macquarie Bank, 6, 18 Managed money, CFTC, 419 Margin, 444–445 Margin financing, 444–445 Marginal cost base metals, 136–137 commodity valuation, 20–21 Mark to market (MTM), options risk management trading, 70

523

Index Marker crude, 191–193 differential, 193–194 Market manipulation cocoa, 424–426 electricity, 288 Market precariousness, convenience yield, 27 Market risk, 58–59 case study, 65–66 crude oil, 196 forward risk management, 64 Marketing year, coffee, 405–406 Mars, 207 MASP. See Monthly Average Settlement Price Massey, J., 295 Masters, B., 472 Maturity base metal basket options, 152 EFPs, 206 electricity, 298 fair value, 22 gold floating and flat rate forwards, 97 jet fuel hedging, 235 options, 12 risk management, 64 OTC, 128 price fixing hedge, 338 short-dated, 60 spot price, 7, 25 supply and offtake agreements, 453 swaps, 10 MBTE. See Methyl tert-butyl ether Mean reversion base metals, 134 commodity valuation, 21 Medium dated maturities, 61 Medium term notes (MTNs), 464 Metal warrants, 138, 435, 451 Metallgesellschaft AG (MG), 74–75 Methane, 165, 237, 334 GHG, 369 Methyl tert-butyl ether (MBTE), 411 MG. See Metallgesellschaft AG MG Refining and Marketing Inc. (MGRM), 74–75 Middle distillates, 177 Min-max, base metal options, 146–147, 148 MON. See Motor Octane Number Monomer plastics, 334 Month contracts, natural gas exchange traded futures, 263 Monthly Average Settlement Price (MASP), LME, 124 Moody’s, 313 Morgan Stanley, 466 Motor Octane Number (MON), 165 MSCI, gold price, 91 MTM. See Mark to market MTNs. See Medium term notes

N Naphtha, 162, 165 applications, 231 monomer plastics, 334 NAR. See Net as received NASA, 368 NASAAC. See North American Special Aluminum Alloy Contract Natenberg, S., 39 National Balancing Point (NBP), natural gas, 253, 262 National Grid, 284 National Grid Gas, 244, 258, 263 National oil companies (NOCs), 163–164, 195 National Transmission System (NTS), natural gas, 239, 240 Nationalism base metal price, 131 crude oil, 187 Nationally determined contribution (NDC), 376 Natural disasters agricultural products, 408 crude oil price, 186 plastics, 337 Natural gas. See also Liquefied natural gas Bermudan options, 277–278 consumption, 248 customers, 241–242 delivery points, 262 deregulation and re-regulation, 242–245 derivatives, 263–279 electricity, 281–282, 296–297, 349 exchange traded futures, 263–266 exporting, 248–249, 259 fixed rate, 277–278 formation, 237 forward contracts, 267–269 hedge funds, 72–74 interconnectors, 240–241 investment banks, 5 measuring, 238 monomer plastics, 334 NPPs, 242 options, 275–278 volatility skew, 53–54 OTC, 262, 266–274 plastics options, 340 price, 250–257 coal, 350 drivers, 257–260 plastics, 337 production, 246–247 proved reserves, 257–258 relative importance, 245–246 reserves, 246 risk management, 251, 260 R/P, 248 security, 259

