Energy risk: valuing and managing energy derivatives
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| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
New York, NY [u.a.]
McGraw-Hill
2007
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| Edition: | 2. ed. |
| Subjects: | |
| Online Access: | Table of contents only Inhaltsverzeichnis |
| Physical Description: | XVI, 512 S. Ill., graph. Darst. |
| ISBN: | 9780071485944 0071485945 |
Staff View
MARC
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| 245 | 1 | 0 | |a Energy risk |b valuing and managing energy derivatives |c Dragana Pilipovic |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a New York, NY [u.a.] |b McGraw-Hill |c 2007 | |
| 300 | |a XVI, 512 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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| 338 | |b nc |2 rdacarrier | ||
| 650 | 7 | |a Energia (aspectos econômicos) |2 larpcal | |
| 650 | 4 | |a Electric utilities | |
| 650 | 4 | |a Energy industries | |
| 650 | 4 | |a Commodity futures | |
| 650 | 4 | |a Derivative securities | |
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| adam_text | CONTENTS
PREFACE xiii
ACKNOWLEDGMENTS xv
Chapter 1
Energy Markets: Trading, Modeling, and Hedging 1
1.1. Introduction 1
1.2. Energy Trading 2
1.2.1. Understanding the Fundamentals 2
1.2.2. Liquidity, Volatility, and Intra Market Correlations 4
1.2.3. Market Deregulation 6
1.3. Energy Modeling 8
1.3.1. Energies Are Still Unique 8
1.3.2. Model Complexity 8
1.3.3. Quants vs. Traders vs. Reality 9
1.4. Energy Hedging and Risk Management 10
1.4.1. Adding Financial Products to the Hedging Mix 10
1.4.2. Risk Management: A Profitable Business Function? 11
1.4.3. Hedging for the Little Guys 12
1.4.4. Assets as Hedges 12
1.4.5. Regulatory Response to Bad Stories 13
1.5. Conclusions 14
Chapter 2
What Makes Energies So Different? 17
2.1. Introduction 17
2.1.1. Quantitative and Fundamental Analysis IS
2.2. What Makes Energies So Different? 19
2.3. Energies Are Harder to Model 20
2.4. Market Response to Cycles and Events 23
2.5. Impact on Supply Drivers 26
2.6. Energies Have a Split Personality 28
2.7. Impact of Demand Drivers 28
Contents
2.7.1. The Convenience Yield 29
2.7.2. Seasonality 30
2.8. Regulation and Illiquidity 31
2.9. Decentralization of Markets and Expertise 31
2.10. Energies Require More Exotic Contracts 32
2.11. Conclusion 33
Chapter 3
Modeling Principles and Market Behavior 35
3.1. The Modeling Process 35
3.2. The Value of Benchmarks 36
3.2.1. Diffusing Personalized Attachments to Models 36
3.3. The Ideal Modeling Process 38
3.4. The Role of Assumptions: Market Before Theory 38
3.4.1. Typical Assumptions 39
3.4.2. Market Variable vs. Modeling Parameter 41
3.4.3. Testing Assumptions Through Benchmarks 42
3.4.4. Assumptions and Implementation 45
3.5. Contract Terms and Issues 45
3.5.1. Underlying Price or Market 45
3.5.2. Derivative Contract 46
3.5.3. Option Settlement Price 46
3.5.4. Delivery 46
3.5.5. Complexity of Contracts for Delivery 47
3.6. Modeling Terms and Issues 49
3.6.1. Price Returns 49
3.6.2. Elements of a Price Model 49
3.6.3. Convenience Yield 52
3.6.4. Cost of Risk 54
3.7. Quantitative Financial Models Across Markets 55
3.7.1. Lognormal Market 56
3.7.2. Mean Reverting Market 60
3.8. The Taylor Series and Ito s Lemma 63
3.8.1. The Taylor Series 63
3.8.2. Ito s Lemma 64
3.9. Lessons from Money Markets 65
3.9.1. Modeling Price vs. Rate: Defining the Market Drivers 65
3.9.2. Yield vs. Forward Rate Curves 66
3.9.3. Drawbacks of Single Factor Mean Reverting Models 68
Contents
3.9.4. Drawbacks of Single Factor Non Mean Reverting Models 69
3.9.5. Volatility and Correlation Market Discovery 69
Chapter 4
Essential Statistical Tools 72
4.1. Introduction 71
4.2. Time Series and Distribution Analysis 72
4.2.1. Time Series Analysis 72
4.2.2. Distribution Analysis 75
4.3. Other Statistical Tests 81
