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Simulation Techniques in Financial Risk Management, by Ngai Hang Chan and Hoi Ying Wong, 2006, John Wiley & Sons, Hoboken, NJ, pp. 240. ISBN: 978-0-471-46987-2
Reviewer: Puneet Prakash, Virginia Commonwealth University
The Wiley InterScience "Statistics in Practice" series aims to provide both practitioners and research workers with statistical techniques for their respective disciplines, and this book is no exception. Although the authors' intended audience is practitioners in financial risk management, the book is also a useful tool for graduate students in the field because it provides concise simulation methodologies for many financial risk models.
Simulation is a necessity in financial risk management, allowing practitioners to solve many problems that lack closed-form solutions. The book is perfectly positioned between Ross (2002) and Glasserman (2004) and is a valuable intermediate-level text. It contains a semester's worth of topics in financial risk management, provided the course is taught only through simulations. The book does an excellent job of explaining why simulations are important in general as controlled experiments, as well as why, specifically, they are valued in the financial risk discipline.
Although the authors require basic exposure to probability and statistics at the undergraduate level, prior knowledge of mathematics/statistics at the graduate level would also be helpful. For example, a reader with only the recommended exposure to mathematics/statistics at the Hogg and Tanis (2006) level would have difficulty grasping the difference between Stratonovich and Ito integrals (Chapter 2, exercise 5).
The authors of the text are statisticians, and the book bears their mark. Examples 1.3.1 and 1.3.2 would have fit a math/statistics text (see Hubbard and Hubbard, 1999) very well. Notation and results are usually introduced first, while intuition associated with symbols and their definitions follow later. Because this is a text presumably aimed at first-time readers, a reverse approach might be more suitable.
In the preface, the authors correctly state that the book requires a rudimentary knowledge of finance. However, when the authors say that they aim to strike a balance between theory and applications of risk management, what they really mean by theory is statistical theory. Readers expecting a more rigorous treatment of financial theory will be disappointed. Even though the field of risk management is an amalgamation of disciplines, and the authors...