524 Natural gas. See also Liquefied natural gas (Continued) spread options, 278 spread trades, 72–74 storage, 239, 265 supply, 241 supply chain, 260 swaps, 269–274 swaptions, 275–277 trading, 260–263 UK, 262–263 UK, 244, 282 NBP. See National Balancing Point NDC. See Nationally determined contribution NDFs. See Non-deliverable forwards Negative prices electricity, 298–299 WTI, 211 NERC. See North American Electric Reliability Corporation Net as received (NAR), coal, 348 Net carry, 473 Net present value (NPV) C/T, 18 swaps, 32 NETA. See New Electricity Trading Arrangements Network Code, 245, 262 natural gas, 240 New Electricity Trading Arrangements (NETA), 288 New technology agricultural products, 414 commodity valuation, 20 crude oil, 172 plastic price, 338 New York Mercantile Exchange (NYMEX) crude oil price, 210–211 freight futures, 366 natural gas, 73, 252 swaps, 271 natural gas exchange traded futures, 263–264 Nitrogen oxides, iron ore freight, 361 Nitrous oxide EU ETS, 381 GHG, 369 NOCs. See National oil companies Non-constant volatility, options, 51–57 Non-deliverable forwards (NDFs), gold, 108–109 Non-physical participants (NPPs) coal, 349 natural gas, 242 North American Electric Reliability Corporation (NERC), 289–290 North American Special Aluminum Alloy Contract (NASAAC), 139 North Sea Dated. See Dated Brent NPPs. See Non-physical participants NPV. See Net present value

INDEX NTS. See National Transmission System NYMEX. See New York Mercantile Exchange

O OCM. See On-the-Day Commodity Market Off peak, electricity, 303 Official selling price, crude oil, 193 Offset hedge, plastics, 338, 339 OGA. See Oil and Gas Authority, UK OGCT. See Open Cycle Gas Turbine Oil and Gas Authority, UK (OGA), 244 OIS. See Overnight Index Swap One-off transactions, 7 On-the-Day Commodity Market (OCM), natural gas, 261, 262–263 OPEC. See Organisation for Petroleum Exporting Countries Open Cycle Gas Turbine (OGCT), 282–283 Options, 40. See also specific types agricultural products, 427–429 base metals, combination, 146–149 cash settlement, supply and offtake agreements, 453 commodity markets, 11–13 copper, 126 correlation risk, 65 crude oil, crack spread heading, 226–227 electricity, 321 emissions, 388 fair value, 41, 104 gold, 102–106 heat rate, electricity, 328–331 interbank, 50 iron ore, 354–355 freight, 367 jet fuel hedging, 235–236 LME, 122–123, 124 natural gas, 275–278 non-constant volatility, 51–57 plastics, 340 put-call parity, 43–44 risk management, 42, 64–65 measurement, 44–57 trading, 69–75 underlying price, 40 valuation, 39–44 volatility term structure, 54–57 weather, 392 Organisation for Petroleum Exporting Countries (OPEC), 187–188, 192–193 OTC. See Over-the-counter Out-of-the-money (OTM) barrier options, 15 two asset, 106 base metal short options, 144–146 synthetic long put, 142 call options, supply and offtake agreements, 453

Index coal swaptions, 353 credit risk, 66 gold yield enhancement, 111 income structures, 491 options, 12, 42 non-constant volatility, 51 risk management trading, 70 volatility skew, 52 prepaid variable forwards, 446–447 vega options, 50–51 zero premium collars, 393 Outperformance gold, 495–496 notes, 495–496 options, 13 Overnight Index Swap (OIS), 34 discounting, 37–38 Overnights, electricity, 303 Over-the-counter (OTC) agricultural products, 426–432 Brent forward contract, 201 coal swaps, 349, 351–352 swaptions, 352–353 crude oil crack spread hedging, 225–226, 227 electricity, 302, 308 emissions, 385 forward contracts, 8, 9 gold, 78 LME, 123, 128 natural gas, 262, 266–274 plastics options, 340 weather, 391 Ownership, financing, 434

P Palladium, 76 automotive sector, 139 correlation risk management, 65 EVs, 133 Palm oil, 398–401 Panamax/Kamsarmax, iron ore freight, 355, 356 Paraffinic crude oil, 162 Paris Agreement, 376 PCW. See PetroChem Wire PE. See Polyethylene Peak load, electricity, 303 Peanuts, 418 Pentane, 334 Perfluorocarbons (PFCs), 369 EU ETS, 381 PET. See Polyethylene terephthalate PetroChem Wire (PCW), 336 PFCs. See Perfluorocarbons PGMs. See Platinum Group Metals Pipelines, natural gas, 239–240