4.3.1. The Q Q Plot 81
4.3.2. The Autocorrelation Test 83
4.3.3. Measures of Fit S3
4.4. How Statistics Helps to Understand Reality 85
4.4.1. A Simple Case 85
4.4.2. The Difference Between Price and Return 86
4.4.3. Distinguishing Drift Terms 86
4.5. The Six Step Model Selection Process 88
4.5.1. Step 1: An Informal Look 89
4.5.2. Step 2: A Shortlist of Possible Models 90
4.5.3. Step 3: Time Series Analysis 90
4.5.4. Step 4: From Underlying Price Models to Distributions 91
4.5.5. Step 5: Distribution Analysis 92
4.5.6. Step 6: Select the Most Appropriate Model 93
4.6. Relevance to Option Pricing 93
Chapter 5
Spot Price Behavior 95
5.1. Introduction 95
5.2. Looking at the Actual Market Data 96
5.3. A Shortlist of Possible Models 103
5.3.1. The Lognormal Price Model 103
5.3.2. Mean Reverting Models 105
5.3.3. Cost Based Models for Electric Utilities 111
5.3.4. Interest Rate Models 111
5.4. Calibrating Parameters Through Time Series Analysis 111
5.4.1. Incorporating Seasonality with Underlying Models 112
5.4.2. Results from Time Series Analysis 113
Contents
5.5. Performing Distribution Analysis 119
5.5.1. Implementation of Distribution Analysis 119
5.5.2. Results of Distribution Analysis 120
5.6. Analysis Summary 121
Chapter 6
The Forward Price Curve 127
6.1. Introduction 127
6.1.1. The Difference Between Forwards and Futures 128
6.2. Reading the Underlying Curve 129
6.3. Seasonality in the Forward Curve 132
6.4. Modeling Concepts Relating Spot, Forwards, and Seasonality 135
6.4.1. S P 500 136
6.4.2. WTI Crude Oil 136
6.4.3. Seasonal Markets 137
6.5. Linking Spot Price Models to Forward Price Models 143
6.5.1. The Arbitrage Free Condition 143
6.5.2. Capturing Market Characteristics Within the Model
or During Implementation 145
6.5.3. Influence of the Convenience Yield 145
6.6. Modeling the Underlying Forward Price Curve 147
6.6.1. Difference Between Spot and Forward Prices 147
6.6.2. Going from Spot Price Models to Forward Price Models 150
6.6.3. The Risk Free Portfolio 150
6.6.4. Effect of Dividends 153
6.6.5. Equivalence Between Dividends and the Convenience Yield 155
6.6.6. Adding a Second Factor 156
6.6.7. Seasonality 157
6.7. The Two Factor Mean Reverting Model (Pilipovic) 158
6.8. Testing the Spot Price Model on Forward Price Data 162
Chapter 7
Building Marked to Market Forward Price Curves:
Implementing Forward Price Models 163
7.1. Introduction: What Is a Marked to Market Forward Price Curve? 164
7.2. Forward Price Contract Valuation 166
7.2.1. Simple Contract for One Day Delivery 170
7.2.2. Contract for Delivery Over a Period 173
7.2.3. Bootstrapping and the Problem of Daily Price Discovery 179
Contents
7.3. Fitting the Modeling Needs to Trading Needs 182
7.3.1. Case of Trading Exchange Traded Products Only 182
7.3.2. Case of Trading OTC 183
7.3.3. Case of Owning Power Production 184
7.4. Building Marked to Market Forward Price Curves:
Issues to Consider 184
7.4.1. Quote Strips 184
7.4.2. Step Function Treatment 187
7.4.3. Linear Interpolation 187
7.4.4. Applying Forward Price Models Based on Spot Price Analysis 188
7.4.5. Many Degrees of Freedom Within Implementation:
Part Art, Part Science 189
7.4.6. From Events to Models 191
1.4.1. Parameter Calibration 192
7.5. Modeling Middle Term Event Expectations 193
7.6. Modeling Forward Price Seasonality 195
7.6.1. Cosine Seasonality 196
7.6.2. Exponential Seasonality 197
7.6.3. Power N Model—Flat Seasonality 201
7.6.4. Multiperiod Seasonality Treatment 201
7.7. Special Case of Basis Markets 205
7.8. Noise Versus Events 209
7.9. Markets with Little or No Market Discovery: Off Peak and Hourly
Forward Price Curves 211
7.10. Conclusion 212
Chapter 8
Volatilities 215
8.1. Introduction 215
8.2. Measuring Randomness 216
8.2.1. Standard Deviation and Variance 216
8.2.2. Volatility Defined 217
8.2.3. Comparing Variance and Volatility 218
8.2.4. Variance and Volatility in Spot Price Models 218
