Preface xix
Acknowledgements xxiii
About the Editors xxv
List of Contributors xxvii
Part One Commodity Markets and Products
Chapter 1 Oil Markets and Products 3
Cristiano Campi and Francesco Galdenzi
1.1 Introduction 3
1.2 Risk Management for Corporations: Hedging Using Derivative Instruments 4
1.2.1 Crude Oil and Oil Products Risk Management for Corporations 4
1.2.2 Aviation: Risk Profile and Hedging Strategies 11
1.2.3 Shipping: Risk Profile and Hedging Strategies 20
1.2.4 Land Transportation: Risk Profile and Hedging Strategies 27
1.2.5 Utilities: Risk Profile and Hedging Strategies 32
1.2.6 Refineries: Risk Profile and Hedging Strategies 35
1.2.7 Industrial Consumers: Risk Profile and Hedging Strategies 40
1.3 Oil Physical Market Hedging and Trading 41
1.3.1 The Actors, Futures and OTC Prices 41
1.3.2 The Most Commonly Used Financial Instruments 45
1.3.3 How to Monitor and Manage Risk 49
1.3.4 How to Create a Market View 52
1.3.5 Trading Strategies to Maximize a Market View 54
Further Reading 66
Chapter 2 Coal Markets and Products 67
Lars Schernikau
2.1 Introduction 67
2.2 Source of Coal - Synopsis of the Resource Coal 72
2.2.1 The Fundamentals of Energy Sources and Fossil Fuels 72
2.2.2 Process of Coal Formation 74
2.2.3 Coal Classification 74
2.2.4 Reserves and Resources 79
2.2.5 Coal Mining and Production 83
2.3 Use of Coal - Power Generation and More 90
2.3.1 Steam Coal and its Role in Power Generation 91
2.3.2 Coal-Fired Power Plant Technologies 93
2.3.3 Cement and Other Industry 95
2.3.4 Alternatives to Coal: Shale Gas and Other 95
2.3.5 Future Trend: CtL and Coal Bed Methane 101
2.4 Overview of Worldwide Steam Coal Supply and Demand 102
2.4.1 Atlantic Demand Market: Europe at its Core 102
2.4.2 Pacific Demand Market: China, India, Japan, Taiwan, Korea and SEA 104
2.4.3 Steam Coal Supply Regions: ID, AU, USA, SA, RU, CO and Others 107
2.4.4 Seaborne Freight 116
2.4.5 Geopolitical and Policy Environment 118
2.5 The Global Steam Coal Trade Market and its Future 121
2.5.1 Current and Future Market Dynamics of the Coal Trade 121
2.5.2 Future Steam Coal Price Trends 125
2.5.3 Future Source of Energy: What Role Will Coal Play? 127
2.6 Concluding Words 129
Abbreviations and Definitions 130
Acknowledgements 132
References 132
Chapter 3 Natural Gas Markets and Products 135
Mark Cummins and Bernard Murphy
3.1 Physical Natural Gas Markets 135
3.1.1 Physical Structure 141
3.1.2 Natural Gas Market Hubs and Main Participants 146
3.1.3 Liquefied Natural Gas 147
3.1.4 Shale Gas 149
3.2 Natural Gas Contracting and Pricing 154
3.2.1 Natural Gas Price Formation 155
3.3 Financial Natural Gas Markets 158
3.3.1 Exchange-Based Markets 158
3.3.2 Natural Gas Futures 159
3.3.3 Natural Gas Options 172
3.3.4 OTC Markets and Products 179
References 180
Chapter 4 Electricity Markets and Products 181
Stefano Fiorenzani, Bernard Murphy and Mark Cummins
4.1 Market Structure and Price Components 181
4.1.1 Spot and Forward Markets 181
4.1.2 Supply and Demand Interaction 183
4.1.3 Electricity Derivatives 186
4.1.4 Power Price Models 189
4.1.5 Spot Price Analysis (IPEX Case) 196
4.1.6 Forward Price Analysis (EEX Case) 200
4.2 Renewables, Intra-Day Trading and Capacity Markets 205
4.2.1 Renewables Expansion Targets 205
4.2.2 Growth in Intra-Day Trading 206
4.2.3 Implications for Future Price Volatility and Price Profiles 207
4.2.4 Reforms and Innovations in Capacity Markets 209
4.2.5 Provision and Remuneration of Flexibility - Storage Assets 212
4.3 Risk Measures for Power Portfolios 216
4.3.1 Value-Based Risk Measures 216
4.3.2 Flow-Based Risk Measures 218
4.3.3 Credit Risk for Power Portfolios 220