525 Piracy crude oil freight, 186 iron ore freight, 361 Plastics applications, 335 chemistry, 332–333 forward contracts, 338–340 futures, LME, 336 monomers, 334 offset hedge, 339 options, 340 polymerisation, 334 price determination, 336 drivers, 337–338 production, 333 proxy hedge, 339–340 supply chain, 336 swaps, 338–340 Platinum automotive sector, 139 correlation risk management, 65 Platinum Group Metals (PGMs), 76 fixed value, 80 Polyethylene (PE), 335 Polyethylene terephthalate (PET), 335 Polymerisation, plastics, 334 Polypropylene (PP), 335, 336 Polystyrene (PS), 335 Polytetrafluoroethylene (PTFE), 335 Polyvinyl chloride (PVC), 335 Pools, electricity, 285–286 Popcorn spread, 421 Population growth, agricultural products, 415–416 Position risk, 450 Possession, financing, 434 Pour point, crude oil, 162 Power and natural gas, 1 PP. See Polypropylene PRAs. See Price reporting agencies Precious metals, 1. See also Gold LME futures, 124 spreads, 68 Premiums avros, 17 barrier options, 104–105 base metals, 137–139 basket options, 154 binary options, 14 coffee, 408 delta options, 44–47 LME, 137–139 options, 12, 39, 40–41 volatility term structure, 54–57 risk, 467–468 theta options, 48–49 Prepaid variable forwards, 446–449 Prepay structures, financing, 445–446

526 Present value (PV). See also Net present value aluminium, 154 cash flow, 446 LIBOR discounting, 35, 37 prepay structures, 446 Price arbitrage, 6 Price fixing hedge, 338–339 Price indexes natural gas, 252 PRA, 5 swaps, 10 Price inelasticity, commodity valuation, 20 Price reporting agencies (PRAs), commodity markets, 4–5 Price risk, crude oil, 212–236 Probability of exercise, delta options, 44, 46 Product substitution agricultural products, 415 base metal price, 131 commodity valuation, 20 crude oil, 172, 181 Production costs base metal price, 131 crude oil, 184 Production disruption, base meta1 price, 130 Profitability, 37 aluminium, 30 carry trade, 450 crude oil, 169–172 Project finance, 437–439 Propane, 165, 334 Protectionism agricultural products, 417 base metal price, 131 Proved reserves coal, 343 crude oil, 172, 173 price driver, 180 natural gas, 257–258 Proxy hedge cocoa, 425–426 crude oil, 212 plastics, 339–340 PS. See Polystyrene PTFE. See Polytetrafluoroethylene Put options, 12 agricultural products, 429 avros, 16 gamma, 48 gold convertible forwards, 97 put-call parity, 43–44 vanilla, 102–103 weather, 393 Put-call parity, 43–44 PV. See Present value PVC. See Polyvinyl chloride

INDEX

Q Quality arbitrage (technical arbitrage), forward price curve, 31 Quality risk, 450 Quality swaps, gold, 99–100 Quarter contracts, natural gas exchange traded futures, 263

R Ratio min-max, base metal options, 147, 148 RBOB. See Reformulated Gasoline Blendstock for Oxygen Blending RC. See Refining costs Real money accounts, 462 commodity markets, 6 Recycling, plastic price, 337 Red coal, 342 Refined products, 1 applications, 231 avros, 16–17 backwardation, 25 commodity trading houses, 6 crude oil hedging, 230–236 forward price curve, 21, 27 investment banks, 5 nonhomogeneity of, 2 options volatility term structure, 55–56 PRAs, 4 swaps, 10, 32, 35 volatility skew, 51–52 Refining costs (RC), LME, 124 Reformulated Gasoline Blendstock for Oxygen Blending (RBOB), 209 Regional Transmission Organisations (RTOs), electricity, 289 Relative value trades, 463 Religion, agricultural products, 416 Remargining, 443 Repurchase agreements crude oil, 440–443 emissions, 385–386 hedging, 71 inventories, 439–444 Research Octane Number (RON), 165 Reserves to Production (R/P), 172–174 coal, 343 natural gas, 248 Reverse convertibles, 492–493 Rhodium, 76 EVs, 133 PRAs, 4 Rice, 418 Ring sessions, copper, 125, 126 Risk Magazine, 25, 42 Risk management. See also specific risk types base metal, 74–75 coffee, 408

