市场风险评估MEASURING MARKET RISK 2E +CD
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作者： Kevin Dowd 著
出 版 社： John Wiley & Sons
出版时间： 2006-12-1字数：版次： 1页数：印刷时间： 2005/07/01开本：印次：纸张： 胶版纸I S B N ： 9780470013038包装： 精装内容简介
Fully revised and restructured, Measuring Market Risk, Second Edition includes a new chapter on options risk management, as well as substantial new information on parametric risk, non-parametric measurements and liquidity risks, more practical information to help with specific calculations, and new examples including Q&A’s and case studies. The accompanying CD-ROM includes a Measuring Market Risk toolbox, with about 150 risk measurement functions, a manual and a selection of Excel workbooks illustrating basic risk measurement functions.
作者简介:KEVIN DOWD is Professor of Risk Management at Nottingham University Business School, where he works in the Centre for Risk and Insurance Studies. He is also Director of Research for Black Swan Risk Advisors, based in Berkeley, CA. Professor Dowd did his PhD in macroeconomics,and has written extensively on financial and monetary economics, most particularly onfinancial regulation and free banking and, more recently, on financial risk management. He is a regular columnist for 'Financial EngineeringNews'.
目录
Preface to the Second Edition
Acknowledgements
1 The Rise of Value at Risk
1.1 The emergence of financial risk management
1.2 Market risk management
1.3 Risk management before VaR
1.4 Value at risk
Appendix 1: Types of Market Risk
2 Measures of Financial Risk
2.1 The Mean–Variance framework for measuring financial risk
2.2 Value at risk
2.3 Coherent risk measures
2.4 Conclusions
Appendix 1: Probability Functions
Appendix 2: Regulatory Uses of VaR
3 Estimating Market Risk Measures: An Introduction and Overview
3.1 Data
3.2 Estimating historical simulation VaR
3.3 Estimating parametric VaR
3.4 Estimating coherent risk measures
3.5 Estimating the standard errors of risk measure estimators
3.6 Overview
Appendix 1: Preliminary Data Analysis
Appendix 2: Numerical Integration Methods
4 Non-parametric Approaches
4.1 Compiling historical simulation data
4.2 Estimation of historical simulation VaR and ES
4.3 Estimating confidence intervals for historical simulation VaR and ES
4.4 Weighted historical simulation
4.5 Advantages and disadvantages of non-parametric methods
4.6 Conclusions
Appendix 1: Estimating Risk Measures with Order Statistics
Appendix 2: The Bootstrap
Appendix 3: Non-parametric Density Estimation
Appendix 4: Principal Components Analysis and Factor Analysis
5 Forecasting Volatilities, Covariances and Correlations
5.1 Forecasting volatilities
5.2 Forecasting covariances and correlations
5.3 Forecasting covariance matrices
Appendix 1: Modelling Dependence: Correlations and Copulas
6 Parametric Approaches (I)
6.1 Conditional vs unconditional distributions
6.2 Normal VaR and ES
6.3 The t-distribution
6.4 The lognormal distribution
6.5 Miscellaneous parametric approaches
6.6 The multivariate normal variance–covariance approach
6.7 Non-normal variance–covariance approaches
6.8 Handling multivariate return distributions with copulas
6.9 Conclusions
Appendix 1: Forecasting longer-term Risk Measures
7 Parametric Approaches (II): Extreme Value
7.1 Generalised extreme-value theory
7.2 The peaks-over-threshold approach: the generalised pareto distribution
7.3 Refinements to EV approaches
7.4 Conclusions
8 Monte Carlo Simulation Methods
9 Applications of Stochastic Risk Measurement Methods
10 Estimating Options Risk Measures
11 Incremental and Component Risks
12 Mapping Positions to Risk Factors
14 Estimating Liquidity Risks
15 Backtesting Market Risk Models
16 Model Risk
Bibliography
Author Index
Subject Index
