Measuring market risk
著者
書誌事項
Measuring market risk
Wiley, c2005
2nd ed
大学図書館所蔵 全7件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Originally published 2002
Bibliography: p. [365]-377
Includes index
内容説明・目次
内容説明
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.
目次
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
8.1 Uses of monte carlo simulation
8.2 Monte carlo simulation with a single risk factor
8.3 Monte carlo simulation with multiple risk factors
8.4 Variance-reduction methods
8.5 Advantages and disadvantages of monte carlo simulation
8.6 Conclusions
9 Applications of Stochastic Risk Measurement Methods
9.1 Selecting stochastic processes
9.2 Dealing with multivariate stochastic processes
9.3 Dynamic risks
9.4 Fixed-income risks
9.5 Credit-related risks
9.6 Insurance risks
9.7 Measuring pensions risks
9.8 Conclusions
10 Estimating Options Risk Measures
10.1 Analytical and algorithmic solutions m for options VaR
10.2 Simulation approaches
10.3 Delta-gamma and related approaches
10.4 Conclusions
11 Incremental and Component Risks
11.1 Incremental VaR
11.2 Component VaR
11.3 Decomposition of coherent risk measures
12 Mapping Positions to Risk Factors
12.1 Selecting core instruments
12.2 Mapping positions and VaR estimation
13 Stress Testing
13.1 Benefits and difficulties of stress testing
13.2 Scenario analysis
13.3 Mechanical stress testing
13.4 Conclusions
14 Estimating Liquidity Risks
14.1 Liquidity and liquidity risks
14.2 Estimating liquidity-adjusted VaR
14.3 Estimating liquidity at risk (LaR)
14.4 Estimating liquidity in crises
15 Backtesting Market Risk Models
15.1 Preliminary data issues
15.2 Backtests based on frequency tests
15.3 Backtests based on tests of distribution equality
15.4 Comparing alternative models
15.5 Backtesting with alternative positions and data
15.6 Assessing the precision of backtest results
15.7 Summary and conclusions
Appendix 1: Testing Whether Two Distributions are Different
16 Model Risk
16.1 Models and model risk
16.2 Sources of model risk
16.3 Quantifying model risk
16.4 Managing model risk
16.5 Conclusions
Bibliography
Author Index
Subject Index
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