References 221
Further Reading 221
Chapter 5 Emissions Markets and Products 223
Marc Chesney, Luca Taschini and Jonathan Gheyssens
5.1 Introduction 223
5.2 Climate Change and the Economics of Externalities 224
5.2.1 The Climate Change Issue 224
5.2.2 The Economics of Externality and GHG Pollution 226
5.3 The Kyoto Protocol 227
5.3.1 The United Nations Framework Convention on Climate Change 227
5.3.2 The Conference of Parties and the Subsidiary Bodies 229
5.3.3 The Kyoto Protocol 229
5.3.4 The Road to Paris 231
5.4 The EU ETS 232
5.4.1 Institutional Features 232
5.4.2 Allocation Criteria 234
5.4.3 Market Players and the Permit Markets 236
5.4.4 The Future of the EU ETS 238
5.5 Regional Markets: A Fragmented Landscape 239
5.5.1 Regional Markets 239
5.5.2 Voluntary Markets 240
5.6 A New Asset Class: CO2 Emission Permits 241
5.6.1 Macroeconomic Models 242
5.6.2 Econometric Investigation of CO2 Permit Price Time-Series 243
5.6.3 Stochastic Equilibrium Models 251
Abbreviations 252
References 252
Chapter 6 Weather Risk and Weather Derivatives 255
Alessandro Mauro
6.1 Introduction 255
6.2 Identification of Volumetric Risk 257
6.2.1 Weather Events on the Demand Curve 258
6.2.2 Weather Events on the Supply Curve 260
6.2.3 Risk Measurement and Weather-at-Risk 262
6.3 Atmospheric Temperature and Natural Gas Market 264
6.3.1 Characterization of the Air Temperature Meteorological Variable 264
6.3.2 Degree Days 267
6.3.3 Volumetric Risk in the Natural Gas Market 270
6.4 Modification of Weather Risk Exposure with Weather Derivatives 272
6.4.1 Weather Derivatives for Temperature-Related Risk 273
6.5 Conclusions 276
Nomenclature 277
References 277
Chapter 7 Industrial Metals Markets and Products 279
Alessandro Porru
7.1 General Overview 279
7.1.1 Brief History of the LME 280
7.1.2 Non-ferrous Metals 282
7.1.3 Other Metals 291
7.1.4 LME Instruments 292
7.1.5 OTC Instruments 298
7.1.6 A New Player: The Investor 301
7.2 Forward Curves 305
7.2.1 Building LME's Curves in Practice 308
7.2.2 Interpolation 313
7.2.3 LME, COMEX and SHFE Copper Curve and Arbitrage 314
7.2.4 Contango Limit... 318
7.2.5 ...and No-Limit Backwardation 324
7.2.6 Hedging the Curve in Practice 328
7.3 Volatility 337
7.3.1 A European Disguised as an American 338
7.3.2 LME's Closing Volatilities 339
7.3.3 Sticky Strike, Sticky Delta and Skew 342
7.3.4 Building the Surface in Practice 345
7.3.5 Considerations on Vega Hedging 348
Acknowledgements 352
References 353
Further Reading 353
Chapter 8 Freight Markets and Products 355
Manolis G. Kavussanos, Ilias D. Visvikis and Dimitris N. Dimitrakopoulos
8.1 Introduction 355
8.2 Business Risks in Shipping 356
8.2.1 The Sources of Risk in the Shipping Industry 356
8.2.2 Market Segmentation in the Shipping Industry 358
8.2.3 Empirical Regularities in Freight Rate Markets 359
8.2.4 Traditional Risk Management Strategies 365
8.3 Freight Rate Derivatives 366
8.3.1 Risk Management in Shipping 366
8.3.2 The Underlying Indices of Freight Rate Derivatives 366
8.3.3 The Freight Derivatives Market 372
8.3.4 Examples of Freight Derivatives Trading 380
8.4 Pricing, Hedging and Freight Rate Risk Measurement 382
8.4.1 Pricing and Hedging Effectiveness of Freight Derivatives 382
8.4.2 Value-at-Risk (VaR) in Freight Markets 384
8.4.3 Expected Shortfall (ES) in Freight Markets 389
8.4.4 Empirical Evidence on Freight Derivatives 390
8.5 Other Derivatives for the Shipping Industry 393
8.5.1 Bunker Fuel Derivatives 393
8.5.2 Vessel Value Derivatives 395
8.5.3 Foreign Exchange Rate Derivatives Contracts 395
8.5.4 Interest Rate Derivatives Contracts 396
8.6 Conclusion 396
Acknowledgements 396
References 397
