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The implementation of sound quantitative risk models is a vital concern for all financial institutions, and this trend has accelerated in recent years with regulatory processes such as Basel II. This book provides a comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management and equips readers--whether financial risk analysts, actuaries, regulators, or students of quantitative finance--with practical tools to solve real-world problems. The authors cover methods for market, credit, and operational risk modelling; place standard industry approaches on a more formal footing; and describe recent developments that go beyond, and address main deficiencies of, current practice.
The book's methodology draws on diverse quantitative disciplines, from mathematical finance through statistics and econometrics to actuarial mathematics. Main concepts discussed include loss distributions, risk measures, and risk aggregation and allocation principles. A main theme is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. The techniques required derive from multivariate statistical analysis, financial time series modelling, copulas, and extreme value theory. A more technical chapter addresses credit derivatives. Based on courses taught to masters students and professionals, this book is a unique and fundamental reference that is set to become a standard in the field.
- Sales Rank: #1313841 in Books
- Published on: 2005-10-16
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 1.34" h x 6.50" w x 9.48" l,
- Binding: Hardcover
- 538 pages
Review
One of the Top 10 Technical Books on Financial Engineering by Financial Engineering News for 2006
"Quantitative Risk Managment can be highly recommended to anyone looking for an excellent survey of the most important techniques and tools used in this rapidly growing field."--Holger Drees, Risk
"This book provides a state-of-the-art discussion of the three main categories of risk in financial markets, market risk, . . . credit risk . . . and operational risk. . . . This is a high level, but well-written treatment, rigorous (sometimes succinct), complete with theorems and proofs."--D.L. McLeish, Short Book Reviews of the International Statistical Institute
"Quantitative Risk Management is highly recommended for financial regulators. The statistical and mathematical tools facilitate a better understanding of the strengths and weaknesses of a useful range of advanced risk-management concepts and models, while the focus on aggregate risk enhances the publication's value to banking and insurance supervisors."--Hans Blommestein, The Financial Regulator
"A great summary of the latest techniques available within quantitative risk measurement. . . . [I]t is an excellent text to have on the shelf as a reference when your day job covers the whole spectrum of quantitative techniques in risk management."--Financial Engineering News
"Alexander McNeil, Rudiger Frey and Paul Embrechts have written a beautiful book. . . . [T]here is no book that can provide the type of rigorous, detailed, well balanced and relevant coverage of quantitative risk management topics that Quantitative Risk Management: Concepts, Techniques, and Tools offers. . . . I believe that this work may become the book on quantitative risk management. . . . [N]o book that I know of can provide better guidance."--Dr. Riccardo Rebonato, Global Association of Risk Professionals (GARP) Review
"This is a very impressive book on a rapidly growing field. It certainly helps to discover the forest in an area where a lot of trees are popping up daily."--Hans Bühlmann, SIAM Review
From the Back Cover
"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 book that 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
About the Author
Alexander J. McNeil is Professor of Mathematics at the Swiss Federal Institute of Technology (ETH) in Zurich. Rudiger Frey is Professor of Financial Mathematics at the University of Leipzig. Paul Embrechts, Professor of Insurance Mathematics at the Swiss Federal Institute of Technology (ETH) in Zurich, is the coauthor of "Modelling Extremal Events for Insurance and Finance".
Most helpful customer reviews
24 of 24 people found the following review helpful.
Software implementation available for S-Plus and R
By B. Peterson
Although not obvious, there is software available to implement the functionality described mathematically in the book. Alexander McNeil provides S-Plus code on his personal website, and there is an R port of that code on CRAN called QRMlib. Most of the provided software is on fitting fat-tailed distributions. This is all very useful in practice, if you care to be statistically precise. Unfortunately, many practitioners would clearly prefer rules of thumb to quantitative methods only usable with statistical software that doesn't run in Excel. Excellent theoretical text with solid backing software.
1 of 1 people found the following review helpful.
Study material for next 2 years
By Amazon Customer
Excellent academic material
11 of 11 people found the following review helpful.
Power tools
By Fangbing Wu
I'd add the word power in front of tools in the book title! Yes the book doesn't give you any step-by-step how to of doing any of the things like some have complained. Then again, it's not meant to be a how-to book. This is a "why" book and the authors explain the whys brilliantly. Even the chapters covering statistical background materials, the authors chose the exact level of details for coverage without wasting any pages. To appreciate the book, the reader does need a strong math background. Then every page of the book is worth it.
See all 14 customer reviews...
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