8.3. The Stochastic Term 220
8.3.1. Case of Constant Volatility 220
8.3.2. Case of Volatilities with Term Structure 221
8.4. Measuring Historical Volatilities 222
8.4.1. Simple Techniques 222
8.4.2. More Complex Techniques 223
Contents
8.5. Market Implied Volatilities 224
8.5.1. Option Implied Volatilities 224
8.5.2. Implied Volatilities from a Series of Options 225
8.5.3. Calibrating Caplet Volatility Term Structure 226
8.5.4. Implied Volatilities from Options on the Average of Price 230
8.5.5. The Volatility Smile 232
8.6. Model Implied Volatilities 232
8.6.1. The Lognormal Model 233
8.6.2. The Log of Price Mean Reverting Model 234
8.6.3. The Price Mean Reverting Model 236
8.7. Building the Volatility Matrix 240
8.7.1. Introduction to the Forward Volatility Matrix 241
8.7.2. Discrete Volatilities 242
8.7.3. Tying In Caplet Volatilities 244
8.7.4. Two Dimensional Approach to Volatility Term Structure 246
8.7.5. Tying In Historical Volatilities 249
8.7.6. Tying In Caplet and Swaption Prices 249
8.8. Implementing the Volatility Matrix 251
Chapter 9
Overview of Option Pricing for Energies 255
9.1. Introduction 255
9.2. Basic Concepts of Option Pricing 256
9.2.1. Parity Value 256
9.2.2. Settlement 258
9.3. Types of Options 258
9.3.1. European Options 259
9.3.2. American Options 259
9.3.3. Asian Options: Options on an Average of Price 259
9.3.4. Swing Options 260
9.4. Effect of Underlying Behavior 261
9.5. Option Pricing Implementation Techniques 263
9.5.1. Closed Form Solutions 263
9.5.2. Simulations 265
9.5.3. Trees 266
9.5.4. Human Error in Implementation 267
9.6. Choosing the Right Option Pricing Model 267
9.6.1. Three Criteria for Evaluating Option Models 268
9.6.2. Investing in Pricing Model versus Implementation 269
9.6.3. A Model Is Only as Good as Its Implementation 270
Contents
9.7. Option Valuation Process: What Should It Be? 270
9.7.1. Defining Underlying Market Price Behavior 270
9.7.2. Testing Alternative Models 271
9.7.3. Selecting the Most Appropriate Option Model 272
9.8. Did That Option Make Money? 273
Chapter 10
Option Valuation 275
10.1. Introduction 275
10.2. Option Model Implementation 276
10.3. Closed Form Solutions 276
10.3.1. Pros 276
10.3.2. Cons 277
10.3.3. The Black Scholes Model 277
10.3.4. The Black Model 279
10.4. Approximations to Closed Form Solutions 283
10.4.1. Pros 283
10.4.2. Cons 284
10.4.3. The Volatility Smile 284
10.4.4. The Edgeworth Series Expansion 285
10.4.5. Pulling It All Together 288
10.5. The Tree Approach 290
10.5.1. Pros 291
10.5.2. Cons 291
10.5.3. Binomial Trees 292
10.5.4. Trinomial Trees 292
10.5.5. Using a Tree to Value a European Style Option 293
10.5.6. Using a Tree to Value an American Style Option 295
10.5.7. Energy Specific American Style Options 295
10.6. Monte Carlo Simulations 300
10.7. Conclusions 302
Chapter 11
Valuing Energy Options 303
11.1. Introduction 303
11.2. Daily Settled Options 304
11.2.1. Extending Daily Methodology to Hourly
Settled Options 312
Contents
11.3. Monthly Settled Options 313
11.3.1. Cash Settled: Look Back Monthly Settled Average
Price Options 314
11.3.2. Monthly Settled (Look Forward) Options on Monthly
Forwards 317
11.3.3. Incorporating Price Mean Reversion (PMR) into Monthly
Settled Options 326
11.3.4. Extending Monthly Methodology to Calendar Year Options 332
11.4. Optionality in Cheapest to Deliver Forward Prices 333
11.5. Types of Energy Swing Options 334
11.6. Demand Swing Contracts 336
11.6.1. Demand Swing Options 336
11.6.2. Demand Swing Forwards 339
11.6.3. Load Behavior 340
11.7. Price Swing Contracts 345
11.7.1. Multiple Peaker Swing Options 346
11.7.2. Forward Starting Swing 358
11.7.3. Natural Gas Storage 360
11.8. Spread Options 361
11.8.1. Various Approximations to Spread Option Valuation 362
11.8.2. The Tree Approach 370
11.8.3. Crack Spread, Spark Spread, and Basis
Spread Options 372
