Measuring market risk:
CD-ROM contains: MATLAB folder of risk measurement functions -- Examples in Excel/VBA.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Chichester
Wiley
2002
|
| Schriftenreihe: | Wiley finance series
|
| Schlagworte: | |
| Online-Zugang: | Table of contents Inhaltsverzeichnis |
| Zusammenfassung: | CD-ROM contains: MATLAB folder of risk measurement functions -- Examples in Excel/VBA. |
| Beschreibung: | XIX, 370 S. graph. Darst. |
| ISBN: | 0471521744 |
Internformat
MARC
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| 520 | 3 | |a CD-ROM contains: MATLAB folder of risk measurement functions -- Examples in Excel/VBA. | |
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| 650 | 4 | |a Risk management | |
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Datensatz im Suchindex
| _version_ | 1804129313972289536 |
|---|---|
| adam_text | Contents Preface xi
Acknowledgements xxi
1 The Risk Measurement Revolution 1
1.1 Contributory Factors 1
1.1.1 A Volatile Environment 1
1.1.2 Growth in Trading Activity 2
1.1.3 Advances in Information Technology 3
1.2 Risk Measurement Before VaR 3
1.2.1 Gap Analysis 3
1.2.2 Duration Analysis 4
1.2.3 Scenario Analysis 5
1.2.4 Portfolio Theory 5
1.2.5 Derivatives Risk Measures 7
1.3 Value at Risk 8
1.3.1 The Origin and Development of VaR 8
1.3.2 Attractions of VaR 10
1.3.3 Criticisms of VaR 11
1.4 Recommended Reading 13
2 Measures of Financial Risk 15
2.1 The Mean Variance Framework For Measuring Financial Risk 15
2.1.1 The Normality Assumption 15
2.1.2 Limitations of the Normality Assumption 17
2.1.3 Traditional Approaches to Financial Risk Measurement 20
2.1.3.1 Portfolio Theory 20
2.1.3.2 Duration Approaches to Fixed income
Risk Measurement 21
2.2 Value at Risk 21
2.2.1 VaR Basics 21
2.2.2 Choice of VaR Parameters 27
vi Contents 2.2.3 Limitations of VaR as a Risk Measure 28
2.2.3.1 VaR Uninformative of Tail Losses 28
2.2.3.2 VaR Can Create Perverse Incentive Structures 28
2.2.3.3 VaR Can Discourage Diversification 29
2.2.3.4 VaR Not Sub additive 30
2.3 Expected Tail Loss 31
2.3.1 Coherent Risk Measures 31
2.3.2 The Expected Tail Loss 32
2.4 Conclusions 36
2.5 Recommended Reading 36
3 Basic Issues in Measuring Market Risk 37
3.1 Data 37
3.1.1 Profit/Loss Data 37
3.1.2 Loss/Profit Data 38
3.1.3 Arithmetic Returns Data 38
3.1.4 Geometric Returns Data 38
3.2 Estimating Historical Simulation VaR 39
3.3 Estimating Parametric VaR 40
3.3.1 Estimating VaR with Normally Distributed Profits/Losses 40
3.3.2 Estimating VaR with Normally Distributed Arithmetic Returns 42
3.3.3 Estimating Lognormal VaR 42
3.4 Estimating Expected Tail Loss 43
3.5 Summary 46
Appendix: Mapping Positions to Risk Factors 47
A3.1 Selecting Core Instruments or Factors 48
A3.1.1 Selecting Core Instruments 48
A3.1.2 Selecting Core Factors 49
A3.2 Mapping Positions and VaR Estimation 49
A3.2.1 The Basic Building Blocks 50
A3.2.1.1 Basic FX Positions 50
A3.2.1.2 Basic Equity Positions 50
A3.2.1.3 Zero coupon Bonds 52
A3.2.1.4 Basic Forwards/Futures 54
A3.2.2 More Complex Positions 55
A3.3 Recommended Reading 56
4 Non parametric VaR and ETL 57
4.1 Compiling Historical Simulation Data 57
4.2 Estimation of Historical Simulation VaR and ETL 58
4.2.1 Basic Historical Simulation 58
4.2.2 Historical Simulation Using Non parametric Density Estimation 59
4.2.3 Estimating Curves and Surfaces for VaR and ETL 61
4.3 Estimating Confidence Intervals for Historical Simulation VaR and ETL 62
4.3.1 A Quantile Standard Error Approach to the Estimation of
Confidence Intervals for HS VaR and ETL 62
^ Contents vii
4.3.2 An Order Statistics Approach to the Estimation of Confidence
Intervals for HS VaR and ETL 62
4.3.3 A Bootstrap Approach to the Estimation of Confidence Intervals for
HS VaR and ETL 63
4.4 Weighted Historical Simulation 65
4.4.1 Age weighted Historical Simulation 66
4.4.2 Volatility weighted Historical Simulation 67
4.4.3 Filtered Historical Simulation 69
4.5 Advantages and Disadvantages of Historical Simulation 72
4.5.1 Advantages 72
4.5.2 Disadvantages 72
4.5.2.1 Total Dependence on the Data Set 72
4.5.2.2 Problems of Data Period Length 73
4.6 Principal Components and Related Approaches to VaR and
ETL Estimation 74
4.7 Conclusions 74
4.8 Recommended Reading 75
