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библиотека / Holton Glyn. Value-at-Risk Theory and Practice. |
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Author: Glyn A. Holton
Year: 2003
Publisher: Academic Press
Format: Hardcover
Pages: 408
Exercises: Yes
"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
Six years in writing, Value-at-Risk: Theory and Practice is the definitive book on value-at-risk (VaR). It takes readers from the basics of value-at-risk to the most advanced techniques, many of which have never been published in book form. Its focus is on how to make value-at-risk work in practice—how to design, implement and use scalable production value-at-risk measures on real trading floors.
Practical, detailed examples are drawn from markets around the world, such as: Euro deposits, Pacific Basin equities, physical coffees, and North American natural gas. 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.
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.
The book offers a lot of "firsts." It is the first non-elementary book on value-at-risk. It is the first to provide exercises. It is the first to fully disclose methodologies such as quadratic value-at-risk and variance reduction for value-at-risk. It is the first to approach value-at-risk from the bottom up. It is the first to document the history of value-at-risk dating back to capital requirements implemented by the New York Stock Exchange during the 1920s and the first published value-at-risk measure, which appeared in 1945.
There are plenty of books that offer an introductory treatment of value-at-risk. This one targets experienced practitioners, researchers and MBA students.
OVERVIEW
0. Preface
What We're About
Contents Overview
Audience
How to Read the Book
Notation and Terminology
1. Value-at-Risk
History
Measures
Risk Measures
Market Risk
Value-at-Risk
Risk Limits
Examples
VaR Measures
ESSENTIAL MATHEMATICS
2. Mathematical Preliminaries
Notation and Terminology
Gradient and Gradient-Hessian Approximations
Ordinary Interpolation
Complex Numbers
Eigenvalues and Eigenvectors
Cholesky Factorization
Minimizing a Quadratic Polynomial
Ordinary Least Squares
Cubic Spline Interpolation
Finite Difference Approximations of Derivatives
Newton's Method
Change of Variables Formula
Numerical Integration in One Dimension
Numerical Integration in Multiple Dimensions
3. Probability
Prerequisites
Parameters
Parameters of Random Vectors
Linear Polynomials of Random Vectors
Properties of Covariance Matrices
Principal Component Analysis
Uniform and Related Distributions
Normal and Related Distributions
Mixtures of Distributions
Moment-Generating Functions
Quadratic Polynomials of Joint-Normal Random Vectors
The Cornish-Fisher Expansion
Central Limit Theorem
The Inversion Theorem
Quantiles of Quadratic Polynomials of Joint-Normal Random Vectors
4. Statistics and Time Series Analysis
From Probability to Statistics
Estimation
Maximum Likelihood Estimators
Stochastic Processes
White Noise, Autoregressive and Moving Average Processes
GARCH Processes
Regime-Switching Processes
5. Monte Carlo Method
The Monte Carlo Method
Realizations of Samples
Pseudorandom Numbers
Testing Pseudorandom Number Generators
Implementing Pseudorandom Number Generators
Breaking the Curse of Dimensionality
Pseudorandom Variates
Variance Reduction
VALUE-AT-RISK
6. Market Data
Forms of Data
Nonsynchronous Data
Data Errors
Data Biases
Futures
Implied Volatilities
7. Inference
Selecting Key Factors
Current Practice
Unconditional Leptokurtosis and Conditional Heteroskedasticity
Historical Realizations
8. Primary Mappings
Day Counts
Primary Mappings
Example: Equities
Example: Forwards
Example: Options
Example: Physical Commodities
9. Remappings
Holdings Remappings
Global Remappings
Change-of-Variables Remappings
Principal-Component Remappings
10. Transformations
Linear Transformation Procedures
Quadratic Transformation Procedures
Monte Carlo Transformation Procedures
Variance Reduction
Glyn A. Holton is a renown authority on value-at-risk. He has written extensively on VaR. Through his consulting practice, he has helped hundreds of professionals implement and use VaR measures. Since 1997, he has conducted an acclaimed training seminar on VaR for practitioners, and he has spoken frequently at industry conferences. His forthcoming book will be the authoritative work on VaR for many years to come. |
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