11.8.4. Valuing Power Plants and Transmission Lines 372
11.9. Conclusion 373
Chapter 12
Measuring Risk 375
12.1. Introduction 375
12.2. The Risk/Return Framework 375
12.3. Types of Risk 377
12.3.1. Market Risk 378
12.3.2. Commodity Risk 378
12.3.3. Human Error 378
12.3.4. Model Risk 379
12.4. Definition of a Portfolio 380
12.4.1. Change in Portfolio Value 381
12.4.2. Time Buckets 381
12.5. Measuring Changes in Portfolio Value 383
12.5.1. Taylor Series 383
Contents
12.6. Portfolio Sensitivity: The Greeks 385
12.6.1. Delta: Sensitivity to Price Change 385
12.6.2. Vega: Sensitivity to Volatility Change 386
12.6.3. Theta: Sensitivity to Time 388
12.6.4. Rho: Sensitivity to Discounting Rates 391
12.6.5. Gamma: Sensitivity to Changes in Delta 391
12.6.6. Quantity Specific Risks 394
12.6.7. Sensitivity to Correlation Change 394
12.7. Hedging 395
12.8. Marking to Market 396
12.8.1. Information for Marking to Market 396
12.8.2. Mark to Market Valuation 397
12.8.3. Testing the Mark to Market Process 398
Chapter 13
Portfolio Analysis 401
13.1. Introduction 401
13.2. Applications of Portfolio Analysis 402
13.3. Analyzing the Change in Portfolio Value 402
13.4. The Minimum Variance Method 404
13.4.1. The Hedged Portfolio 405
13.4.2. Per Deal Hedges 406
13.4.3. Portfolio with Options 410
13.4.4. Lessons from Inadequate Hedging Policies 411
13.5. The Generalized Minimum Variance Model 417
13.6. Correlations 417
13.7. Value at Risk (VAR) Analysis 418
13.7.1. Fixed Scenario Stress Simulations 420
13.7.2. Monte Carlo Simulations 420
13.7.3. Estimated Variance Covariance Method 422
13.7.4. Historical Simulations 422
13.8. The Special Case of Electricity 423
13.9. The Corporate Utility Function 424
Chapter 14
Risk Management Policies 427
14.1. Introduction 427
14.2. The Case for a Risk Management Policy 428
14.2.1. Horror Stories 429
Contents
14.3. Risk Management Goals and Strategies 430
14.3.1. Speculation 431
14.3.2. Arbitrage 432
14.3.3. Market Maker 433
14.3.4. Treasury 434
14.3.5. Mixed Strategies 434
14.4. Initial Evaluation Checklist 435
14.4.1. Diagnosing and Selecting Trading Strategies 437
14.4.2. Gaps Between Existing and Desired Market Position 438
14.4.3. Corporate Culture 438
14.5. The Front/Middle/Back Office Paradigm 439
14.5.1. Conflicts Between Offices 440
14.5.2. Interoffice Committees 441
14.6. The Energy Team 441
14.6.1. Appropriate Knowledge by Organizational Level
and Functions 444
14.6.2. Management Issues 445
14.6.3. Common Management Misconceptions 450
14.7. Implementation of Risk Management Policies 453
Appendix A: Mathematical and Statistical Notes 455
Appendix B: Models from Interest Rate and Bond Markets 463
Appendix C: Analysis of Markets Published in the First Edition
of Energy Risk 467
Glossary of Energy Risk Management Terms 485
Select Bibliography 499
INDEX 503
|
| adam_txt |
CONTENTS
PREFACE xiii
ACKNOWLEDGMENTS xv
Chapter 1
Energy Markets: Trading, Modeling, and Hedging 1
1.1. Introduction 1
1.2. Energy Trading 2
1.2.1. Understanding the Fundamentals 2
1.2.2. Liquidity, Volatility, and Intra Market Correlations 4
1.2.3. Market Deregulation 6
1.3. Energy Modeling 8
1.3.1. Energies Are Still Unique 8
1.3.2. Model Complexity 8
1.3.3. Quants vs. Traders vs. Reality 9
1.4. Energy Hedging and Risk Management 10
1.4.1. Adding Financial Products to the Hedging Mix 10
1.4.2. Risk Management: A Profitable Business Function? 11
1.4.3. Hedging for the Little Guys 12
1.4.4. Assets as Hedges 12
1.4.5. Regulatory Response to "Bad" Stories 13
1.5. Conclusions 14
Chapter 2
What Makes Energies So Different? 17
2.1. Introduction 17
2.1.1. Quantitative and Fundamental Analysis IS
2.2. What Makes Energies So Different? 19
2.3. Energies Are Harder to Model 20
2.4. Market Response to Cycles and Events 23
2.5. Impact on Supply Drivers 26
2.6. Energies Have a "Split Personality" 28
2.7. Impact of Demand Drivers 28
Contents
2.7.1. The Convenience Yield 29