Chapter 9 Agricultural and Soft Markets 399
Francis Declerk
9.1 Introduction: Stakes and Objectives 399
9.1.1 Stakes 399
9.1.2 Objectives 399
9.2 Agricultural Commodity Specificity and Futures Markets 400
9.2.1 Agricultural Commodity Specificity 400
9.2.2 Volatility of Agricultural Markets 402
9.2.3 Forward Contract and Futures Contract 402
9.2.4 Major Agricultural Futures Markets and Contracts 404
9.2.5 Roles of Futures Markets 405
9.2.6 Institutions Related to Futures Markets 406
9.2.7 Commodity Futures Contracts 406
9.2.8 The Operators 408
9.2.9 Monitoring Hedging: Settlement 409
9.2.10 Accounting and Tax Rules 409
9.3 Demand and Supply, Price Determinants and Dynamics 409
9.3.1 Supply and Demand for Agricultural Commodities: The Determinants 409
9.3.2 Agricultural Market Prices, Failures and Policies 413
9.3.3 The Price Dynamics of Seasonal and Storable Agricultural Commodities 416
9.3.4 The Features of Major Agricultural and Soft Markets 417
9.4 Hedging and Basis Management 466
9.4.1 Short Hedging for Producers 466
9.4.2 Long Hedging for Processors 469
9.4.3 Management of Basis Risk 471
9.5 The Financialization of Agricultural Markets and Hunger: Speculation and Regulation 480
9.5.1 Factors Affecting the Volatility of Agricultural Commodity Prices 480
9.5.2 Financialization: Impact of Non-commercial Traders on Market Price 483
9.5.3 The Financialization of Grain Markets and Speculation 484
9.5.4 Bubble or Not, Agricultural Commodities have Become an Asset Class 489
9.5.5 Price Volatility and Regulation 490
9.5.6 Ongoing Research about Speculation and Regulation 493
9.6 Conclusion about Hedging and Futures Contracts 493
9.6.1 Hedging Process 493
9.6.2 Key Success Factors for Agricultural Commodity Futures Contracts 494
9.6.3 Conclusion and Prospects 495
References 495
Further Reading 496
Glossary, Quotations and Policy on Websites 497
Chapter 10 Foreign Exchange Markets and Products 499
Antonio Castagna
10.1 The FX Market 499
10.1.1 FX Rates and Spot Contracts 499
10.1.2 Outright and FX Swap Contracts 500
10.1.3 FX Option Contracts 504
10.1.4 Main Traded FX Options Structures 507
10.2 Pricing Models for FX Options 509
10.2.1 The Black-Scholes Model 510
10.3 The Volatility Surface 511
10.4 Barrier Options 512
10.4.1 A Taxonomy of Barrier Options 512
10.5 Sources of FX Risk Exposure 513
10.6 Hedging FX Exposures Embedded in Energy and Commodity Contracts 517
10.6.1 FX Forward Exposures and Conversions 518
10.6.2 FX-Linked Energy Contracts 522
10.7 Typical Hedging Structures for FX Risk Exposure 533
10.7.1 Collar Plain Vanilla 533
10.7.2 Leveraged Forward 536
10.7.3 Participating Forward 538
10.7.4 Knock-Out Forward 540
10.7.5 Knock-In Forward 543
10.7.6 Knock-In Knock-out Forward 545
10.7.7 Resettable Forward 548
10.7.8 Range Resettable Forward 550
References 553
Part Two Quantitative Topics
Chapter 11 An Introduction to Stochastic Calculus with Matlab (R) Examples 557
Laura Ballotta and Gianluca Fusai
11.1 Brownian Motion 558
11.1.1 Defining Brownian Motion 558
11.2 The Stochastic Integral and Stochastic Differential Equations 566
11.2.1 Introduction 566
11.2.2 Defining the Stochastic Integral 567
11.2.3 The It Stochastic Integral as a Mean Square Limit of Suitable Riemann-Stieltjes Sums 567
11.2.4 A Motivating Example: Computing 0tW(s)dW(s) 568
11.2.5 Properties of the Stochastic Integral 569
11.2.6 Ito Process and Stochastic Differential Equations 571
11.2.7 Solving Stochastic Integrals and/or Stochastic Differential Equations 573
11.3 Introducing Ito's Formula 575
11.3.1 A Fact from Ordinary Calculus 576
11.3.2 Ito's Formula when Y = g(x), g(x) C2 576
11.3.3 Guiding Principle 577
