The fourth volume in the Market Risk Analysis set, Market Risk Analysis: Value-at-Models Models, Volume IV builds on the information in the three previous volumes, which introduced readers to basic knowledge of financial mathematics and statistics particular to value-at-risk (VaR) models. This volume provides the most detailed treatment of VaR models through a pedagogical approach usingempirical examples and case studies relevant to market risk analysis in practice. Market risk analysts, fund managers, portfolio analysts, consultants and software companies, and graduate level students will all benefit from this volume. INDICE: List of Figures. List of Tables. List of Examples. Foreword. Preface to Volume IV. IV.1 Value at Risk and Other Risk Metrics. IV.1.1 Introduction. IV.1.2 An Overview of Market Risk Assessment. IV.1.3 Downside and Quantile Risk Metrics. IV.1.4 Defining Value at Risk. IV.1.5 Foundations of Value-at-Risk Measurement. IV.1.6 Risk Factor Value at Risk. IV.1.7 Decomposition of Value at Risk. IV.1.8 Risk Metrics Associated with Value at Risk. IV.1.9 Introduction to Value-at-Risk Models. IV.1.10 Summary and Conclusions. IV.2 Parametric Linear VaR Models. IV.2.1 Introduction. IV.2.2 Foundations of Normal Linear Value at Risk. IV.2.3 Normal Linear Value at Risk for Cash-Flow Maps. IV.2.4 Case Study: PC Value at Risk of a UK Fixed Income Portfolio. IV.2.5 Normal LinearValue at Risk for Stock Portfolios. IV.2.6 Systematic Value-at-Risk Decomposition for Stock Portfolios. IV.2.7 Case Study: Normal Linear Value at Risk for Commodity Futures. IV.2.8 Student t Distributed Linear Value at Risk. IV.2.9 Linear Value at Risk with Mixture Distributions. IV.2.10 Exponential Weighting with Parametric Linear Value at Risk. IV.2.11 Expected Tail Loss (Conditional VaR). IV.2.12 Case Study: Credit Spread Parametric Linear Value at Risk and ETL. IV.2.13 Summary and Conclusions. IV.3 Historical Simulation. IV.3.1 Introduction. IV.3.2 Properties of Historical Value at Risk. IV.3.3 Improving the Accuracy of Historical Value at Risk. IV.3.4 Precision of Historical Value at Risk at Extreme Quantiles. IV.3.5 Historical Value at Risk for Linear Portfolios.IV.3.6 Estimating Expected Tail Loss in the Historical Value-at-Risk Model. IV.3.7 Summary and Conclusions. IV.4 Monte Carlo VaR. IV.4.1 Introduction. IV.4.2 Basic Concepts. IV.4.3 Modelling Dynamic Properties in Risk Factor Returns.IV.4.4 Modelling Risk Factor Dependence. IV.4.5 Monte Carlo Value at Risk forLinear Portfolios. IV.4.6 Summary and Conclusions. IV.5 Value at Risk for Option Portfolios. IV.5.1 Introduction. IV.5.2 Risk Characteristics of Option Portfolios. IV.5.3 Analytic Value-at-Risk Approximations. IV.5.4 Historical Valueat Risk for Option Portfolios. IV.5.5 Monte Carlo Value at Risk for Option Portfolios. IV.5.6 Summary and Conclusions. IV.6 Risk Model Risk. IV.6.1 Introduction. IV.6.2 Sources of Risk Model Risk. IV.6.3 Estimation Risk. IV.6.4 ModelValidation. IV.6.5 Summary and Conclusions. IV.7 Scenario Analysis and StressTesting. IV.7.1 Introduction. IV.7.2 Scenarios on Financial Risk Factors. IV.7.3 Scenario Value at Risk and Expected Tail Loss. IV.7.4 Introduction to Stress Testing. IV.7.5 A Coherent Framework for Stress Testing. IV.7.6 Summary andConclusions. IV.8 Capital Allocation. IV.8.1 Introduction. IV.8.2 Minimum Market Risk Capital Requirements for Banks. IV.8.3 Economic Capital Allocation. IV.8.4 Summary and Conclusions. References. Index.
- ISBN: 978-0-470-99788-8
- Editorial: John Wiley & Sons
- Encuadernacion: Cartoné
- Páginas: 492
- Fecha Publicación: 09/01/2009
- Nº Volúmenes: 1
- Idioma: Inglés