Quantitative Risk Management: Concepts, Techniques and Tools - Revised Edition

by Alexander J. McNeil, Rüdiger Frey, Paul Embrechts

This book provides the most comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management. Whether you are a financial risk analyst, actuary, regulator or student of quantitative finance, Quantitative Risk Management gives you the practical tools you need to solve real-world problems.

Describing the latest advances in the field, Quantitative Risk Management covers the methods for market, credit and operational risk modelling. It places standard industry approaches on a more formal footing and explores key concepts such as loss distributions, risk measures and risk aggregation and allocation principles. The book’s methodology draws on diverse quantitative disciplines, from mathematical finance and statistics to econometrics and actuarial mathematics. A primary theme throughout is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. Proven in the classroom, the book also covers advanced topics like credit derivatives.

Fully revised and expanded to reflect developments in the field since the financial crisis Features shorter chapters to facilitate teaching and learning Provides enhanced coverage of Solvency II and insurance risk management and extended treatment of credit risk, including counterparty credit risk and CDO pricing Includes a new chapter on market risk and new material on risk measures and risk aggregation

Genres: Finance, Textbooks, Management

720 pages, Kindle Edition

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".