11.3.4 Ito's Formula when Y(t) = g(t, X), g(t, X) C1,2 577
11.3.5 The Multivariate Ito's Lemma when Z = g(t, X, Y) 578
11.4 Important SDEs 581
11.4.1 The Geometric Brownian Motion GBM(𝜇, 𝜎) 581
11.4.2 The Vasicek Mean-Reverting Process 588
11.4.3 The Cox-Ingersoll-Ross (CIR) Model 595
11.4.4 The Constant Elasticity of Variance (CEV) Model 604
11.4.5 The Brownian Bridge 607
11.4.6 The Stochastic Volatility Heston Model (1987) 611
11.5 Stochastic Processes with Jumps 618
11.5.1 Preliminaries 618
11.5.2 Jump Diffusion Processes 623
11.5.3 Time-Changed Brownian Motion 628
11.5.4 Final Remark: Levy Processes 632
References 633
Further Reading 633
Chapter 12 Estimating Commodity Term Structure Volatilities 635
Andrea Roncoroni, Rachid Id Brik and Mark Cummins
12.1 Introduction 635
12.2 Model Estimation Using the Kalman Filter 635
12.2.1 Description of the Methodology 636
12.2.2 Case Study: Estimating Parameters on Crude Oil 642
12.3 Principal Components Analysis 646
12.3.1 PCA: Technical Presentation 647
12.3.2 Case Study: Risk Analysis on Energy Markets 651
12.4 Conclusion 655
Appendix 655
References 657
Chapter 13 Nonparametric Estimation of Energy and Commodity Price Processes 659
Gianna Fig`a-Talamanca and Andrea Roncoroni
13.1 Introduction 659
13.2 Estimation Method 660
13.3 Empirical Results 663
References 672
Chapter 14 How to Build Electricity Forward Curves 673
Ruggero Caldana, Gianluca Fusai and Andrea Roncoroni
14.1 Introduction 673
14.2 Review of the Literature 674
14.3 Electricity Forward Contracts 675
14.4 Smoothing Forward Price Curves 677
14.5 An Illustrative Example: Daily Forward Curve 679
14.6 Conclusion 684
References 684
Chapter 15 GARCH Models for Commodity Markets 687
Eduardo Rossi and Filippo Spazzini
15.1 Introduction 687
15.2 The GARCH Model: General Definition 690
15.2.1 The ARCH(q) Model 692
15.2.2 The GARCH(p,q) Model 693
15.2.3 The Yule-Walker Equations for the Squared Process 695
15.2.4 Stationarity of the GARCH(p,q) 696
15.2.5 Forecasting Volatility with GARCH 698
15.3 The IGARCH(p,q) Model 699
15.4 A Permanent and Transitory Component Model of Volatility 700
15.5 Asymmetric Models 702
15.5.1 The EGARCH(p,q) Model 702
15.5.2 Other Asymmetric Models 704
15.5.3 The News Impact Curve 706
15.6 Periodic GARCH 707
15.6.1 Periodic EGARCH 708
15.7 Nesting Models 708
15.8 Long-Memory GARCH Models 713
15.8.1 The FIGARCH Model 716
15.8.2 The FIEGARCH Model 719
15.9 Estimation 720
15.9.1 Likelihood Computation 720
15.10 Inference 722
15.10.1 Testing for ARCH Effects 722
15.10.2 Test for Asymmetric Effects 723
15.11 Multivariate GARCH 725
15.11.1 BEKK Parameterization of MGARCH 726
15.11.2 The Dynamic Conditional Correlation Model 726
15.12 Empirical Applications 727
15.12.1 Univariate Volatility Modelling 727
15.12.2 A Simple Risk Measurement Application: A Bivariate Example with Copulas 733
15.13 Software 740
References 748
Chapter 16 Pricing Commodity Swaps with Counterparty Credit Risk: The Case of Credit Value Adjustment 755
Marina Marena, Gianluca Fusai and Chiara Quaglini
16.1 Introduction 755
16.1.1 Energy Company Strategies in Derivative Instruments 755
16.2 Company Energy Policy 756
16.2.1 Commodity Risk 756
16.2.2 Credit Risk 757
16.3 A Focus on Commodity Swap Contracts 758
16.3.1 Definition and Main Features of a Commodity Swap 758
16.4 Modelling the Dynamics of Oil Spot Prices and the Forward Curve 760
16.4.1 The Schwartz and Smith Pricing Model 760
16.5 An Empirical Application 764
16.5.1 The Commodity Swap Features 764
16.5.2 Calibration of the Theoretical Schwartz and Smith Forward Curve 765
16.5.3 The Monte Carlo Simulation of Oil Spot Prices 772
