Book review: quantitative risk management: concepts, techniques and tools, revised edition, by A.F. McNeil, R. Frey and P. Embrechts. Princeton University Press, 2015, ISBN 978-0-691-16627-8, xix + 700 pp.

authors use Monte Carlo simulation extensively. Monte Carlo simulations are used to help students understand the important concept of sampling distributions as well as other concepts, such as violations and potential biases to linear models. By using the authors’ Excel workbooks, students are able to perform Monte Carlo simulations almost effortlessly. Humberto and Barreto have written a worthwhile and unique textbook on introductory econometrics. I was initially skeptical that Excel and Monte Carlo simulation could be integrated coherently, but the authors execute it well. This book has many positives, including accessibility, potential to engage some students who otherwise might not be interested, and likelihood of students finishing with a strong understanding of sampling distributions and linear regression. On the other hand, a few negative aspects exist. Whereas a narrow focus is advantageous in some ways, it precludes comprehensive development of some topics. For instance, no mention is made of analysis of variance methods. Consequently, any instructor considering this text should check the table of contents to ensure that all relevant topics are covered (or be prepared to provide other sources where necessary). In addition, because the text uses Excel exclusively, students entering the job market or applying for graduate school cannot claim knowledge of a statistical package—a potentially marketable skill. Regardless of these criticisms, the positives outweigh the negatives, and instructors should consider this progressive textbook for their undergraduate econometrics course.