{"product_id":"handbook-of-multi-commodity-markets-and-products-isbn-9780470745243","title":"Handbook of Multi-Commodity Markets and Products","description":"\u003cb\u003eHandbook of Multi-Commodity Markets and Products\u003c\/b\u003eOver recent decades, the marketplace has seen an increasing integration, not only among different types of commodity markets such as energy, agricultural, and metals, but also with financial markets. This trend raises important questions about how to identify and analyse opportunities in and manage risks of commodity products.  \u003cp\u003eThe \u003ci\u003eHandbook of Multi-Commodity Markets and Products \u003c\/i\u003eoffers traders, commodity brokers, and other professionals a practical and comprehensive manual that covers market structure and functioning, as well as the practice of trading across a wide range of commodity markets and products. Written in non-technical language, this important resource includes the information needed to begin to master the complexities of and to operate successfully in today’s challenging and fluctuating commodity marketplace.  \u003c\/p\u003e\u003cp\u003eDesigned as a practical practitioner-orientated resource, the book includes a detailed overview of key markets – oil, coal, electricity, emissions, weather, industrial metals, freight, agricultural and foreign exchange – and contains a set of tools for analysing, pricing and managing risk for the individual markets. Market features and the main functioning rules of the markets in question are presented, along with the structure of basic financial products and standardised deals. A range of vital topics such as stochastic and econometric modelling, market structure analysis, contract engineering, as well as risk assessment and management are presented and discussed in detail with illustrative examples to commodity markets. \u003c\/p\u003e\u003cp\u003eThe authors showcase how to structure and manage both simple and more complex multi-commodity deals. Addressing the issues of profit-making and risk management, the book reveals how to exploit pay-off profiles and trading strategies on a diversified set of commodity prices. In addition, the book explores how to price energy products and other commodities belonging to markets segmented across specific structural features. \u003c\/p\u003e\u003cp\u003eThe \u003ci\u003eHandbook of Multi-Commodity Markets and Products\u003c\/i\u003e includes a wealth of proven methods and useful models that can be selected and developed in order to make appropriate estimations of the future evolution of prices and appropriate valuations of products. The authors additionally explore market risk issues and what measures of risk should be adopted for the purpose of accurately assessing exposure from multi-commodity portfolios. \u003c\/p\u003e\u003cp\u003eThis vital resource offers the models, tools, strategies and general information commodity brokers and other professionals need to succeed in today’s highly competitive marketplace. \u003c\/p\u003e\u003cp\u003ePreface xix\u003c\/p\u003e \u003cp\u003eAcknowledgements xxiii\u003c\/p\u003e \u003cp\u003eAbout the Editors xxv\u003c\/p\u003e \u003cp\u003eList of Contributors xxvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart One Commodity Markets and Products\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Oil Markets and Products\u003c\/b\u003e \u003cb\u003e3\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eCristiano Campi and Francesco Galdenzi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 3\u003c\/p\u003e \u003cp\u003e1.2 Risk Management for Corporations: Hedging Using Derivative Instruments 4\u003c\/p\u003e \u003cp\u003e1.2.1 Crude Oil and Oil Products Risk Management for Corporations 4\u003c\/p\u003e \u003cp\u003e1.2.2 Aviation: Risk Profile and Hedging Strategies 11\u003c\/p\u003e \u003cp\u003e1.2.3 Shipping: Risk Profile and Hedging Strategies 20\u003c\/p\u003e \u003cp\u003e1.2.4 Land Transportation: Risk Profile and Hedging Strategies 27\u003c\/p\u003e \u003cp\u003e1.2.5 Utilities: Risk Profile and Hedging Strategies 32\u003c\/p\u003e \u003cp\u003e1.2.6 Refineries: Risk Profile and Hedging Strategies 35\u003c\/p\u003e \u003cp\u003e1.2.7 Industrial Consumers: Risk Profile and Hedging Strategies 40\u003c\/p\u003e \u003cp\u003e1.3 Oil Physical Market Hedging and Trading 41\u003c\/p\u003e \u003cp\u003e1.3.1 The Actors, Futures and OTC Prices 41\u003c\/p\u003e \u003cp\u003e1.3.2 The Most Commonly Used Financial Instruments 45\u003c\/p\u003e \u003cp\u003e1.3.3 How to Monitor and Manage Risk 49\u003c\/p\u003e \u003cp\u003e1.3.4 How to Create a Market View 52\u003c\/p\u003e \u003cp\u003e1.3.5 Trading Strategies to Maximize a Market View 54\u003c\/p\u003e \u003cp\u003eFurther Reading 66\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Coal Markets and Products\u003c\/b\u003e \u003cb\u003e67\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eLars Schernikau\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 67\u003c\/p\u003e \u003cp\u003e2.2 Source of Coal – Synopsis of the Resource Coal 72\u003c\/p\u003e \u003cp\u003e2.2.1 The Fundamentals of Energy Sources and Fossil Fuels 72\u003c\/p\u003e \u003cp\u003e2.2.2 Process of Coal Formation 74\u003c\/p\u003e \u003cp\u003e2.2.3 Coal Classification 74\u003c\/p\u003e \u003cp\u003e2.2.4 Reserves and Resources 79\u003c\/p\u003e \u003cp\u003e2.2.5 Coal Mining and Production 