527

Index financing, 449–450 futures, 9 hedge funds, 72–74 hedging corporations, 61–63 customers, 63–66 natural gas, 251, 260 options, 42, 64–65 measurement, 44–57 principles, 58–75 steel, 122 swaps, 64 trading, 66–75 forward price, 67–68 gamma options, 71 options, 69–75 spot price, 67 swaps, 68 vega options, 69 Risk premium, 467–468 Risk transference, swaps, 10 Robusta coffee, 404 Roll yield, 471–476 Rolling process, WTI negative prices, 211 RON. See Research Octane Number Ross, Gary, 185 R/P. See Reserves to Production RTOs. See Regional Transmission Organisations Rubber, 418 Rumsfeld, Donald, 172

S SCA. See Specialty Coffee Association Scaroni, Paolo, 179 Schofield, N. C., 324 Scrubbing systems, iron ore freight, 361 Season contracts, natural gas exchange traded futures, 263 Seasonality commodity valuation, 19 crude oil, 172 iron ore freight, 362 natural gas, 258, 259 Secured Overnight Financing Rate (SOFR), 438, 457 Security, natural gas, 259 Sell buyback, 440n1 Semi-fabricators copper, 117, 119 LME, 124 Shale gas, 247 Shanghai Futures Exchange (SHFE), 28–29 Shape change, forward price curve, 135 SHFE. See Shanghai Futures Exchange Shimko, D., 472 Shipping. See Freight Short dated maturities, 60 Short options, base metals, 144–146 Silver, 1

fixed value, 80 Singapore Exchange, iron ore, 354, 356–357 Singapore futures exchange, 341 Slope change, forward price curve, 135 Slope of price line delta options, 44, 46 theta options, 48 Smithson, Charles, 63 SMP. See System marginal price SOFR. See Secured Overnight Financing Rate Soft commodities, 1 cocoa, 408–409 coffee, 1, 20, 403–408 sugar, 403 Solar energy, 281, 297 SONIA. See Sterling Overnight Index Average Souleles, N., 480 Sovereign Wealth Funds, 462 Soybeans, 401–403 S&P Global Platts, 200

®

S&P GSCI , 183 S&P Platts crude oil, 193, 194, 199 electricity, 327 refined products, 230, 231 Spall, Jonathan, 81, 88 Spark spreads, 68 electricity, 299–301 Specialty Coffee Association (SCA), 404 Specialty markets, 1 Specialty products, crude oil, 165 Speculation agricultural products, 418 crude oil price, 183 fair value, 183 Spot deferred, gold forward contracts, 97 Spot index, 470 Spot price, 7–8 barrier options, 15 capital protected notes, 487–488 coffee, 408 electricity, 297–298 emissions, 384 exchange traded futures, 7 forward contracts, 8 forward price curve, 24, 25, 26, 27, 29 gold, 91, 487–488 ITM, 12 maturity, 7, 25 natural gas, 252 options, 11, 39, 40 project finance, 438 risk management trading, 67 roll yield, 471–476 swaps, 10 theta options, 48 vega options, 50 Spread options, 16

