Measuring Market Risk

Name: Measuring Market Risk
Brand: Wiley
Price: 73.99 EUR
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Kevin Dowd(Author)

Wiley (Publisher)

Published on 9. December 2002

392 pages

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978-0-470-85521-8 (ISBN)

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Content

Intro
Measuring Market Risk
Contents
Preface
Acknowledgements
1 The Risk Measurement Revolution
1.1 Contributory Factors
1.1.1 A Volatile Environment
1.1.2 Growth in Trading Activity
1.1.3 Advances in Information Technology
1.2 Risk Measurement Before VaR
1.2.1 Gap Analysis
1.2.2 Duration Analysis
1.2.3 Scenario Analysis
1.2.4 Portfolio Theory
1.2.5 Derivatives Risk Measures
1.3 Value at Risk
1.3.1 The Origin and Development of VaR
1.3.2 Attractions of VaR
1.3.3 Criticisms of VaR
1.4 Recommended Reading
2 Measures of Financial Risk
2.1 The Mean-Variance Framework For Measuring Financial Risk
2.1.1 The Normality Assumption
2.1.2 Limitations of the Normality Assumption
2.1.3 Traditional Approaches to Financial Risk Measurement
2.1.3.1 Portfolio Theory
2.1.3.2 Duration Approaches to Fixed-income Risk Measurement
2.2 Value at Risk
2.2.1 VaR Basics
2.2.2 Choice of VaR Parameters
2.2.3 Limitations of VaR as a Risk Measure
2.2.3.1 VaR Uninformative of Tail Losses
2.2.3.2 VaR Can Create Perverse Incentive Structures
2.2.3.3 VaR Can Discourage Diversification
2.2.3.4 VaR Not Sub-additive
2.3 Expected Tail Loss
2.3.1 Coherent Risk Measures
2.3.2 The Expected Tail Loss
2.4 Conclusions
2.5 Recommended Reading
3 Basic Issues in Measuring Market Risk
3.1 Data
3.1.1 Profit/Loss Data
3.1.2 Loss/Profit Data
3.1.3 Arithmetic Returns Data
3.1.4 Geometric Returns Data
3.2 Estimating Historical Simulation VaR
3.3 Estimating Parametric VaR
3.3.1 Estimating VaR with Normally Distributed Profits/Losses
3.3.2 Estimating VaR with Normally Distributed Arithmetic Returns
3.3.3 Estimating Lognormal VaR
3.4 Estimating Expected Tail Loss
3.5 Summary
Appendix: Mapping Positions to Risk Factors
A3.1 Selecting Core Instruments or Factors
A3.1.1 Selecting Core Instruments
A3.1.2 Selecting Core Factors
A3.2 Mapping Positions and VaR Estimation
A3.2.1 The Basic Building Blocks
A3.2.1.1 Basic FX Positions
A3.2.1.2 Basic Equity Positions
A3.2.1.3 Zero-coupon Bonds
A3.2.1.4 Basic Forwards/Futures
A3.2.2 More Complex Positions
A3.3 Recommended Reading
4 Non-parametric VaR and ETL
4.1 Compiling Historical Simulation Data
4.2 Estimation of Historical Simulation VaR and ETL
4.2.1 Basic Historical Simulation
4.2.2 Historical Simulation Using Non-parametric Density Estimation
4.2.3 Estimating Curves and Surfaces for VaR and ETL
4.3 Estimating Confidence Intervals for Historical Simulation VaR and ETL
4.3.1 A Quantile Standard Error Approach to the Estimation of Confidence Intervals for HS VaR and ETL
4.3.2 An Order Statistics Approach to the Estimation of Confidence Intervals for HS VaR and ETL
4.3.3 A Bootstrap Approach to the Estimation of Confidence Intervals for HS VaR and ETL
4.4 Weighted Historical Simulation
4.4.1 Age-weighted Historical Simulation
4.4.2 Volatility-weighted Historical Simulation