5 Parametric VaR and ETL 77
5.1 Normal VAR and ETL 78
5.1.1 General Features 78
5.1.2 Disadvantages of Normality 82
5.2 The Student / distribution 82
5.3 The Lognormal Distribution 85
5.4 Extreme Value Distributions 88
5.4.1 The Generalised Extreme Value Distribution 89
5.4.2 The Peaks Over Threshold (Generalised Pareto) Approach 90
5.5 Miscellaneous Parametric Approaches 92
5.5.1 Stable Levy Approaches 92
5.5.2 Elliptical and Hyperbolic Approaches 92
5.5.3 Normal Mixture Approaches 93
5.5.4 The Cornish Fisher Approximation 95
5.6 The Multivariate Normal Variance Covariance Approach 96
5.7 Non normal Variance Covariance Approaches 99
5.7.1 Elliptical Variance Covariance Approaches 99
5.7.2 The Hull White Transformation to normality Approach 100
5.8 Handling Multivariate Return Distributions With Copulas 101
5.9 Conclusions 102
5.10 Recommended Reading 104
Appendix 1: Delta Gamma and Related Approximations 105
A5.1 Delta Normal Approaches 105
A5.2 Delta Gamma Approaches 107
A5.2.1 The Delta Gamma Approximation 107
A5.2.2 The Delta Gamma Normal Approach 107
A5.2.3 Wilson s Delta Gamma Approach 108
A5.2.4 Other Delta Gamma Approaches 110
viii Contents A5.3 Conclusions 111
A5.4 Recommended Reading 112
Appendix 2: Solutions for Options VaR? 113
A5.5 When and How Can We Solve for Options VaR 113
A5.6 Measuring Options VaR and ETL 115
A5.6.1 A General Framework for Measuring Options Risks 115
A5.6.2 A Worked Example: Measuring the VaR of a European
Call Option 116
A5.6.3 VaR/ETL Approaches and Greek Approaches to
Options Risk 121
A5.7 Recommended Reading 122
6 Simulation Approaches to VaR and ETL Estimation 123
6.1 Options VaR and ETL 123
6.1.1 Preliminary Considerations 123
6.1.2 An Example: Estimating the VaR and ETL of an American Put 124
6.1.3 Refining MCS Estimation of Options VaR and ETL 125
6.2 Estimating VaR by Simulating Principal Components 126
6.2.1 Basic Principal Components Simulation 126
6.2.2 Scenario Simulation 127
6.3 Fixed income VaR and ETL 128
6.3.1 General Considerations 128
6.3.1.1 Stochastic Processes for Interest Rates 129
6.3.1.2 The Term Structure of Interest Rates 129
6.3.2 A General Approach to Fixed income VaR and ETL 130
6.4 Estimating VaR and ETL under a Dynamic Portfolio Strategy 131
6.5 Estimating Credit related Risks with Simulation Methods 134
6.6 Estimating Insurance Risks with Simulation Methods 136
6.7 Estimating Pensions Risks with Simulation Methods 136
6.7.1 Estimating Risks of Defined benefit Pension Plans 138
6.7.2 Estimating Risks of Defined contribution Pension Plans 140
6.8 Conclusions 141
6.9 Recommended Reading 142
7 Lattice Approaches to VaR and ETL Estimation 143
7.1 Binomial Tree Methods 143
7.1.1 Introduction to Binomial Tree Methods 143
7.1.2 A Worked Example: Estimating the VaR and ETL of an
American Put with a Binomial Tree 145
7.1.3 Other Considerations 148
7.2 Trinomial Tree Methods 149
7.3 Summary 151
7.4 Recommended Reading 151
8 Incremental and Component Risks 153
8.1 Incremental VaR 153
8.1.1 Interpreting Incremental VaR 153
Contents ix
8.1.2 Estimating IVaR by Brute Force: The Before and After
Approach 154
8.1.3 Estimating IVaR Using Marginal VaRs 155
8.1.3.1 Garman s delVaR Approach 155
8.1.3.2 Potential Drawbacks of the delVaR Approach 158
8.2 Component VaR 159
8.2.1 Properties of Component VaR 159
8.2.2 Uses of Component VaR 161
8.2.2.1 Drill Down Capability 161
8.2.2.2 Reporting Component VaRs 161
8.3 Conclusions 163
8.4 Recommended Reading 163
9 Estimating Liquidity Risks 165
9.1 Liquidity and Liquidity Risks 165
9.2 Estimating Liquidity adjusted VaR and ETL 166
9.2.1 A Transactions Cost Approach 166
9.2.2 The Exogenous Spread Approach 169
9.2.3 The Market Price Response Approach 170
9.2.4 Derivatives Pricing Approaches 170
9.2.5 The Liquidity Discount Approach 171
9.2.6 A Summary and Comparison of Alternative Approaches 172
9.3 Estimating Liquidity at Risk 173
9.4 Estimating Liquidity in Crises 176
9.5 Recommended Reading 177
10 Backtesting Market Risk Models 179
10.1 Preliminary Data Issues 179
10.1.1 Obtaining Data 179
10.2 Statistical Backtests Based on The Frequency of Tail Losses 181
10.2.1 The Basic Frequency of tail losses (or Kupiec) Test 181
10.2.2 The Time to first tail loss Test 183