83\u003c\/p\u003e \u003cp\u003e2.3 Use of Coal – Power Generation and More 90\u003c\/p\u003e \u003cp\u003e2.3.1 Steam Coal and its Role in Power Generation 91\u003c\/p\u003e \u003cp\u003e2.3.2 Coal-Fired Power Plant Technologies 93\u003c\/p\u003e \u003cp\u003e2.3.3 Cement and Other Industry 95\u003c\/p\u003e \u003cp\u003e2.3.4 Alternatives to Coal: Shale Gas and Other 95\u003c\/p\u003e \u003cp\u003e2.3.5 Future Trend: CtL and Coal Bed Methane 101\u003c\/p\u003e \u003cp\u003e2.4 Overview of Worldwide Steam Coal Supply and Demand 102\u003c\/p\u003e \u003cp\u003e2.4.1 Atlantic Demand Market: Europe at its Core 102\u003c\/p\u003e \u003cp\u003e2.4.2 Pacific Demand Market: China, India, Japan, Taiwan, Korea and SEA 104\u003c\/p\u003e \u003cp\u003e2.4.3 Steam Coal Supply Regions: ID, AU, USA, SA, RU, CO and Others 107\u003c\/p\u003e \u003cp\u003e2.4.4 Seaborne Freight 116\u003c\/p\u003e \u003cp\u003e2.4.5 Geopolitical and Policy Environment 118\u003c\/p\u003e \u003cp\u003e2.5 The Global Steam Coal Trade Market and its Future 121\u003c\/p\u003e \u003cp\u003e2.5.1 Current and Future Market Dynamics of the Coal Trade 121\u003c\/p\u003e \u003cp\u003e2.5.2 Future Steam Coal Price Trends 125\u003c\/p\u003e \u003cp\u003e2.5.3 Future Source of Energy: What Role Will Coal Play? 127\u003c\/p\u003e \u003cp\u003e2.6 Concluding Words 129\u003c\/p\u003e \u003cp\u003eAbbreviations and Definitions 130\u003c\/p\u003e \u003cp\u003eAcknowledgements 132\u003c\/p\u003e \u003cp\u003eReferences 132\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Natural Gas Markets and Products\u003c\/b\u003e \u003cb\u003e135\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eMark Cummins and Bernard Murphy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Physical Natural Gas Markets 135\u003c\/p\u003e \u003cp\u003e3.1.1 Physical Structure 141\u003c\/p\u003e \u003cp\u003e3.1.2 Natural Gas Market Hubs and Main Participants 146\u003c\/p\u003e \u003cp\u003e3.1.3 Liquefied Natural Gas 147\u003c\/p\u003e \u003cp\u003e3.1.4 Shale Gas 149\u003c\/p\u003e \u003cp\u003e3.2 Natural Gas Contracting and Pricing 154\u003c\/p\u003e \u003cp\u003e3.2.1 Natural Gas Price Formation 155\u003c\/p\u003e \u003cp\u003e3.3 Financial Natural Gas Markets 158\u003c\/p\u003e \u003cp\u003e3.3.1 Exchange-Based Markets 158\u003c\/p\u003e \u003cp\u003e3.3.2 Natural Gas Futures 159\u003c\/p\u003e \u003cp\u003e3.3.3 Natural Gas Options 172\u003c\/p\u003e \u003cp\u003e3.3.4 OTC Markets and Products 179\u003c\/p\u003e \u003cp\u003eReferences 180\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Electricity Markets and Products\u003c\/b\u003e \u003cb\u003e181\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eStefano Fiorenzani, Bernard Murphy and Mark Cummins\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Market Structure and Price Components 181\u003c\/p\u003e \u003cp\u003e4.1.1 Spot and Forward Markets 181\u003c\/p\u003e \u003cp\u003e4.1.2 Supply and Demand Interaction 183\u003c\/p\u003e \u003cp\u003e4.1.3 Electricity Derivatives 186\u003c\/p\u003e \u003cp\u003e4.1.4 Power Price Models 189\u003c\/p\u003e \u003cp\u003e4.1.5 Spot Price Analysis (IPEX Case) 196\u003c\/p\u003e \u003cp\u003e4.1.6 Forward Price Analysis (EEX Case) 200\u003c\/p\u003e \u003cp\u003e4.2 Renewables, Intra-Day Trading and Capacity Markets 205\u003c\/p\u003e \u003cp\u003e4.2.1 Renewables Expansion Targets 205\u003c\/p\u003e \u003cp\u003e4.2.2 Growth in Intra-Day Trading 206\u003c\/p\u003e \u003cp\u003e4.2.3 Implications for Future Price Volatility and Price Profiles 207\u003c\/p\u003e \u003cp\u003e4.2.4 Reforms and Innovations in Capacity Markets 209\u003c\/p\u003e \u003cp\u003e4.2.5 Provision and Remuneration of Flexibility – Storage Assets 212\u003c\/p\u003e \u003cp\u003e4.3 Risk Measures for Power Portfolios 216\u003c\/p\u003e \u003cp\u003e4.3.1 Value-Based Risk Measures 216\u003c\/p\u003e \u003cp\u003e4.3.2 Flow-Based Risk Measures 218\u003c\/p\u003e \u003cp\u003e4.3.3 Credit Risk for Power Portfolios 220\u003c\/p\u003e \u003cp\u003eReferences 221\u003c\/p\u003e \u003cp\u003eFurther Reading 221\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Emissions Markets and Products\u003c\/b\u003e \u003cb\u003e223\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eMarc Chesney, Luca Taschini and Jonathan Gheyssens\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 223\u003c\/p\u003e \u003cp\u003e5.2 Climate Change and the Economics of Externalities 224\u003c\/p\u003e \u003cp\u003e5.2.1 The Climate Change Issue 224\u003c\/p\u003e \u003cp\u003e5.2.2 The Economics of Externality and GHG Pollution 226\u003c\/p\u003e \u003cp\u003e5.3 The Kyoto Protocol 227\u003c\/p\u003e \u003cp\u003e5.3.1 The United Nations Framework Convention on Climate Change 227\u003c\/p\u003e \u003cp\u003e5.3.2 The Conference of Parties and the Subsidiary Bodies 229\u003c\/p\u003e \u003cp\u003e5.3.3 The Kyoto Protocol 229\u003c\/p\u003e \u003cp\u003e5.3.4 The Road to Paris 231\u003c\/p\u003e \u003cp\u003e5.4 The EU ETS 232\u003c\/p\u003e \u003cp\u003e5.4.1 Institutional Features 232\u003c\/p\u003e \u003cp\u003e5.4.2 Allocation Criteria 234\u003c\/p\u003e \u003cp\u003e5.4.3 Market Players and the Permit Markets 236\u003c\/p\u003e \u003cp\u003e5.4.4 The Future of the EU ETS 238\u003c\/p\u003e \u003cp\u003e5.5 Regional Markets: A Fragmented Landscape 239\u003c\/p\u003e \u003cp\u003e5.5.1 Regional Markets 239\u003c\/p\u003e \u003cp\u003e5.5.2 Voluntary