Quantitative Risk Management: Concepts, Techniques, and Tools

Description

''This book is a compendium of the statistical arrows that should be in any quantitative risk manager's quiver. It includes extensive discussion of dynamic volatility models, extreme value theory, copulas, and credit risk. Academics, Ph.D. students, and quantitative practitioners will find many new and useful results in this important volume.'' — Robert F. Engle III, 2003 Nobel Laureate in Economic Sciences, Michael Armellino Professor in the Management of Financial Services at New York University's Stern School of Business''This book provides a framework and a useful toolkit for analysis a wide variety of risk management problems. Common pitfalls are pointed out, and mathematical sophistication is used in pursuit of useful and usable solutions. Every financial institution has a risk management department that looks at aggregated portfolio-wide risks on longer time scales, and at risk exposure to large, or extreme, market movements. Risk managers are always on the lookout for good techniques to help them do their jobs. This very good book provides these techniques and addresses an important, and under-developed, area of practical research.'' — Martin Baxter, Nomura International''McNeil, Frey, and Embrechts present a wide-ranging yet remarkably clear and coherent introduction to the modelling of financial risk. Unlike most finance texts, where the focus is on pricing individual instruments, the primary focus in this book is the statistical behavior of portfolios of risky instruments, which is, after all, the primary concern of risk management. This ought to be a core text in every risk manager's training, and a useful reference for experienced professionals.'' — Michael Gordy''There is no bookthat provides the type of rigorous and detailed coverage of risk management topics that this book does. This could become the book on quantitative risk management.'' — Riccardo Rebonato, Royal Bank of Scotland, author of Modern Pricing of Interest-Rate Derivatives