2.7.2. Seasonality 30
2.8. Regulation and Illiquidity 31
2.9. Decentralization of Markets and Expertise 31
2.10. Energies Require More Exotic Contracts 32
2.11. Conclusion 33
Chapter 3
Modeling Principles and Market Behavior 35
3.1. The Modeling Process 35
3.2. The Value of Benchmarks 36
3.2.1. Diffusing Personalized Attachments to Models 36
3.3. The Ideal Modeling Process 38
3.4. The Role of Assumptions: Market Before Theory 38
3.4.1. Typical Assumptions 39
3.4.2. Market Variable vs. Modeling Parameter 41
3.4.3. Testing Assumptions Through Benchmarks 42
3.4.4. Assumptions and Implementation 45
3.5. Contract Terms and Issues 45
3.5.1. Underlying Price or Market 45
3.5.2. Derivative Contract 46
3.5.3. Option Settlement Price 46
3.5.4. Delivery 46
3.5.5. Complexity of Contracts for Delivery 47
3.6. Modeling Terms and Issues 49
3.6.1. Price Returns 49
3.6.2. Elements of a Price Model 49
3.6.3. Convenience Yield 52
3.6.4. Cost of Risk 54
3.7. Quantitative Financial Models Across Markets 55
3.7.1. Lognormal Market 56
3.7.2. Mean Reverting Market 60
3.8. The Taylor Series and Ito's Lemma 63
3.8.1. The Taylor Series 63
3.8.2. Ito's Lemma 64
3.9. Lessons from Money Markets 65
3.9.1. Modeling Price vs. Rate: Defining the Market Drivers 65
3.9.2. Yield vs. Forward Rate Curves 66
3.9.3. Drawbacks of Single Factor Mean Reverting Models 68
Contents
3.9.4. Drawbacks of Single Factor Non Mean Reverting Models 69
3.9.5. Volatility and Correlation Market Discovery 69
Chapter 4
Essential Statistical Tools 72
4.1. Introduction 71
4.2. Time Series and Distribution Analysis 72
4.2.1. Time Series Analysis 72
4.2.2. Distribution Analysis 75
4.3. Other Statistical Tests 81
4.3.1. The Q Q Plot 81
4.3.2. The Autocorrelation Test 83
4.3.3. Measures of Fit S3
4.4. How Statistics Helps to Understand Reality 85
4.4.1. A Simple Case 85
4.4.2. The Difference Between Price and Return 86
4.4.3. Distinguishing Drift Terms 86
4.5. The Six Step Model Selection Process 88
4.5.1. Step 1: An Informal Look 89
4.5.2. Step 2: A Shortlist of Possible Models 90
4.5.3. Step 3: Time Series Analysis 90
4.5.4. Step 4: From Underlying Price Models to Distributions 91
4.5.5. Step 5: Distribution Analysis 92
4.5.6. Step 6: Select the Most Appropriate Model 93
4.6. Relevance to Option Pricing 93
Chapter 5
Spot Price Behavior 95
5.1. Introduction 95
5.2. Looking at the Actual Market Data 96
5.3. A Shortlist of Possible Models 103
5.3.1. The Lognormal Price Model 103
5.3.2. Mean Reverting Models 105
5.3.3. Cost Based Models for Electric Utilities 111
5.3.4. Interest Rate Models 111
5.4. Calibrating Parameters Through Time Series Analysis 111
5.4.1. Incorporating Seasonality with Underlying Models 112
5.4.2. Results from Time Series Analysis 113
Contents
5.5. Performing Distribution Analysis 119
5.5.1. Implementation of Distribution Analysis 119
5.5.2. Results of Distribution Analysis 120
5.6. Analysis Summary 121
Chapter 6
The Forward Price Curve 127
6.1. Introduction 127
6.1.1. The Difference Between Forwards and Futures 128
6.2. Reading the Underlying Curve 129
6.3. Seasonality in the Forward Curve 132
6.4. Modeling Concepts Relating Spot, Forwards, and Seasonality 135
6.4.1. S P 500 136
6.4.2. WTI Crude Oil 136
6.4.3. Seasonal Markets 137
6.5. Linking Spot Price Models to Forward Price Models 143
6.5.1. The Arbitrage Free Condition 143
6.5.2. Capturing Market Characteristics Within the Model
or During Implementation 145
6.5.3. Influence of the Convenience Yield 145
6.6. Modeling the Underlying Forward Price Curve 147
6.6.1. Difference Between Spot and Forward Prices 147
6.6.2. Going from Spot Price Models to Forward Price Models 150
6.6.3. The Risk Free Portfolio 150
6.6.4. Effect of Dividends 153
6.6.5. Equivalence Between Dividends and the Convenience Yield 155
6.6.6. Adding a Second Factor 156
6.6.7. Seasonality 157
6.7. The Two Factor Mean Reverting Model (Pilipovic) 158