Markets 240\u003c\/p\u003e \u003cp\u003e5.6 A New Asset Class: CO\u003csub\u003e2\u003c\/sub\u003e Emission Permits 241\u003c\/p\u003e \u003cp\u003e5.6.1 Macroeconomic Models 242\u003c\/p\u003e \u003cp\u003e5.6.2 Econometric Investigation of CO\u003csub\u003e2\u003c\/sub\u003e Permit Price Time-Series 243\u003c\/p\u003e \u003cp\u003e5.6.3 Stochastic Equilibrium Models 251\u003c\/p\u003e \u003cp\u003eAbbreviations 252\u003c\/p\u003e \u003cp\u003eReferences 252\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Weather Risk and Weather Derivatives 255\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eAlessandro Mauro\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 255\u003c\/p\u003e \u003cp\u003e6.2 Identification of Volumetric Risk 257\u003c\/p\u003e \u003cp\u003e6.2.1 Weather Events on the Demand Curve 258\u003c\/p\u003e \u003cp\u003e6.2.2 Weather Events on the Supply Curve 260\u003c\/p\u003e \u003cp\u003e6.2.3 Risk Measurement and Weather-at-Risk 262\u003c\/p\u003e \u003cp\u003e6.3 Atmospheric Temperature and Natural Gas Market 264\u003c\/p\u003e \u003cp\u003e6.3.1 Characterization of the Air Temperature Meteorological Variable 264\u003c\/p\u003e \u003cp\u003e6.3.2 Degree Days 267\u003c\/p\u003e \u003cp\u003e6.3.3 Volumetric Risk in the Natural Gas Market 270\u003c\/p\u003e \u003cp\u003e6.4 Modification of Weather Risk Exposure with Weather Derivatives 272\u003c\/p\u003e \u003cp\u003e6.4.1 Weather Derivatives for Temperature-Related Risk 273\u003c\/p\u003e \u003cp\u003e6.5 Conclusions 276\u003c\/p\u003e \u003cp\u003eNomenclature 277\u003c\/p\u003e \u003cp\u003eReferences 277\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Industrial Metals Markets and Products\u003c\/b\u003e \u003cb\u003e279\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eAlessandro Porru\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 General Overview 279\u003c\/p\u003e \u003cp\u003e7.1.1 Brief History of the LME 280\u003c\/p\u003e \u003cp\u003e7.1.2 Non-ferrous Metals 282\u003c\/p\u003e \u003cp\u003e7.1.3 Other Metals 291\u003c\/p\u003e \u003cp\u003e7.1.4 LME Instruments 292\u003c\/p\u003e \u003cp\u003e7.1.5 OTC Instruments 298\u003c\/p\u003e \u003cp\u003e7.1.6 A New Player: The Investor 301\u003c\/p\u003e \u003cp\u003e7.2 Forward Curves 305\u003c\/p\u003e \u003cp\u003e7.2.1 Building LME’s Curves in Practice 308\u003c\/p\u003e \u003cp\u003e7.2.2 Interpolation 313\u003c\/p\u003e \u003cp\u003e7.2.3 LME, COMEX and SHFE Copper Curve and Arbitrage 314\u003c\/p\u003e \u003cp\u003e7.2.4 Contango Limit… 318\u003c\/p\u003e \u003cp\u003e7.2.5 …and No-Limit Backwardation 324\u003c\/p\u003e \u003cp\u003e7.2.6 Hedging the Curve in Practice 328\u003c\/p\u003e \u003cp\u003e7.3 Volatility 337\u003c\/p\u003e \u003cp\u003e7.3.1 A European Disguised as an American 338\u003c\/p\u003e \u003cp\u003e7.3.2 LME’s Closing Volatilities 339\u003c\/p\u003e \u003cp\u003e7.3.3 Sticky Strike, Sticky Delta and Skew 342\u003c\/p\u003e \u003cp\u003e7.3.4 Building the Surface in Practice 345\u003c\/p\u003e \u003cp\u003e7.3.5 Considerations on Vega Hedging 348\u003c\/p\u003e \u003cp\u003eAcknowledgements 352\u003c\/p\u003e \u003cp\u003eReferences 353\u003c\/p\u003e \u003cp\u003eFurther Reading 353\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Freight Markets and Products\u003c\/b\u003e \u003cb\u003e355\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eManolis G. Kavussanos, Ilias D. Visvikis and Dimitris N. Dimitrakopoulos\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 355\u003c\/p\u003e \u003cp\u003e8.2 Business Risks in Shipping 356\u003c\/p\u003e \u003cp\u003e8.2.1 The Sources of Risk in the Shipping Industry 356\u003c\/p\u003e \u003cp\u003e8.2.2 Market Segmentation in the Shipping Industry 358\u003c\/p\u003e \u003cp\u003e8.2.3 Empirical Regularities in Freight Rate Markets 359\u003c\/p\u003e \u003cp\u003e8.2.4 Traditional Risk Management Strategies 365\u003c\/p\u003e \u003cp\u003e8.3 Freight Rate Derivatives 366\u003c\/p\u003e \u003cp\u003e8.3.1 Risk Management in Shipping 366\u003c\/p\u003e \u003cp\u003e8.3.2 The Underlying Indices of Freight Rate Derivatives 366\u003c\/p\u003e \u003cp\u003e8.3.3 The Freight Derivatives Market 372\u003c\/p\u003e \u003cp\u003e8.3.4 Examples of Freight Derivatives Trading 380\u003c\/p\u003e \u003cp\u003e8.4 Pricing, Hedging and Freight Rate Risk Measurement 382\u003c\/p\u003e \u003cp\u003e8.4.1 Pricing and Hedging Effectiveness of Freight Derivatives 382\u003c\/p\u003e \u003cp\u003e8.4.2 Value-at-Risk (VaR) in Freight Markets 384\u003c\/p\u003e \u003cp\u003e8.4.3 Expected Shortfall (ES) in Freight Markets 389\u003c\/p\u003e \u003cp\u003e8.4.4 Empirical Evidence on Freight Derivatives 390\u003c\/p\u003e \u003cp\u003e8.5 Other Derivatives for the Shipping Industry 393\u003c\/p\u003e \u003cp\u003e8.5.1 Bunker Fuel Derivatives 393\u003c\/p\u003e \u003cp\u003e8.5.2 Vessel Value Derivatives 395\u003c\/p\u003e \u003cp\u003e8.5.3 Foreign Exchange Rate Derivatives Contracts 395\u003c\/p\u003e \u003cp\u003e8.5.4 Interest Rate Derivatives Contracts 396\u003c\/p\u003e \u003cp\u003e8.6 Conclusion 396\u003c\/p\u003e \u003cp\u003eAcknowledgements 396\u003c\/p\u003e \u003cp\u003eReferences 397\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Agricultural and Soft Markets\u003c\/b\u003e \u003cb\u003e399\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eFrancis Declerk\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction: Stakes and Objectives 399\u003c\/p\u003e \u003cp\u003e9.1.1 Stakes 399\u003c\/p\u003e \u003cp\u003e9.1.2 Objectives 399\u003c\/p\u003e \u003cp\u003e9.2 Agricultural Commodity Specificity and Futures Markets 400\u003c\/p\u003e \u003cp\u003e9.2.1 Agricultural Commodity Specificity 400\u003c\/p\u003e \u003cp\u003e9.2.2 Volatility of Agricultural Markets 402\u003c\/p\u003e \u003cp\u003e9.2.3 Forward Contract and Futures Contract 402\u003c\/p\u003e \u003cp\u003e9.2.4 Major Agricultural Futures Markets and Contracts 404\u003c\/p\u003e \u003cp\u003e9.2.5 Roles of Futures Markets 405\u003c\/p\u003e \u003cp\u003e9.2.6 Institutions Related to Futures Markets 406\u003c\/p\u003e \u003cp\u003e9.2.7 Commodity Futures Contracts 406\u003c\/p\u003e \u003cp\u003e9.2.8 The Operators 408\u003c\/p\u003e \u003cp\u003e9.2.9 Monitoring Hedging: Settlement 409\u003c\/p\u003e \u003cp\u003e9.2.10 Accounting and Tax Rules 409\u003c\/p\u003e \u003cp\u003e9.3 Demand and Supply, Price Determinants and Dynamics 409\u003c\/p\u003e \u003cp\u003e9.3.1 Supply and Demand for Agricultural Commodities: The Determinants 409\u003c\/p\u003e \u003cp\u003e9.3.2 Agricultural Market Prices, Failures and Policies 413\u003c\/p\u003e \u003cp\u003e9.3.3 The Price Dynamics of Seasonal and Storable Agricultural Commodities 416\u003c\/p\u003e \u003cp\u003e9.3.4 The Features of Major Agricultural and Soft Markets 417\u003c\/p\u003e \u003cp\u003e9.4 Hedging and Basis Management 466\u003c\/p\u003e \u003cp\u003e9.4.1 Short Hedging for Producers 466\u003c\/p\u003e \u003cp\u003e9.4.2 Long Hedging for Processors 469\u003c\/p\u003e \u003cp\u003e9.4.3 Management of Basis Risk 471\u003c\/p\u003e \u003cp\u003e9.5 The Financialization of Agricultural Markets and Hunger: Speculation and Regulation 480\u003c\/p\u003e \u003cp\u003e9.5.1 Factors Affecting the Volatility of Agricultural Commodity Prices 480\u003c\/p\u003e \u003cp\u003e9.5.2 Financialization: Impact of Non-commercial Traders on Market Price 483\u003c\/p\u003e \u003cp\u003e9.5.3 The Financialization of Grain Markets and Speculation 484\u003c\/p\u003e \u003cp\u003e9.5.4 Bubble or Not, Agricultural Commodities have Become an Asset Class 489\u003c\/p\u003e \u003cp\u003e9.5.5 Price Volatility and Regulation 490\u003c\/p\u003e \u003cp\u003e9.5.6 Ongoing Research about Speculation and Regulation 493\u003c\/p\u003e \u003cp\u003e9.6 Conclusion about Hedging and Futures Contracts 493\u003c\/p\u003e \u003cp\u003e9.6.1 Hedging Process 493\u003c\/p\u003e \u003cp\u003e9.6.2 Key Success Factors for Agricultural Commodity Futures Contracts 494\u003c\/p\u003e \u003cp\u003e9.6.3 Conclusion and Prospects 495\u003c\/p\u003e \u003cp\u003eReferences 495\u003c\/p\u003e \u003cp\u003eFurther Reading 496\u003c\/p\u003e \u003cp\u003eGlossary, Quotations and Policy on Websites 497\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Foreign Exchange Markets and Products\u003c\/b\u003e \u003cb\u003e499\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eAntonio Castagna\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 The FX Market 499\u003c\/p\u003e \u003cp\u003e10.1.1 FX Rates and Spot Contracts 499\u003c\/p\u003e \u003cp\u003e10.1.2 Outright and FX Swap Contracts 500\u003c\/p\u003e \u003cp\u003e10.1.3 FX Option Contracts 504\u003c\/p\u003e \u003cp\u003e10.1.4 Main Traded FX Options Structures 507\u003c\/p\u003e \u003cp\u003e10.2 Pricing Models for FX Options 509\u003c\/p\u003e \u003cp\u003e10.2.1 The Black–Scholes Model 510\u003c\/p\u003e \u003cp\u003e10.3 The Volatility Surface 511\u003c\/p\u003e \u003cp\u003e10.4 Barrier Options 512\u003c\/p\u003e \u003cp\u003e10.4.1 A Taxonomy of Barrier Options 512\u003c\/p\u003e \u003cp\u003e10.5 Sources of FX Risk Exposure 513\u003c\/p\u003e \u003cp\u003e10.6 Hedging FX Exposures Embedded in Energy and Commodity Contracts 517\u003c\/p\u003e \u003cp\u003e10.6.1 FX Forward Exposures and Conversions 518\u003c\/p\u003e \u003cp\u003e10.6.2 FX-Linked Energy Contracts 522\u003c\/p\u003e \u003cp\u003e10.7 Typical Hedging Structures for FX Risk Exposure 533\u003c\/p\u003e \u003cp\u003e10.7.1 Collar Plain Vanilla 533\u003c\/p\u003e \u003cp\u003e10.7.2 Leveraged Forward 536\u003c\/p\u003e \u003cp\u003e10.7.3 Participating Forward 538\u003c\/p\u003e \u003cp\u003e10.7.4 Knock-Out Forward 540\u003c\/p\u003e \u003cp\u003e10.7.5 Knock-In Forward 543\u003c\/p\u003e \u003cp\u003e10.7.6 Knock-In Knock-out Forward 545\u003c\/p\u003e \u003cp\u003e10.7.7 Resettable Forward 548\u003c\/p\u003e \u003cp\u003e10.7.8 Range Resettable Forward 550\u003c\/p\u003e \u003cp\u003eReferences 553\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart Two Quantitative Topics\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 An Introduction to Stochastic Calculus with Matlab\u003csup\u003e®\u003c\/sup\u003e Examples 557\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eLaura Ballotta and Gianluca Fusai\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Brownian Motion 558\u003c\/p\u003e \u003cp\u003e11.1.1 Defining Brownian Motion 558\u003c\/p\u003e \u003cp\u003e11.2 The Stochastic Integral and Stochastic Differential Equations 566\u003c\/p\u003e \u003cp\u003e11.2.1 Introduction 566\u003c\/p\u003e \u003cp\u003e11.2.2 Defining the Stochastic Integral 567\u003c\/p\u003e \u003cp\u003e11.2.3 The It Stochastic Integral as a Mean Square Limit of Suitable Riemann–Stieltjes Sums 567\u003c\/p\u003e \u003cp\u003e11.2.4 A Motivating Example: Computing ∫\u003csub\u003e0\u003c\/sub\u003e\u003csup\u003et\u003c\/sup\u003e\u003ci\u003eW\u003c\/i\u003e(\u003ci\u003es\u003c\/i\u003e)\u003ci\u003edW\u003c\/i\u003e(\u003ci\u003es\u003c\/i\u003e) 568\u003c\/p\u003e \u003cp\u003e11.2.5 Properties of the Stochastic Integral 569\u003c\/p\u003e \u003cp\u003e11.2.6 Itˆo Process and Stochastic Differential Equations 571\u003c\/p\u003e \u003cp\u003e11.2.7 Solving Stochastic Integrals and\/or Stochastic Differential Equations 573\u003c\/p\u003e \u003cp\u003e11.3 Introducing Itȏ’s Formula 575\u003c\/p\u003e \u003cp\u003e11.3.1 A Fact from Ordinary Calculus 576\u003c\/p\u003e \u003cp\u003e11.3.2 Itˆo’s Formula when \u003ci\u003eY \u003c\/i\u003e= \u003ci\u003eg\u003c\/i\u003e(\u003ci\u003ex\u003c\/i\u003e), \u003ci\u003eg\u003c\/i\u003e(\u003ci\u003ex\u003c\/i\u003e) ∈ \u003ci\u003eC\u003c\/i\u003e\u003csup\u003e2\u003c\/sup\u003e 576\u003c\/p\u003e \u003cp\u003e11.3.3 Guiding Principle 577\u003c\/p\u003e \u003cp\u003e11.3.4 Itˆo’s Formula when \u003ci\u003eY\u003c\/i\u003e(\u003ci\u003et\u003c\/i\u003e) = \u003ci\u003eg\u003c\/i\u003e(\u003ci\u003et\u003c\/i\u003e, \u003ci\u003eX\u003c\/i\u003e), \u003ci\u003eg\u003c\/i\u003e(\u003ci\u003et\u003c\/i\u003e, \u003ci\u003eX\u003c\/i\u003e) ∈ \u003ci\u003eC\u003c\/i\u003e\u003csup\u003e1,2 \u003c\/sup\u003e577\u003c\/p\u003e \u003cp\u003e11.3.5 The Multivariate Itˆo’s Lemma when \u003ci\u003eZ \u003c\/i\u003e= \u003ci\u003eg\u003c\/i\u003e(\u003ci\u003et\u003c\/i\u003e, \u003ci\u003eX\u003c\/i\u003e, \u003ci\u003eY\u003c\/i\u003e) 578\u003c\/p\u003e \u003cp\u003e11.4 Important SDEs 581\u003c\/p\u003e \u003cp\u003e11.4.1 The Geometric Brownian Motion \u003ci\u003eGBM\u003c\/i\u003e(\u003ci\u003e𝜇\u003c\/i\u003e, \u003ci\u003e𝜎\u003c\/i\u003e) 581\u003c\/p\u003e \u003cp\u003e11.4.2 The Vasicek Mean-Reverting Process 588\u003c\/p\u003e \u003cp\u003e11.4.3 The Cox–Ingersoll–Ross (CIR) Model 595\u003c\/p\u003e \u003cp\u003e11.4.4 The Constant Elasticity of Variance (CEV) Model 604\u003c\/p\u003e \u003cp\u003e11.4.5 The Brownian Bridge 607\u003c\/p\u003e \u003cp\u003e11.4.6 The Stochastic Volatility Heston Model (1987) 611\u003c\/p\u003e \u003cp\u003e11.5 Stochastic Processes with Jumps 618\u003c\/p\u003e \u003cp\u003e11.5.1 Preliminaries 618\u003c\/p\u003e \u003cp\u003e11.5.2 Jump Diffusion Processes 623\u003c\/p\u003e \u003cp\u003e11.5.3 Time-Changed Brownian Motion 628\u003c\/p\u003e \u003cp\u003e11.5.4 Final Remark: Lévy Processes 632\u003c\/p\u003e \u003cp\u003eReferences 633\u003c\/p\u003e \u003cp\u003eFurther Reading 633\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 Estimating Commodity Term Structure Volatilities 635\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAndrea Roncoroni, Rachid Id Brik and Mark Cummins\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 635\u003c\/p\u003e \u003cp\u003e12.2 Model Estimation Using the Kalman Filter 635\u003c\/p\u003e \u003cp\u003e12.2.1 Description of the Methodology 636\u003c\/p\u003e \u003cp\u003e12.2.2 Case Study: Estimating Parameters on Crude Oil 642\u003c\/p\u003e \u003cp\u003e12.3 Principal Components Analysis 646\u003c\/p\u003e \u003cp\u003e12.3.1 PCA: Technical Presentation 647\u003c\/p\u003e \u003cp\u003e12.3.2 Case Study: Risk Analysis on Energy Markets 651\u003c\/p\u003e \u003cp\u003e12.4 Conclusion 655\u003c\/p\u003e \u003cp\u003eAppendix 655\u003c\/p\u003e \u003cp\u003eReferences 657\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 Nonparametric Estimation of Energy and Commodity Price Processes 659\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGianna Fig`a-Talamanca and Andrea Roncoroni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 659\u003c\/p\u003e \u003cp\u003e13.2 Estimation Method 660\u003c\/p\u003e \u003cp\u003e13.3 Empirical Results 663\u003c\/p\u003e \u003cp\u003eReferences 672\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 How to Build Electricity Forward Curves 673\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRuggero Caldana, Gianluca Fusai and Andrea Roncoroni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 673\u003c\/p\u003e \u003cp\u003e14.2 Review of the Literature 674\u003c\/p\u003e \u003cp\u003e14.3 Electricity Forward Contracts 675\u003c\/p\u003e \u003cp\u003e14.4 Smoothing Forward Price Curves 677\u003c\/p\u003e \u003cp\u003e14.5 An Illustrative Example: Daily Forward Curve 679\u003c\/p\u003e \u003cp\u003e14.6 Conclusion 684\u003c\/p\u003e \u003cp\u003eReferences 684\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15 GARCH Models for Commodity Markets 687\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eEduardo Rossi and Filippo Spazzini\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 687\u003c\/p\u003e \u003cp\u003e15.2 The GARCH Model: General Definition 690\u003c\/p\u003e \u003cp\u003e15.2.1 The ARCH(\u003ci\u003eq\u003c\/i\u003e) Model 692\u003c\/p\u003e \u003cp\u003e15.2.2 The GARCH(\u003ci\u003ep\u003c\/i\u003e,\u003ci\u003eq\u003c\/i\u003e) Model 693\u003c\/p\u003e \u003cp\u003e15.2.3 The Yule–Walker Equations for the Squared Process 695\u003c\/p\u003e \u003cp\u003e15.2.4 Stationarity of the GARCH(\u003ci\u003ep\u003c\/i\u003e,\u003ci\u003eq\u003c\/i\u003e) 696\u003c\/p\u003e \u003cp\u003e15.2.5 Forecasting Volatility with GARCH 698\u003c\/p\u003e \u003cp\u003e15.3 The IGARCH(\u003ci\u003ep\u003c\/i\u003e,\u003ci\u003eq\u003c\/i\u003e) Model 699\u003c\/p\u003e \u003cp\u003e15.4 A Permanent