4.4.3 Filtered Historical Simulation
4.5 Advantages and Disadvantages of Historical Simulation
4.5.1 Advantages
4.5.2 Disadvantages
4.5.2.1 Total Dependence on the Data Set
4.5.2.2 Problems of Data Period Length
4.6 Principal Components and Related Approaches to VaR and ETL Estimation
4.7 Conclusions
4.8 Recommended Reading
5 Parametric VaR and ETL
5.1 Normal VAR and ETL
5.1.1 General Features
5.1.2 Disadvantages of Normality
5.2 The Student t-distribution
5.3 The Lognormal Distribution
5.4 Extreme Value Distributions
5.4.1 The Generalised Extreme Value Distribution
5.4.2 The Peaks Over Threshold (Generalised Pareto) Approach
5.5 Miscellaneous Parametric Approaches
5.5.1 Stable Lévy Approaches
5.5.2 Elliptical and Hyperbolic Approaches
5.5.3 Normal Mixture Approaches
5.5.4 The Cornish-Fisher Approximation
5.6 The Multivariate Normal Variance-Covariance Approach
5.7 Non-normal Variance-Covariance Approaches
5.7.1 Elliptical Variance-Covariance Approaches
5.7.2 The Hull-White Transformation-to-normality Approach
5.8 Handling Multivariate Return Distributions With Copulas
5.9 Conclusions
5.10 Recommended Reading
Appendix 1: Delta-Gamma and Related Approximations
A5.1 Delta-Normal Approaches
A5.2 Delta-Gamma Approaches
A5.2.1 The Delta-Gamma Approximation
A5.2.2 The Delta-Gamma Normal Approach
A5.2.3 Wilson's Delta-Gamma Approach
A5.2.4 Other Delta-Gamma Approaches
A5.3 Conclusions
A5.4 Recommended Reading
Appendix 2: Solutions for Options VaR?
A5.5 When and How Can We Solve for Options VaR
A5.6 Measuring Options VaR and ETL
A5.6.1 A General Framework for Measuring Options Risks
A5.6.2 A Worked Example: Measuring the VaR of a European Call Option
A5.6.3 VaR/ETL Approaches and Greek Approaches to Options Risk
A5.7 Recommended Reading
6 Simulation Approaches to VaR and ETL Estimation
6.1 Options VaR and ETL
6.1.1 Preliminary Considerations
6.1.2 An Example: Estimating the VaR and ETL of an American Put
6.1.3 Refining MCS Estimation of Options VaR and ETL
6.2 Estimating VaR by Simulating Principal Components
6.2.1 Basic Principal Components Simulation
6.2.2 Scenario Simulation
6.3 Fixed-income VaR and ETL
6.3.1 General Considerations
6.3.1.1 Stochastic Processes for Interest Rates
6.3.1.2 The Term Structure of Interest Rates
6.3.2 A General Approach to Fixed-income VaR and ETL
6.4 Estimating VaR and ETL under a Dynamic Portfolio Strategy
6.5 Estimating Credit-related Risks with Simulation Methods
6.6 Estimating Insurance Risks with Simulation Methods
6.7 Estimating Pensions Risks with Simulation Methods
6.7.1 Estimating Risks of Defined-benefit Pension Plans
6.7.2 Estimating Risks of Defined-contribution Pension Plans
6.8 Conclusions
6.9 Recommended Reading
7 Lattice Approaches to VaR and ETL Estimation
7.1 Binomial Tree Methods
7.1.1 Introduction to Binomial Tree Methods
7.1.2 A Worked Example: Estimating the VaR and ETL of an American Put with a Binomial Tree
7.1.3 Other Considerations
7.2 Trinomial Tree Methods
7.3 Summary
7.4 Recommended Reading
8 Incremental and Component Risks
8.1 Incremental VaR
8.1.1 Interpreting Incremental VaR
8.1.2 Estimating IVaR by Brute Force: The 'Before and After' Approach