6.8. Testing the Spot Price Model on Forward Price Data 162
Chapter 7
Building Marked to Market Forward Price Curves:
Implementing Forward Price Models 163
7.1. Introduction: What Is a Marked to Market Forward Price Curve? 164
7.2. Forward Price Contract Valuation 166
7.2.1. Simple Contract for One Day Delivery 170
7.2.2. Contract for Delivery Over a Period 173
7.2.3. Bootstrapping and the Problem of Daily Price Discovery 179
Contents
7.3. Fitting the Modeling Needs to Trading Needs 182
7.3.1. Case of Trading Exchange Traded Products Only 182
7.3.2. Case of Trading OTC 183
7.3.3. Case of Owning Power Production 184
7.4. Building Marked to Market Forward Price Curves:
Issues to Consider 184
7.4.1. Quote Strips 184
7.4.2. Step Function Treatment 187
7.4.3. Linear Interpolation 187
7.4.4. Applying Forward Price Models Based on Spot Price Analysis 188
7.4.5. Many Degrees of Freedom Within Implementation:
Part Art, Part Science 189
7.4.6. From Events to Models 191
1.4.1. Parameter Calibration 192
7.5. Modeling Middle Term Event Expectations 193
7.6. Modeling Forward Price Seasonality 195
7.6.1. Cosine Seasonality 196
7.6.2. Exponential Seasonality 197
7.6.3. Power N Model—Flat Seasonality 201
7.6.4. Multiperiod Seasonality Treatment 201
7.7. Special Case of Basis Markets 205
7.8. Noise Versus Events 209
7.9. Markets with Little or No Market Discovery: Off Peak and Hourly
Forward Price Curves 211
7.10. Conclusion 212
Chapter 8
Volatilities 215
8.1. Introduction 215
8.2. Measuring Randomness 216
8.2.1. Standard Deviation and Variance 216
8.2.2. Volatility Defined 217
8.2.3. Comparing Variance and Volatility 218
8.2.4. Variance and Volatility in Spot Price Models 218
8.3. The Stochastic Term 220
8.3.1. Case of Constant Volatility 220
8.3.2. Case of Volatilities with Term Structure 221
8.4. Measuring Historical Volatilities 222
8.4.1. Simple Techniques 222
8.4.2. More Complex Techniques 223
Contents
8.5. Market Implied Volatilities 224
8.5.1. Option Implied Volatilities 224
8.5.2. Implied Volatilities from a Series of Options 225
8.5.3. Calibrating Caplet Volatility Term Structure 226
8.5.4. Implied Volatilities from Options on the Average of Price 230
8.5.5. The Volatility Smile 232
8.6. Model Implied Volatilities 232
8.6.1. The Lognormal Model 233
8.6.2. The Log of Price Mean Reverting Model 234
8.6.3. The Price Mean Reverting Model 236
8.7. Building the Volatility Matrix 240
8.7.1. Introduction to the Forward Volatility Matrix 241
8.7.2. Discrete Volatilities 242
8.7.3. Tying In Caplet Volatilities 244
8.7.4. Two Dimensional Approach to Volatility Term Structure 246
8.7.5. Tying In Historical Volatilities 249
8.7.6. Tying In Caplet and Swaption Prices 249
8.8. Implementing the Volatility Matrix 251
Chapter 9
Overview of Option Pricing for Energies 255
9.1. Introduction 255
9.2. Basic Concepts of Option Pricing 256
9.2.1. Parity Value 256
9.2.2. Settlement 258
9.3. Types of Options 258
9.3.1. European Options 259
9.3.2. American Options 259
9.3.3. Asian Options: Options on an Average of Price 259
9.3.4. Swing Options 260
9.4. Effect of Underlying Behavior 261
9.5. Option Pricing Implementation Techniques 263
9.5.1. Closed Form Solutions 263
9.5.2. Simulations 265
9.5.3. Trees 266
9.5.4. Human Error in Implementation 267
9.6. Choosing the Right Option Pricing Model 267
9.6.1. Three Criteria for Evaluating Option Models 268
9.6.2. Investing in Pricing Model versus Implementation 269
9.6.3. A Model Is Only as Good as Its Implementation 270
Contents
9.7. Option Valuation Process: What Should It Be? 270
9.7.1. Defining Underlying Market Price Behavior 270
9.7.2. Testing Alternative Models 271
9.7.3. Selecting the Most Appropriate Option Model 272
9.8. Did That Option Make Money? 273
Chapter 10
Option Valuation 275
10.1. Introduction 275
10.2. Option Model Implementation 276
10.3. Closed Form Solutions 276
10.3.1. Pros 276
10.3.2. Cons 277