and Transitory Component Model of Volatility 700\u003c\/p\u003e \u003cp\u003e15.5 Asymmetric Models 702\u003c\/p\u003e \u003cp\u003e15.5.1 The EGARCH(\u003ci\u003ep\u003c\/i\u003e,\u003ci\u003eq\u003c\/i\u003e) Model 702\u003c\/p\u003e \u003cp\u003e15.5.2 Other Asymmetric Models 704\u003c\/p\u003e \u003cp\u003e15.5.3 The News Impact Curve 706\u003c\/p\u003e \u003cp\u003e15.6 Periodic GARCH 707\u003c\/p\u003e \u003cp\u003e15.6.1 Periodic EGARCH 708\u003c\/p\u003e \u003cp\u003e15.7 Nesting Models 708\u003c\/p\u003e \u003cp\u003e15.8 Long-Memory GARCH Models 713\u003c\/p\u003e \u003cp\u003e15.8.1 The FIGARCH Model 716\u003c\/p\u003e \u003cp\u003e15.8.2 The FIEGARCH Model 719\u003c\/p\u003e \u003cp\u003e15.9 Estimation 720\u003c\/p\u003e \u003cp\u003e15.9.1 Likelihood Computation 720\u003c\/p\u003e \u003cp\u003e15.10 Inference 722\u003c\/p\u003e \u003cp\u003e15.10.1 Testing for ARCH Effects 722\u003c\/p\u003e \u003cp\u003e15.10.2 Test for Asymmetric Effects 723\u003c\/p\u003e \u003cp\u003e15.11 Multivariate GARCH 725\u003c\/p\u003e \u003cp\u003e15.11.1 BEKK Parameterization of MGARCH 726\u003c\/p\u003e \u003cp\u003e15.11.2 The Dynamic Conditional Correlation Model 726\u003c\/p\u003e \u003cp\u003e15.12 Empirical Applications 727\u003c\/p\u003e \u003cp\u003e15.12.1 Univariate Volatility Modelling 727\u003c\/p\u003e \u003cp\u003e15.12.2 A Simple Risk Measurement Application: A Bivariate Example with Copulas 733\u003c\/p\u003e \u003cp\u003e15.13 Software 740\u003c\/p\u003e \u003cp\u003eReferences 748\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 16 Pricing Commodity Swaps with Counterparty Credit Risk: The Case of Credit Value Adjustment 755\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMarina Marena, Gianluca Fusai and Chiara Quaglini\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 755\u003c\/p\u003e \u003cp\u003e16.1.1 Energy Company Strategies in Derivative Instruments 755\u003c\/p\u003e \u003cp\u003e16.2 Company Energy Policy 756\u003c\/p\u003e \u003cp\u003e16.2.1 Commodity Risk 756\u003c\/p\u003e \u003cp\u003e16.2.2 Credit Risk 757\u003c\/p\u003e \u003cp\u003e16.3 A Focus on Commodity Swap Contracts 758\u003c\/p\u003e \u003cp\u003e16.3.1 Definition and Main Features of a Commodity Swap 758\u003c\/p\u003e \u003cp\u003e16.4 Modelling the Dynamics of Oil Spot Prices and the Forward Curve 760\u003c\/p\u003e \u003cp\u003e16.4.1 The Schwartz and Smith Pricing Model 760\u003c\/p\u003e \u003cp\u003e16.5 An Empirical Application 764\u003c\/p\u003e \u003cp\u003e16.5.1 The Commodity Swap Features 764\u003c\/p\u003e \u003cp\u003e16.5.2 Calibration of the Theoretical Schwartz and Smith Forward Curve 765\u003c\/p\u003e \u003cp\u003e16.5.3 The Monte Carlo Simulation of Oil Spot Prices 772\u003c\/p\u003e \u003cp\u003e16.5.4 The Computation of Brent Forward Curves at Any Given Valuation Date 773\u003c\/p\u003e \u003cp\u003e16.6 Measuring Counterparty Risk 777\u003c\/p\u003e \u003cp\u003e16.6.1 CVA Calculation 779\u003c\/p\u003e \u003cp\u003e16.6.2 Swap Fixed Price Adjustment for Counterparty Risk 782\u003c\/p\u003e \u003cp\u003e16.6.3 Right- and Wrong-Way Risk 784\u003c\/p\u003e \u003cp\u003e16.7 Sensitivity Analysis 788\u003c\/p\u003e \u003cp\u003e16.8 Accounting for Derivatives and Credit Value Adjustments 788\u003c\/p\u003e \u003cp\u003e16.8.1 Example of Hedge Effectiveness 791\u003c\/p\u003e \u003cp\u003e16.8.2 Accounting for CVA 796\u003c\/p\u003e \u003cp\u003e16.9 Conclusions 797\u003c\/p\u003e \u003cp\u003eReferences 798\u003c\/p\u003e \u003cp\u003eFurther Reading 798\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 17 Pricing Energy Spread Options 801\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eFred Espen Benth and Hanna Zdanowicz\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Spread Options in Energy Markets 801\u003c\/p\u003e \u003cp\u003e17.2 Pricing of Spread Options with Zero Strike 805\u003c\/p\u003e \u003cp\u003e17.3 Issues of hedging 813\u003c\/p\u003e \u003cp\u003e17.4 Pricing of Spread Options with Nonzero Strike 815\u003c\/p\u003e \u003cp\u003e17.4.1 Kirk’s Approximation Formula 817\u003c\/p\u003e \u003cp\u003e17.4.2 Approximation by Margrabe Based on Taylor Expansion 820\u003c\/p\u003e \u003cp\u003e17.4.3 Other Pricing Methods 823\u003c\/p\u003e \u003cp\u003eAcknowledgement 824\u003c\/p\u003e \u003cp\u003eReferences 825\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 18 Asian Options: Payoffs and Pricing Models 827\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGianluca Fusai, Marina Marena and Giovanni Longo\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Payoff Structures 832\u003c\/p\u003e \u003cp\u003e18.2 Pricing Asian Options in the Lognormal Setting 833\u003c\/p\u003e \u003cp\u003e18.2.1 Moment Matching 835\u003c\/p\u003e \u003cp\u003e18.2.2 Lower Price Bound 844\u003c\/p\u003e \u003cp\u003e18.2.3 Monte carlo simulation 845\u003c\/p\u003e \u003cp\u003e18.3 A Comparison 856\u003c\/p\u003e \u003cp\u003e18.4 The Flexible Square-Root Model 858\u003c\/p\u003e \u003cp\u003e18.4.1 General Setup 861\u003c\/p\u003e \u003cp\u003e18.4.2 Numerical Results 870\u003c\/p\u003e \u003cp\u003e18.4.3 A Case Study 871\u003c\/p\u003e \u003cp\u003e18.5 Conclusions 874\u003c\/p\u003e \u003cp\u003eReferences 874\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 19 Natural Gas Storage Modelling 877\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eA´lvaro Cartea, James Cheeseman