10.2.3 A Tail loss Confidence interval Test 184
10.2.4 The Conditional Backtesting (Christoffersen) Approach 185
10.3 Statistical Backtests Based on the Sizes of Tail Losses 185
10.3.1 The Basic Sizes of tail losses Test 185
10.3.2 The Crnkovic Drachman Backtest Procedure 188
10.3.3 The Berkowitz Approach 190
10.4 Forecast Evaluation Approaches to Backtesting 191
10.4.1 Basic Ideas 191
10.4.2 The Frequency of tail losses (Lopez I) Approach 192
10.4.3 The Size adjusted Frequency (Lopez II) Approach 193
10.4.4 The Blanco Ihle Approach 193
10.4.5 An Alternative Sizes of tail losses Approach 194
10.5 Comparing Alternative Models 194
10.6 Assessing the Accuracy of Backtest Results 195
10.7 Backtesting With Alternative Confidence Levels, Positions and Data 196
10.7.1 Backtesting with Alternative Confidence Levels 197
x Contents 10.7.2 Backtesting with Alternative Positions 197
10.7.3 Backtesting with Alternative Data 198
10.8 Summary 198
10.9 Recommended Reading 199
11 Stress Testing 201
11.1 Benefits and Difficulties of Stress Testing 203
11.1.1 Benefits of Stress Testing 203
11.1.2 Difficulties with Stress Tests 205
11.2 Scenario Analysis 207
11.2.1 Choosing Scenarios 208
11.2.1.1 Stylised Scenarios 208
11.2.1.2 Actual Historical Events 208
11.2.1.3 Hypothetical One off Events 210
11.2.2 Evaluating the Effects of Scenarios 211
11.3 Mechanical Stress Testing 212
11.3.1 Factor Push Analysis 213
11.3.2 Maximum Loss Optimisation 214
11.4 Conclusions 215
11.5 Recommended Reading 216
12 Model Risk 217
12.1 Models and Model Risk 217
12.1.1 Models 217
12.1.2 Model Risk 218
12.2 Sources of Model Risk 219
12.2.1 Incorrect Model Specification 219
12.2.2 Incorrect Model Application 221
12.2.3 Implementation Risk 222
12.2.4 Other Sources of Model Risk 222
12.2.4.1 Incorrect Calibration 222
12.2.4.2 Programming Problems 223
12.2.4.3 Data Problems 223
12.3 Combating Model Risk 224
12.3.1 Combating Model Risk: Some Guidelines for Risk Practitioners 224
12.3.2 Combating Model Risk: Some Guidelines for Managers 225
12.3.3 Institutional Methods to Combat Model Risk 226
12.3.3.1 Procedures to Vet, Check and Review Models 226
12.3.3.2 Independent Risk Oversight 227
12.4 Conclusions 228
12.5 Recommended Reading 229
Toolkit 231
Bibliography 341
Author Index 355
Subject Index 359
Software Index 369
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| indexdate | 2024-07-09T19:03:10Z |
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| isbn | 0471521744 |
| language | English |
| lccn | 2002071367 |
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| physical | XIX, 370 S. graph. Darst. |
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| spelling | Dowd, Kevin Verfasser aut Measuring market risk Kevin Dowd Chichester Wiley 2002 XIX, 370 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Wiley finance series CD-ROM contains: MATLAB folder of risk measurement functions -- Examples in Excel/VBA. Financial futures Risk management Value at Risk (DE-588)4519495-6 gnd rswk-swf Messung (DE-588)4038852-9 gnd rswk-swf Marktrisiko (DE-588)4506224-9 gnd rswk-swf Marktrisiko (DE-588)4506224-9 s Messung (DE-588)4038852-9 s DE-604 Value at Risk (DE-588)4519495-6 s http://www.loc.gov/catdir/toc/wiley023/2002071367.html Table of contents HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009884555&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Dowd, Kevin Measuring market risk Financial futures Risk management Value at Risk (DE-588)4519495-6 gnd Messung (DE-588)4038852-9 gnd Marktrisiko (DE-588)4506224-9 gnd |
| subject_GND | (DE-588)4519495-6 (DE-588)4038852-9 (DE-588)4506224-9 |
| title | Measuring market risk |
| title_auth | Measuring market risk |
| title_exact_search | Measuring market risk |
| title_full | Measuring market risk Kevin Dowd |
| title_fullStr | Measuring market risk Kevin Dowd |
| title_full_unstemmed | Measuring market risk Kevin Dowd |
| title_short | Measuring market risk |
| title_sort | measuring market risk |
| topic | Financial futures Risk management Value at Risk (DE-588)4519495-6 gnd Messung (DE-588)4038852-9 gnd Marktrisiko (DE-588)4506224-9 gnd |
| topic_facet | Financial futures Risk management Value at Risk Messung Marktrisiko |
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