10.3.3. The Black Scholes Model 277
10.3.4. The Black Model 279
10.4. Approximations to Closed Form Solutions 283
10.4.1. Pros 283
10.4.2. Cons 284
10.4.3. The Volatility Smile 284
10.4.4. The Edgeworth Series Expansion 285
10.4.5. Pulling It All Together 288
10.5. The Tree Approach 290
10.5.1. Pros 291
10.5.2. Cons 291
10.5.3. Binomial Trees 292
10.5.4. Trinomial Trees 292
10.5.5. Using a Tree to Value a European Style Option 293
10.5.6. Using a Tree to Value an American Style Option 295
10.5.7. Energy Specific American Style Options 295
10.6. Monte Carlo Simulations 300
10.7. Conclusions 302
Chapter 11
Valuing Energy Options 303
11.1. Introduction 303
11.2. Daily Settled Options 304
11.2.1. Extending Daily Methodology to Hourly
Settled Options 312
Contents
11.3. Monthly Settled Options 313
11.3.1. Cash Settled: Look Back Monthly Settled Average
Price Options 314
11.3.2. Monthly Settled (Look Forward) Options on Monthly
Forwards 317
11.3.3. Incorporating Price Mean Reversion (PMR) into Monthly
Settled Options 326
11.3.4. Extending Monthly Methodology to Calendar Year Options 332
11.4. Optionality in Cheapest to Deliver Forward Prices 333
11.5. Types of Energy Swing Options 334
11.6. Demand Swing Contracts 336
11.6.1. Demand Swing Options 336
11.6.2. Demand Swing Forwards 339
11.6.3. Load Behavior 340
11.7. Price Swing Contracts 345
11.7.1. Multiple Peaker Swing Options 346
11.7.2. Forward Starting Swing 358
11.7.3. Natural Gas Storage 360
11.8. Spread Options 361
11.8.1. Various Approximations to Spread Option Valuation 362
11.8.2. The Tree Approach 370
11.8.3. Crack Spread, Spark Spread, and Basis
Spread Options 372
11.8.4. Valuing Power Plants and Transmission Lines 372
11.9. Conclusion 373
Chapter 12
Measuring Risk 375
12.1. Introduction 375
12.2. The Risk/Return Framework 375
12.3. Types of Risk 377
12.3.1. Market Risk 378
12.3.2. Commodity Risk 378
12.3.3. Human Error 378
12.3.4. Model Risk 379
12.4. Definition of a Portfolio 380
12.4.1. Change in Portfolio Value 381
12.4.2. Time Buckets 381
12.5. Measuring Changes in Portfolio Value 383
12.5.1. Taylor Series 383
Contents
12.6. Portfolio Sensitivity: The "Greeks" 385
12.6.1. Delta: Sensitivity to Price Change 385
12.6.2. Vega: Sensitivity to Volatility Change 386
12.6.3. Theta: Sensitivity to Time 388
12.6.4. Rho: Sensitivity to Discounting Rates 391
12.6.5. Gamma: Sensitivity to Changes in Delta 391
12.6.6. Quantity Specific Risks 394
12.6.7. Sensitivity to Correlation Change 394
12.7. Hedging 395
12.8. Marking to Market 396
12.8.1. Information for Marking to Market 396
12.8.2. Mark to Market Valuation 397
12.8.3. Testing the Mark to Market Process 398
Chapter 13
Portfolio Analysis 401
13.1. Introduction 401
13.2. Applications of Portfolio Analysis 402
13.3. Analyzing the Change in Portfolio Value 402
13.4. The Minimum Variance Method 404
13.4.1. The Hedged Portfolio 405
13.4.2. Per Deal Hedges 406
13.4.3. Portfolio with Options 410
13.4.4. Lessons from Inadequate Hedging Policies 411
13.5. The Generalized Minimum Variance Model 417
13.6. Correlations 417
13.7. Value at Risk (VAR) Analysis 418
13.7.1. Fixed Scenario Stress Simulations 420
13.7.2. Monte Carlo Simulations 420
13.7.3. Estimated Variance Covariance Method 422
13.7.4. Historical "Simulations" 422
13.8. The Special Case of Electricity 423
13.9. The Corporate Utility Function 424
Chapter 14
Risk Management Policies 427
14.1. Introduction 427
14.2. The Case for a Risk Management Policy 428
14.2.1. Horror Stories 429
Contents
14.3. Risk Management Goals and Strategies 430
14.3.1. Speculation 431
14.3.2. Arbitrage 432
14.3.3. Market Maker 433
14.3.4. Treasury 434
14.3.5. Mixed Strategies 434
14.4. Initial Evaluation Checklist 435
14.4.1. Diagnosing and Selecting Trading Strategies 437
14.4.2. Gaps Between Existing and Desired Market Position 438
14.4.3. Corporate Culture 438
14.5. The "Front/Middle/Back Office" Paradigm 439