16.5.4 The Computation of Brent Forward Curves at Any Given Valuation Date 773
16.6 Measuring Counterparty Risk 777
16.6.1 CVA Calculation 779
16.6.2 Swap Fixed Price Adjustment for Counterparty Risk 782
16.6.3 Right- and Wrong-Way Risk 784
16.7 Sensitivity Analysis 788
16.8 Accounting for Derivatives and Credit Value Adjustments 788
16.8.1 Example of Hedge Effectiveness 791
16.8.2 Accounting for CVA 796
16.9 Conclusions 797
References 798
Further Reading 798
Chapter 17 Pricing Energy Spread Options 801
Fred Espen Benth and Hanna Zdanowicz
17.1 Spread Options in Energy Markets 801
17.2 Pricing of Spread Options with Zero Strike 805
17.3 Issues of hedging 813
17.4 Pricing of Spread Options with Nonzero Strike 815
17.4.1 Kirk's Approximation Formula 817
17.4.2 Approximation by Margrabe Based on Taylor Expansion 820
17.4.3 Other Pricing Methods 823
Acknowledgement 824
References 825
Chapter 18 Asian Options: Payoffs and Pricing Models 827
Gianluca Fusai, Marina Marena and Giovanni Longo
18.1 Payoff Structures 832
18.2 Pricing Asian Options in the Lognormal Setting 833
18.2.1 Moment Matching 835
18.2.2 Lower Price Bound 844
18.2.3 Monte carlo simulation 845
18.3 A Comparison 856
18.4 The Flexible Square-Root Model 858
18.4.1 General Setup 861
18.4.2 Numerical Results 870
18.4.3 A Case Study 871
18.5 Conclusions 874
References 874
Chapter 19 Natural Gas Storage Modelling 877
Alvaro Cartea, James Cheeseman and Sebastian Jaimungal
19.1 Introduction 877
19.2 A Simple Model of Storage, Futures Prices, Spot Prices And Convenience Yield 878
19.3 Valuation of Gas Storage 880
19.3.1 Least-Squares Monte Carlo 881
19.3.2 LSMC Greeks 883
19.3.3 Extending the LSMC to Price Gas Storage 883
19.3.4 Toy Storage Model 884
19.3.5 Storage LSMC 888
19.3.6 Swing Options 890
19.3.7 Closed-Form Storage Solution 891
19.3.8 Monte Carlo Convergence 892
19.3.9 Simulated Storage Operations 894
19.3.10 Storage Value 897
References 899
Chapter 20 Commodity-Linked Arbitrage Strategies and Portfolio Management 901
Viviana Fanelli
20.1 Commodity-Linked Arbitrage Strategies 902
20.1.1 The Efficient Market Hypothesis 902
20.1.2 Risk Arbitrage Opportunities in Commodity Markets 903
20.1.3 Basic Quantitative Trading Strategies 906
20.1.4 A General Statistical Arbitrage Trading Methodology 914
20.2 Portfolio Optimization with Commodities 921
20.2.1 Commodities as an Asset Class 921
20.2.2 Commodity Futures Return Characteristics 923
20.2.3 Risk Premiums in Commodity Markets 925
20.2.4 Commodities as a Portfolio Diversifier 928
20.2.5 Risk-Return Optimization in Commodity Portfolios 929 Symbols 936
References 936
Chapter 21 Econometric Analysis of Energy and Commodity Markets: Multiple Hypothesis Testing Techniques 939
Mark Cummins
21.1 Introduction 939
21.2 Multiple Hypothesis Testing 940
21.2.1 Generalized Familywise Error Rate 941
21.2.2 Per-Familywise Error Rate 942
21.2.3 False Discovery Proportion 942
21.2.4 False Discovery Rate 943
21.2.5 Single-Step and Stepwise Procedures 943
21.3 Energy-Emissions Market Interactions 943
21.3.1 Literature Review 943
21.3.2 Data Description 944
21.3.3 Testing Framework 945
21.3.4 Empirical Results 950
21.4 Emissions Market Interactions 953
21.4.1 Testing Framework and Data 953
21.4.2 Empirical Results 955
21.5 Quantitative Spread Trading in Oil Markets 956
21.5.1 Testing Framework and Data 956
21.5.2 Optimal Statistical Arbitrage Model 957
21.5.3 Resampling-Based MHT Procedures 959
21.5.4 Empirical Results 964
References 964
Appendix A Quick Review of Distributions Relevant in Finance with Matlab (R) Examples 967
Laura Ballotta and Gianluca Fusai
Index 1005
