Value-at-risk (VaR) is a measure of market risk that has been widely adopted since the mid-1990s for use on trading floors. This is the first advanced book published on VaR. It describes how to design, implement, and use scalable production VaR measures on actual trading floors. It takes readers from the basics of VaR to the most advanced techniques, many of which have never been published in book form.
Practical, detailed examples are drawn from markets around the world, including: Euro deposits, Pacific Basin equities, physical coffees, and North American natural gas.
Real-world challenges relating to market data, portfolio mappings, multicollinearity, and intra-horizon events are addressed in detail. Exercises reinforce concepts and walk readers step-by-step through computations.
Sophisticated techniques are fully disclosed, including: quadratic ("delta-gamma") methods for nonlinear portfolios, variance reduction (control variates and stratified sampling) for Monte Carlo VaR measures, principal component remappings, techniques to "fix" estimated covariance matrices that are not positive-definite, the Cornish-Fisher expansion, and orthogonal GARCH.
Review quote:
"Laudably balancing clarity of exposition, a unified theoretical approach, and analytical rigor, Holton has produced what is bound to become the standard advanced text and reference work on value-at-risk. Seasoned practitioners will find the treatise every bit as useful as new students to the subject."
- -Christopher L. Culp, Adjunct Associate Professor of Finance, Graduate School of Business, The University of Chicago
"Glyn Holton's book is a great reference for practitioners and theorists, and an excellent textbook for students of VaR--mathematically rigorous and concise, yet lucid and accessible."
- -Michael K. Ong, EVP and Chief Risk Officer, Credit Agricole Indosuez, New York, New York
Table of contents:
Value-at-Risk; Mathematical Preliminaries; Probability; Statistics and Time Series Analysis; Monte Carlo Method; Market Data; Inference; Primary Mappings; Remappings; Transformations.
Practical, detailed examples are drawn from markets around the world, including: Euro deposits, Pacific Basin equities, physical coffees, and North American natural gas.
Real-world challenges relating to market data, portfolio mappings, multicollinearity, and intra-horizon events are addressed in detail. Exercises reinforce concepts and walk readers step-by-step through computations.
Sophisticated techniques are fully disclosed, including: quadratic ("delta-gamma") methods for nonlinear portfolios, variance reduction (control variates and stratified sampling) for Monte Carlo VaR measures, principal component remappings, techniques to "fix" estimated covariance matrices that are not positive-definite, the Cornish-Fisher expansion, and orthogonal GARCH.
Review quote:
"Laudably balancing clarity of exposition, a unified theoretical approach, and analytical rigor, Holton has produced what is bound to become the standard advanced text and reference work on value-at-risk. Seasoned practitioners will find the treatise every bit as useful as new students to the subject."
- -Christopher L. Culp, Adjunct Associate Professor of Finance, Graduate School of Business, The University of Chicago
"Glyn Holton's book is a great reference for practitioners and theorists, and an excellent textbook for students of VaR--mathematically rigorous and concise, yet lucid and accessible."
- -Michael K. Ong, EVP and Chief Risk Officer, Credit Agricole Indosuez, New York, New York
Table of contents:
Value-at-Risk; Mathematical Preliminaries; Probability; Statistics and Time Series Analysis; Monte Carlo Method; Market Data; Inference; Primary Mappings; Remappings; Transformations.