14.5.1. Conflicts Between Offices 440
14.5.2. Interoffice Committees 441
14.6. The Energy Team 441
14.6.1. Appropriate Knowledge by Organizational Level
and Functions 444
14.6.2. Management Issues 445
14.6.3. Common Management Misconceptions 450
14.7. Implementation of Risk Management Policies 453
Appendix A: Mathematical and Statistical Notes 455
Appendix B: Models from Interest Rate and Bond Markets 463
Appendix C: Analysis of Markets Published in the First Edition
of Energy Risk 467
Glossary of Energy Risk Management Terms 485
Select Bibliography 499
INDEX 503 |
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| author | Pilipović, Dragana |
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| callnumber-raw | HG6047.E43 |
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| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.63/28 |
| dewey-search | 332.63/28 |
| dewey-sort | 3332.63 228 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| edition | 2. ed. |
| format | Book |
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| id | DE-604.BV022652849 |
| illustrated | Illustrated |
| index_date | 2024-07-02T18:22:09Z |
| indexdate | 2024-07-09T21:02:38Z |
| institution | BVB |
| isbn | 9780071485944 0071485945 |
| language | English |
| lccn | 2007004861 |
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| physical | XVI, 512 S. Ill., graph. Darst. |
| publishDate | 2007 |
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| publisher | McGraw-Hill |
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| spelling | Pilipović, Dragana Verfasser aut Energy risk valuing and managing energy derivatives Dragana Pilipovic 2. ed. New York, NY [u.a.] McGraw-Hill 2007 XVI, 512 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Energia (aspectos econômicos) larpcal Electric utilities Energy industries Commodity futures Derivative securities Energiemarkt (DE-588)4014712-5 gnd rswk-swf Derivat Wertpapier (DE-588)4381572-8 gnd rswk-swf Energiemarkt (DE-588)4014712-5 s Derivat Wertpapier (DE-588)4381572-8 s b DE-604 http://www.loc.gov/catdir/toc/ecip0710/2007004861.html Table of contents only HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015858838&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Pilipović, Dragana Energy risk valuing and managing energy derivatives Energia (aspectos econômicos) larpcal Electric utilities Energy industries Commodity futures Derivative securities Energiemarkt (DE-588)4014712-5 gnd Derivat Wertpapier (DE-588)4381572-8 gnd |
| subject_GND | (DE-588)4014712-5 (DE-588)4381572-8 |
| title | Energy risk valuing and managing energy derivatives |
| title_auth | Energy risk valuing and managing energy derivatives |
| title_exact_search | Energy risk valuing and managing energy derivatives |
| title_exact_search_txtP | Energy risk valuing and managing energy derivatives |
| title_full | Energy risk valuing and managing energy derivatives Dragana Pilipovic |
| title_fullStr | Energy risk valuing and managing energy derivatives Dragana Pilipovic |
| title_full_unstemmed | Energy risk valuing and managing energy derivatives Dragana Pilipovic |
| title_short | Energy risk |
| title_sort | energy risk valuing and managing energy derivatives |
| title_sub | valuing and managing energy derivatives |
| topic | Energia (aspectos econômicos) larpcal Electric utilities Energy industries Commodity futures Derivative securities Energiemarkt (DE-588)4014712-5 gnd Derivat Wertpapier (DE-588)4381572-8 gnd |
| topic_facet | Energia (aspectos econômicos) Electric utilities Energy industries Commodity futures Derivative securities Energiemarkt Derivat Wertpapier |
| url | http://www.loc.gov/catdir/toc/ecip0710/2007004861.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015858838&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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