Written by main market danger tutorial, Professor Carol Alexander, Value-at-Risk Models varieties half 4 of theMarket Risk Analysis 4 quantity set. Building on the three earlier volumes this ebook offers by far probably the most complete, rigorous and detailed remedy of market VaR fashions. It rests on the essential information of monetary arithmetic and statistics gained from Volume I, of issue fashions, principal part evaluation, statistical fashions of volatility and correlation and copulas from Volume II and, from Volume III, information of pricing and hedging monetary devices and of mapping portfolios of comparable devices to danger elements. A unifying attribute of the collection is the pedagogical strategy to sensible examples which are related to market danger evaluation in observe.
All collectively, the Market Risk Analysis 4 quantity set illustrates nearly each idea or formulation with a sensible, numerical instance or an extended, empirical case examine. Across all 4 volumes there are roughly 300 numerical and empirical examples, 400 graphs and figures and 30 case research lots of that are contained in interactive Excel spreadsheets accessible from the the accompanying CD-ROM . Empirical examples and case research particular to this quantity embrace:
- Parametric linear worth in danger (VaR)fashions: regular, Student t and regular combination and their anticipated tail loss (ETL);
- New formulae for VaR primarily based on autocorrelated returns;
- Historical simulation VaR fashions: find out how to scale historic VaR and volatility adjusted historic VaR;
- Monte Carlo simulation VaR fashions primarily based on multivariate regular and Student t distributions, and primarily based on copulas;
- Examples and case research of quite a few purposes to rate of interest delicate, fairness, commodity and worldwide portfolios;
- Decomposition of systematic VaR of enormous portfolios into commonplace alone and marginal VaR parts;
- Backtesting and the evaluation of danger mannequin danger;
- Hypothetical issue push and historic stress checks, and stress testing primarily based on VaR and ETL.
- Table of Contents
- List of Figures.
- List of Tables.
- List of Examples.
- Preface to Volume IV.
- 1 Value at Risk and Other Risk Metrics.
- 1.1 Introduction.
- 1.2 An Overview of Market Risk Assessment.
- 1.3 Downside and Quantile Risk Metrics.
- 1.4 Defining Value at Risk.
- 1.5 Foundations of Value-at-Risk Measurement.
- 1.6 Risk Factor Value at Risk.
- 1.7 Decomposition of Value at Risk.
- 1.8 Risk Metrics Associated with Value at Risk.
- 1.9 Introduction to Value-at-Risk Models.
- 1.10 Summary and Conclusions.
- 2 Parametric Linear VaR Models.
- 2.1 Introduction.
- 2.2 Foundations of Normal Linear Value at Risk.
- 2.3 Normal Linear Value at Risk for Cash-Flow Maps.
- 2.4 Case Study: PC Value at Risk of a UK Fixed Income Portfolio.
- 2.5 Normal Linear Value at Risk for Stock Portfolios.
- 2.6 Systematic Value-at-Risk Decomposition for Stock Portfolios.
- 2.7 Case Study: Normal Linear Value at Risk for Commodity Futures.
- 2.8 Student tDistributed Linear Value at Risk.
- 2.9 Linear Value at Risk with Mixture Distributions.
- 2.10 Exponential Weighting with Parametric Linear Value at Risk.
- 2.11 Expected Tail Loss (Conditional VaR).
- 2.12 Case Study: Credit Spread Parametric Linear Value at Risk and ETL.
- 2.13 Summary and Conclusions.
- 3 Historical Simulation.
- 3.1 Introduction.
- 3.2 Properties of Historical Value at Risk.
- 3.3 Improving the Accuracy of Historical Value at Risk.
- 3.4 Precision of Historical Value at Risk at Extreme Quantiles.
- 3.5 Historical Value at Risk for Linear Portfolios.
- 3.6 Estimating Expected Tail Loss within the Historical Value-at-Risk Model.
- 3.7 Summary and Conclusions.
- 4 Monte Carlo VaR.
- 4.1 Introduction.
- 4.2 Basic Concepts.
- 4.3 Modelling Dynamic Properties in Risk Factor Returns.
- 4.4 Modelling Risk Factor Dependence.
- 4.5 Monte Carlo Value at Risk for Linear Portfolios.
- 4.6 Summary and Conclusions.
- 5 Value at Risk for Option Portfolios.
- 5.1 Introduction.
- 5.2 Risk Characteristics of Option Portfolios.
- 5.3 Analytic Value-at-Risk Approximations.
- 5.4 Historical Value at Risk for Option Portfolios.
- 5.5 Monte Carlo Value at Risk for Option Portfolios.
- 5.6 Summary and Conclusions.
- 6 Risk Model Risk.
- 6.1 Introduction.
- 6.2 Sources of Risk Model Risk.
- 6.3 Estimation Risk.
IV.6.4 Model Validation.
IV.6.5 Summary and Conclusions.
IV.7 Scenario Analysis and Stress Testing.
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 and Conclusions.
IV.8 Capital Allocation.
IV.8.2 Minimum Market Risk Capital Requirements for Banks.
IV.8.3 Economic Capital Allocation.
IV.8.4 Summary and Conclusions.
Carol Alexander is a Professor of Risk Management on the ICMA Centre, University of Reading, and Chair of the Academic Advisory Council of the Professional Risk Manager’s International Association (PRMIA). She is the creator of Market Models: A Guide to Financial Data Analysis(John Wiley & Sons Ltd, 2001) and has been editor and contributor of a really massive variety of books in finance and arithmetic, together with the multi-volume Professional Risk Manager’s Handbook(McGraw-Hill, 2008 and PRMIA Publications). Carol has revealed practically 100 tutorial journal articles, ebook chapters and books, nearly all of which concentrate on monetary danger administration and mathematical finance. Professor Alexander is likely one of the world’s main authorities on market danger evaluation.