Quantitative Risk Management: Concepts, Techniques, and Tools

by Alexander J. McNeil, Rüdiger Frey, Paul Embrechts

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.

Genres: Finance, Textbooks, Management

538 pages, Hardcover

First published September 26, 2005

Reviews

[Pelle · Rating 5 out of 5]

I enjoyed a lot to read this book. It covers such a vast amount of material that I only read the introductory chapters as well as those regarding multivariate distributions and copulas. There is much more to read about credit risk and applications to market risk which I did not have time to spend on. The theory is presented together with nice examples and common fallacies especially in context with linear correlations are covered.

I would say, this is a must-read for anyone in the banking/insurance Business who is dealing with internal models under Solvency II/Basel III.

[p-adic vacation · Rating 5 out of 5]

I mainly read Chapter 5-7. If there is a book better than this one in quantitative risk management, it should be the 2nd edition of it (although I have only read one book in this area).

[Đạt Phạm Quốc · Rating 5 out of 5]

Very comprehensive - required a prepared knowledge in probability and statistics math. In my case I approached it the seminar during my graduate study, so I struggled with it a lot. But I really recommend it for anyone who is interested in quantitative finance, specifically risk management. The authors also provide some math foundation in some beginning chapters for us to get used to it, then introduce the technical stuff later.

[Marek · Rating 5 out of 5]

It has been the best technical book about risk management concepts, techniques and tools I've read so far. The main reason is that it focuses also on multivariate modeling which are in real world used. No bank, hedge fund, prop shop is trading 1 asset and would use only e.g. univariate VaR/ES model. I appreciate a lot also there are available codes in R which helps to understand the models much faster than reading any book 1000x times. Another added value of this book is that it goes gradually deep in the underlying math and authors wrote it in the different way than many others books. I've read many books about quant. risk management and a lot of them are almost copy-paste. They have very marginal added value. This is real must book for anyone who has genuine interest if quant. risk management. Another complementary outstanding book is "Financial modeling under non-gaussian
distributions".