8.1.3 Estimating IVaR Using Marginal VaRs
8.1.3.1 Garman's 'delVaR' Approach
8.1.3.2 Potential Drawbacks of the delVaR Approach
8.2 Component VaR
8.2.1 Properties of Component VaR
8.2.2 Uses of Component VaR
8.2.2.1 'Drill-Down' Capability
8.2.2.2 Reporting Component VaRs
8.3 Conclusions
8.4 Recommended Reading
9 Estimating Liquidity Risks
9.1 Liquidity and Liquidity Risks
9.2 Estimating Liquidity-adjusted VaR and ETL
9.2.1 A Transactions Cost Approach
9.2.2 The Exogenous Spread Approach
9.2.3 The Market Price Response Approach
9.2.4 Derivatives Pricing Approaches
9.2.5 The Liquidity Discount Approach
9.2.6 A Summary and Comparison of Alternative Approaches
9.3 Estimating Liquidity at Risk
9.4 Estimating Liquidity in Crises
9.5 Recommended Reading
10 Backtesting Market Risk Models
10.1 Preliminary Data Issues
10.1.1 Obtaining Data
10.2 Statistical Backtests Based on The Frequency of Tail Losses
10.2.1 The Basic Frequency-of-tail-losses (or Kupiec) Test
10.2.2 The Time-to-first-tail-loss Test
10.2.3 A Tail-loss Confidence-interval Test
10.2.4 The Conditional Backtesting (Christoffersen) Approach
10.3 Statistical Backtests Based on the Sizes of Tail Losses
10.3.1 The Basic Sizes-of-tail-losses Test
10.3.2 The Crnkovic-Drachman Backtest Procedure
10.3.3 The Berkowitz Approach
10.4 Forecast Evaluation Approaches to Backtesting
10.4.1 Basic Ideas
10.4.2 The Frequency-of-tail-losses (Lopez I) Approach
10.4.3 The Size-adjusted Frequency (Lopez II) Approach
10.4.4 The Blanco-Ihle Approach
10.4.5 An Alternative Sizes-of-tail-losses Approach
10.5 Comparing Alternative Models
10.6 Assessing the Accuracy of Backtest Results
10.7 Backtesting With Alternative Confidence Levels, Positions and Data
10.7.1 Backtesting with Alternative Confidence Levels
10.7.2 Backtesting with Alternative Positions
10.7.3 Backtesting with Alternative Data
10.8 Summary
10.9 Recommended Reading
11 Stress Testing
11.1 Benefits and Difficulties of Stress Testing
11.1.1 Benefits of Stress Testing
11.1.2 Difficulties with Stress Tests
11.2 Scenario Analysis
11.2.1 Choosing Scenarios
11.2.1.1 Stylised Scenarios
11.2.1.2 Actual Historical Events
11.2.1.3 Hypothetical One-off Events
11.2.2 Evaluating the Effects of Scenarios
11.3 Mechanical Stress Testing
11.3.1 Factor Push Analysis
11.3.2 Maximum Loss Optimisation
11.4 Conclusions
11.5 Recommended Reading
12 Model Risk
12.1 Models and Model Risk
12.1.1 Models
12.1.2 Model Risk
12.2 Sources of Model Risk
12.2.1 Incorrect Model Specification
12.2.2 Incorrect Model Application
12.2.3 Implementation Risk
12.2.4 Other Sources of Model Risk
12.2.4.1 Incorrect Calibration
12.2.4.2 Programming Problems
12.2.4.3 Data Problems
12.3 Combating Model Risk
12.3.1 Combating Model Risk: Some Guidelines for Risk Practitioners
12.3.2 Combating Model Risk: Some Guidelines for Managers
12.3.3 Institutional Methods to Combat Model Risk
12.3.3.1 Procedures to Vet, Check and Review Models
12.3.3.2 Independent Risk Oversight
12.4 Conclusions
12.5 Recommended Reading
Toolkit
Bibliography
Author Index
Subject Index
Software Index

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