Statistical Models and Methods for Financial Markets (Springer Texts in Statistics)

Tse Leung Lai's research area is sequential analysis, to which he has made fundamental contributions. However, he has long been interested in finance, and at Stanford he has advised several Ph.D. students on related subjects, among whom Xing, who is now at SUNY Stony Brook. This book is a rather disparate collection of topics in Statistics that are relevant to finance. It can be used as a reference book. Given Lai's caliber, it is always interesting to read his thoughts, even on well-known topics like OLS or GARCH. However, I do have two major criticisms. The first is that there is no common thread to the book. The subjects are generic and broad and their coverage is usually very standard and superficial. As such, they can be learnt better from monographies. Bootstrapping? Get Efron and Tibshirani's book, or even Hastie-Friedman-Tibshirani's Elements of Statistical Learning. Tests of Multiple Hypothesis? Read White's original paper, and Benjamini-Hochberg. The second criticism is that the author seem to have little real-world experience, and this shows in the treatment. There is a disproportionate coverage of GARCH, a disconnected (from applications) coverage of non-parametric regression, and very little on factor models. There is really nothing to show that the authors have spent any time implementing those methods, and weighting their relative importance based on their applicability.Overall, I was very disappointed. Lai is a very gentle person, maybe not a great lecturer, but is a very clear writer, and his survey papers are excellent. I expected much better from him. On the same subject, I would recommend Campbell-Lo-McKinlay's  The Econometrics of Financial Markets  and Tsay's  Analysis of Financial Time Series (Wiley Series in Probability and Statistics)  as the long-standing references.

This book presents a summary of major statistic methods for financial engineering. It is a good book for those who want to learn these stuff quickly, without too much detail, but get the core idea of each method.

Used as textbook for STATS240... Disorganized, no motivation provided for the methods. Just lists of conditions and results. To learn the methods a google search is preferable.

good conditions

Book is okay in theory, code has not been provided in the book itself and the link provided to the code doesn't work. The page has been removed from the website.

Nice book to start with implementation.