528 Spread options (Continued) agricultural products, 422, 427–429 electricity, 319 natural gas, 278 Spread trades crude oil, 197–198 natural gas, 72–74 Starbucks, 407, 408 Steam (thermal) coal, 342 Steam cracking, 334 Steel automotive sector, 139 coal, 341 freight, 121 iron ore, 7, 120–122, 341 price, 121 risk management, 122 Sterling Overnight Index Average (SONIA), 457 Stocks to use ratio, 394 Storage, 3 crude oil, 31, 163 gold, 79 LNG, 241 natural gas, 239, 241, 258, 259, 260, 265 trading houses, 5 Store of value assets, 18 Strike price avros, 16 base metal basket options, 152 binary options, 14 electricity CFD, 318 electricity options, 321 options, 11, 12, 39, 40 risk management, 64 spread options, 16 underlying price, 12 Structured options, base metals, 149–154 Structured products, 486–497 Structured repo, 443 Sturm, F. J., 272 Sugar, 403 ethanol, 409–412 Sulfur, iron ore freight, 361 Sulfur hexafluoride, 369 Supply and offtake agreements, 451–453 Supply chain agricultural products, 395–402 coal, 346–349 coffee, 406 commodity markets, 3–4 copper, 116–117 crude oil, 163–164 price driver, 184–187 price risk, 212–236 electricity, 283–285 ethanol, 411–412 gold, 76 natural gas, 238–242, 260

INDEX plastics, 336 trading houses, 5 Supramax/Ultramax, iron ore freight, 355 Swaps. See also specific types agricultural products, 426–427 CFTC, 419 coal, 349, 351–352 commodity markets, 10–11 crude oil, 32, 216–218 crack spread OTC hedging, 225–226, 227 electricity, 315–317 emissions, 386–387 ETF, 484 fixed rate, 10–11, 32–33, 36, 223–224, 226 FX base metals, 156–157 gold, 106–109 gold, 98–102, 106–109 interest rates, 460–461 iron ore, 8, 354–355 iron ore freight, 366–367 jet fuel heading, 234–235 natural gas, 269–274 plastics, 338–340 risk management, 64 risk management trading, 68 TRS, 464, 477–479 valuation, 32–39 weather, 391–392 Swaptions base metals, 146 coal, 352–353 electricity, 318–319, 323–325 natural gas, 275–277 Swing, natural gas, 240, 272 Synthetic long put, base metals, 142–144 System marginal price (SMP), natural gas, 263, 267

T TAN. See Total Acid Number Tapis/Oman, 191 TAPOs. See Traded Average Price Options Target redemption structures (TARNs), 429–432 Taxation crude oil price, 182 EU ETS, 383–384 TC. See Time charter; Treatment charges Technical arbitrage (quality arbitrage), forward price curve, 31 Thermal (steam) coal, 342 Thermoplastics, 335 Theta options, 48–49 electricity, 321 Three way, base metal options, 147–149 Tick size, 390 Tidal energy, 281 Till, H., 472 Time arbitrage, forward price curve, 29–30

529

Index Time charter (TC), iron ore freight, 356, 364 Time value, options, 40–41 Title trades, OCM, 263 Title Transfer Facility (TTF), natural gas, 253 Tompkins, R., 39, 43, 49–50 Total Acid Number (TAN), 161 Total contracted volume, electricity, 304 Total return (TR) index, 470 Total return swaps (TRS), 464, 477–479 TPA. See Tri-party agreements TR. See Total return index; Trust Receipt Traded Average Price Options (TAPOs), LME, 124 Trading copper, 117–119 crude oil, 176–177, 195–212 electricity, 301–313 gold, 106–110 LME, 125–127 natural gas, 260–263 UK, 262–263 risk management, 66–75 forward price, 67–68 gamma options, 71 options, 69–75 spot price, 67 swaps, 68 Trading advisors, 60, 462 agriculture products, 419 crude oil, 183 Trading houses agricultural products, 416 commodity markets, 5–6 crude oil, 195 gold, 77, 84 short dated maturities, 60 Trafigura, 2, 31 Transmission System Operator (TSO) electricity, 284 natural gas, 240, 260 Transportation. See also Freight agricultural products, 414 for commodity market, 3 crude oil price, 182, 186 Treatment charges (TC), LME, 124 Tri-party agreements (TPA), 444–445 TRS. See Total return swaps Trust Receipt (TR), 434 TSO. See Transmission System Operator TTF. See Title Transfer Facility Two asset barrier options, 105–106 crude oil, 220–223