and Sebastian Jaimungal\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 877\u003c\/p\u003e \u003cp\u003e19.2 A Simple Model of Storage, Futures Prices, Spot Prices And Convenience Yield 878\u003c\/p\u003e \u003cp\u003e19.3 Valuation of Gas Storage 880\u003c\/p\u003e \u003cp\u003e19.3.1 Least-Squares Monte Carlo 881\u003c\/p\u003e \u003cp\u003e19.3.2 LSMC Greeks 883\u003c\/p\u003e \u003cp\u003e19.3.3 Extending the LSMC to Price Gas Storage 883\u003c\/p\u003e \u003cp\u003e19.3.4 Toy Storage Model 884\u003c\/p\u003e \u003cp\u003e19.3.5 Storage LSMC 888\u003c\/p\u003e \u003cp\u003e19.3.6 Swing Options 890\u003c\/p\u003e \u003cp\u003e19.3.7 Closed-Form Storage Solution 891\u003c\/p\u003e \u003cp\u003e19.3.8 Monte Carlo Convergence 892\u003c\/p\u003e \u003cp\u003e19.3.9 Simulated Storage Operations 894\u003c\/p\u003e \u003cp\u003e19.3.10 Storage Value 897\u003c\/p\u003e \u003cp\u003eReferences 899\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 20 Commodity-Linked Arbitrage Strategies and Portfolio Management 901\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eViviana Fanelli\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Commodity-Linked Arbitrage Strategies 902\u003c\/p\u003e \u003cp\u003e20.1.1 The Efficient Market Hypothesis 902\u003c\/p\u003e \u003cp\u003e20.1.2 Risk Arbitrage Opportunities in Commodity Markets 903\u003c\/p\u003e \u003cp\u003e20.1.3 Basic Quantitative Trading Strategies 906\u003c\/p\u003e \u003cp\u003e20.1.4 A General Statistical Arbitrage Trading Methodology 914\u003c\/p\u003e \u003cp\u003e20.2 Portfolio Optimization with Commodities 921\u003c\/p\u003e \u003cp\u003e20.2.1 Commodities as an Asset Class 921\u003c\/p\u003e \u003cp\u003e20.2.2 Commodity Futures Return Characteristics 923\u003c\/p\u003e \u003cp\u003e20.2.3 Risk Premiums in Commodity Markets 925\u003c\/p\u003e \u003cp\u003e20.2.4 Commodities as a Portfolio Diversifier 928\u003c\/p\u003e \u003cp\u003e20.2.5 Risk–Return Optimization in Commodity Portfolios 929 Symbols 936\u003c\/p\u003e \u003cp\u003eReferences 936\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 21 Econometric Analysis of Energy and Commodity Markets: Multiple Hypothesis Testing Techniques 939\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMark Cummins\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21.1 Introduction 939\u003c\/p\u003e \u003cp\u003e21.2 Multiple Hypothesis Testing 940\u003c\/p\u003e \u003cp\u003e21.2.1 Generalized Familywise Error Rate 941\u003c\/p\u003e \u003cp\u003e21.2.2 Per-Familywise Error Rate 942\u003c\/p\u003e \u003cp\u003e21.2.3 False Discovery Proportion 942\u003c\/p\u003e \u003cp\u003e21.2.4 False Discovery Rate 943\u003c\/p\u003e \u003cp\u003e21.2.5 Single-Step and Stepwise Procedures 943\u003c\/p\u003e \u003cp\u003e21.3 Energy–Emissions Market Interactions 943\u003c\/p\u003e \u003cp\u003e21.3.1 Literature Review 943\u003c\/p\u003e \u003cp\u003e21.3.2 Data Description 944\u003c\/p\u003e \u003cp\u003e21.3.3 Testing Framework 945\u003c\/p\u003e \u003cp\u003e21.3.4 Empirical Results 950\u003c\/p\u003e \u003cp\u003e21.4 Emissions Market Interactions 953\u003c\/p\u003e \u003cp\u003e21.4.1 Testing Framework and Data 953\u003c\/p\u003e \u003cp\u003e21.4.2 Empirical Results 955\u003c\/p\u003e \u003cp\u003e21.5 Quantitative Spread Trading in Oil Markets 956\u003c\/p\u003e \u003cp\u003e21.5.1 Testing Framework and Data 956\u003c\/p\u003e \u003cp\u003e21.5.2 Optimal Statistical Arbitrage Model 957\u003c\/p\u003e \u003cp\u003e21.5.3 Resampling-Based MHT Procedures 959\u003c\/p\u003e \u003cp\u003e21.5.4 Empirical Results 964\u003c\/p\u003e \u003cp\u003eReferences 964\u003c\/p\u003e \u003cp\u003eAppendix A Quick Review of Distributions Relevant in Finance with Matlab\u003csup\u003e®\u003c\/sup\u003e Examples 967\u003cb\u003e\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eLaura Ballotta and Gianluca Fusai\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIndex 1005\u003c\/p\u003e \u003cp\u003e\u003cb\u003eANDREA RONCORONI\u003c\/b\u003e is Professor of Finance at ESSEC Business School (Paris-Singapore), regular Visiting Professor at Bocconi University (Milan), and Director of the ESSEC Energy and Commodity Finance research center. He holds PhD’s in Applied Mathematics and in Finance. His research interests primarily cover energy and commodity markets, corporate financial risk analysis and management, quantitative modelling, derivative design and valuation. Andrea put forward the Threshold Model for price simulation in spiky electricity markets, and devised FloRisk Metrics, an effective analytics to monitor and manage corporate financial exposure. He publishes in academic journals, professional reviews, financial book series, and acts as Associate Editor for the \u003ci\u003eJournal of Energy Markets\u003c\/i\u003e and Co-Editor for \u003ci\u003eArgo Review\u003c\/i\u003e. Andrea has co-authored the reference volume \u003ci\u003eImplementing Models in Quantitative Finance\u003c\/i\u003e. As a professional advisor, he consulted for private companies and public institutions, including Dong Energy, Edison, Enel, GDF, Natixis, and Trafigura Electricity Italia (TEI Energy). He is founder and CEO of Energisk, a start-up company developing cutting-edge risk analytics for corporate clients.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eGIANLUCA FUSAI\u003c\/b\u003e is Full Professor in Financial Mathematics at the University of Eastern Piedmont, Italy, and a PT Reader in Mathematical Finance at Cass Business School, City University of London, UK. He holds a PhD in Finance from Warwick Business School, an MSc in Statistics and Operational Research from the University of Essex and a BSc in Economics from Bocconi University. His research interests focus on Energy Markets, Financial Engineering, Numerical Methods for Finance, Quantitative Risk Management. He has published extensively on these topics in top-tier international reviews. Gianluca has also co-authored the best-selling textbook \u003ci\u003eImplementing Models in Quantitative Finance\u003c\/i\u003e. Gianluca has cooperated to several projects in energy markets including a multi-energy risk assessment tool developed in conjunction with a pool of energy and industrial companies and a forward curve builder for the power and gas markets nowadays used for trading and marking to market. He has also been a consultant for private and public sector on building pricing tools of derivative products. Gianluca has been an expert witness in several derivative disputes. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eMARK CUMMINS \u003c\/b\u003eis Senior Lecturer in Finance at the Dublin City University Business School and holds a PhD in Quantitative Finance. Mark’s research interests include a broad range of energy and commodity modelling, derivatives, risk management and trading topics. Mark has published in international journals such as \u003ci\u003eEnergy Economics, Applied Energy\u003c\/i\u003e and the \u003ci\u003eJournal of Energy Markets,\u003c\/i\u003e as well as mainstream finance journals such as the \u003ci\u003eJournal of Financial Markets, International Review of Financial Analysis and Quantitative Finance.\u003c\/i\u003e Mark has previous industry experience working as a Quantitative Analyst within the Global Risk function for BP Oil International Ltd. As part of the Risk Quantitative Analysis team, primary responsibilities included derivatives and price curve model validation and development, with a global remit across BP’s energy and commodity activities. Mark is engaged in ongoing industry training and consultancy activities, focused on the energy sector primarily.  \u003c\/p\u003e\u003cp\u003eOver recent decades, the marketplace has seen an increasing integration, not only among different types of commodity markets such as energy, agricultural, and metals, but also with financial markets. This trend raises important questions about how to identify and analyse opportunities in and manage risks of commodity products.\u003c\/p\u003e  \u003cp\u003eThe \u003ci\u003eHandbook of Multi-Commodity Markets and Products \u003c\/i\u003eoffers traders, commodity brokers, and other professionals a practical and comprehensive manual that covers market structure and functioning, as well as the practice of trading across a wide range of commodity markets and products. Written in non-technical language, this important resource includes the information needed to begin to master the complexities of and to operate successfully in today’s challenging and fluctuating commodity marketplace.  \u003c\/p\u003e\u003cp\u003eDesigned as a practical practitioner-orientated resource, the book includes a detailed overview of key markets – oil, coal, electricity, emissions, weather, industrial metals, freight, agricultural and foreign exchange – and contains a set of tools for analysing, pricing and managing risk for the individual markets. Market features and the main functioning rules of the markets in question are presented, along with the structure of basic financial products and standardised deals. A range of vital topics such as stochastic and econometric modelling, market structure analysis, contract engineering, as well as risk assessment and management are presented and discussed in detail with illustrative examples to commodity markets. \u003c\/p\u003e\u003cp\u003eThe authors showcase how to structure and manage both simple and more complex multi-commodity deals. Addressing the issues of profit-making and risk management, the book reveals how to exploit pay-off profiles and trading strategies on a diversified set of commodity prices. In addition, the book explores how to price energy products and other commodities belonging to markets segmented across specific structural features. \u003c\/p\u003e\u003cp\u003eThe \u003ci\u003eHandbook of Multi-Commodity Markets and Products\u003c\/i\u003e includes a wealth of proven methods and useful models that can be selected and developed in order to make appropriate estimations of the future evolution of prices and appropriate valuations of products. The authors additionally explore market risk issues and what measures of risk should be adopted for the purpose of accurately assessing exposure from multi-commodity portfolios. \u003c\/p\u003e\u003cp\u003eThis vital resource offers the models, tools, strategies and general information commodity brokers and other professionals need to succeed in today’s highly competitive marketplace.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989337325797,"sku":"NP9780470745243","price":168.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470745243.jpg?v=1761783721","url":"https:\/\/k12savings.com\/products\/handbook-of-multi-commodity-markets-and-products-isbn-9780470745243","provider":"K12savings","version":"1.0","type":"link"}