U UK. See United Kingdom ULCC. See Ultra Large Crude Carrier ULSD. See Ultra Low Sulphur Diesel Ultra Large Crude Carrier (ULCC), 164, 209 iron ore freight, 356, 362

Ultra Low Sulphur Diesel (ULSD), 197 Underlying price agricultural product swaps, 426 call options, 44–45 delta options, 44 electricity swaptions, 323 gamma options, 48 gold, 13 natural gas, 328 options, 40 risk management, 64 strike price, 12 swaps, 10 vanilla call option, 235 UNFCCC. See United Nations Framework Convention on Climate Change United Kingdom (UK) electricity, 284, 288 trading conventions, 309–310 natural gas, 244, 282 trading, 262–263 United Nations Framework Convention on Climate Change (UNFCCC), 375 United States (US) electricity, 288–289 traded markets, 310–313 wholesale markets, 290 ethanol, 411 sugar, 403 wheat, 396 Up and out contract, 15 Urals, 162, 169, 191, 217, 218 US. See United States US dollar (USD). See also specific topics crude oil, 183 gold American barrier reset swaps, 100–102 forward contracts, 98 price and, 90, 91, 92–93 hedging, 467–468 plastic price, 338 US Geological Service (USGS), iron ore, 353–354

V Valemax, iron ore freight, 355 Vanilla call option gold, 97 underlying price, 235 Vanilla FX hedge, base metals, 154–156 Vanilla interest rate swap, 456 Vanilla options base metals, 141–142 coal, 349 crude oil, 454–455 financing, 454–456 Vanilla put options, 102–103 reverse convertibles, 493 Vanilla swaps

530 Vanilla swaps (Continued) agricultural products, 427 natural gas, 270 VC. See Voyage charter Vega options, 49–51 electricity, 321 plastics, 340 risk management, 69 Very Large Crude Carrier (VLCC), 164, 186 iron ore freight, 356 Vichichi, Fabrizio, 409 Viscosity, crude oil, 162 VLCC. See Very Large Crude Carrier Volatility. See also Implied volatility cash flow, longer dated maturities, 61 risk premium, 468 skew, options, 51–52 term structure, options, 54–57 Volume per settlement period, electricity, 304 Voyage charter (VC), iron ore freight, 356, 363

W Wall Street Journal, 184 Ward, Anthony, 424 Warehouse receipt, 435–436 Wave energy, 281 WCI. See World Coal Institute Weather, 1 agricultural products, 412–413 call options, 392 crude oil, 183–184 derivatives, 388–393 electricity, 294, 393 exchange traded futures, 389–390 natural gas, 258, 259 options, 392 OTC, 391 plastic price, 337 put options, 393 swaps, 391–392

INDEX West Texas Intermediate (WTI), 10, 169, 191, 192, 193 exchange traded futures, 213–215 negative prices, 211 price relationship, 196, 197 trading, 207 volatility skew, 51–52 West Texas Sour (WTS), 169, 207 Wheat, 396, 397 White products, 164 Widow maker, 73 Wind energy, 281, 297 WisdomTree, 482 Working capital, financing, 439–453 World Coal Institute (WCI), 341 Worldscale System, 359–360 iron ore freight, 365 Worst of structures, 496–497 Wrong way risk, 449 WTI. See West Texas Intermediate WTS. See West Texas Sour

Y Yield enhancement gold price, 111–112 notes, 463 reverse convertible, 492

Z Zero coupons capital protected notes, 486–488 income structures, 491 longer dated maturities, 61 swaps, 34 Zero premium collars, 146, 319, 367 knock-in, 458–460 OTM, 393 prepaid variable forwards, 446 Zinc, 6 automotive sector, 139 brass and, 117 steel, 121, 139

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