The Econometrics of Financial Markets (Hardcover)

~ (Author), (Author), A. Craig MacKinlay (Author), Andrew Y. Lo (Author)

Editorial Reviews

Review

Written by the "A" team of financial empiricism, it is a long awaited book. It covers many topics one could only usually find couched in the technical jargon of research papers, presented in this volume with pedagogical intentions. The language, while remaining technical, is quite accessible. It can be effortlessly read by scientific traders with standard knowledge of statistical methods. . . . This book should be made mandatory reading in research departments. -- Review

Review

The definitive work explaining this complex but important field of academic endeavor. Oh, and by the way, it's not just academic. The big question that financial econometircs addresses is: What can you learn about the future from the financial data available from the past? This broad issue can be specified in many different ways, and all the important ones are discussed in the book. . . . The vast literature on all the topics examined is assessed, rendered coherent, and then analysed by three men who themselves have made significant advances in the field.
(Ruben Lee London Financial Market )

This book is sophisticated, yet accessible; full of details, yet intriguing. . . . Instructors will appreciate the attempt to make each chapter as self contained as possible which leaves them free to choose specified sequences of topics. Professionals will be pleased with the quick and authoritative introductions to important areas of Finance. . . . [A] well written introduction (indeed, something more) to Financial Econometrics. It is alert, explicit and articulate about assumptions. . . a splendid offering. . . .
(Maurizio Tiso Review of Financial Studies )

Written by the "A" team of financial empiricism, it is a long awaited book. It covers many topics one could only usually find couched in the technical jargon of research papers, presented in this volume with pedagogical intentions. The language, while remaining technical, is quite accessible. It can be effortlessly read by scientific traders with standard knowledge of statistical methods. . . . This book should be made mandatory reading in research departments.
(Derivative Strategies )

See all Editorial Reviews

Product Details

• Hardcover: 632 pages
• Publisher: Princeton University Press (December 9, 1996)
• Language: English
• ISBN-10: 0691043019
• ISBN-13: 978-0691043012
• Product Dimensions: 9.4 x 6.3 x 1.8 inches
• Shipping Weight: 2.2 pounds (View shipping rates and policies)
• Average Customer Review: 3.6 out of 5 stars  See all reviews (16 customer reviews)
• Amazon.com Sales Rank: #31,664 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

12 of 12 people found the following review helpful:

4.0 out of 5 stars An excellent text for the advanced reader, December 21, 2001

By	Quant Jockey "DC" (Rockville, MD USA) - See all my reviews

This is a concise treatment of major foundation topics in financial economics. Although my interest is in monetary economics and macro, I finally have a book I will keep and use on financial economics. It closely blends the insight and "wisdom" behind the various theories with parsimonious amounts of math. Careful, patient reading and a comfortable grasp of econometrics is required but will be rewarded. Notation changes were a bit of a problem, though the authors address this issue early on. The end of chapter questions are good but it would've helped to have answers. Overall, it is intuitive "page turner" material.

40 of 48 people found the following review helpful:

1.0 out of 5 stars Spend your money on something better, May 3, 2003

By A Customer

This book seems to have written to cash in on the fame of the authors and the stampede in academia and industry towards financial econometrics.

The book already assumes you are proficent in basic and advanced econometrics, derivatives pricing, fixed income, microstructure, neural networks etc. If you already familiar with those fields, why do you need this book? For example, Chapter 10 on Fixed Income Securities covers a grand total of 28 pages beginning with "Basic Concepts" and ending with "Yield Spreads and Interest Rate forecasts". Meanwhile there are whole tomes devoted to every one of those sections in Chapter 10. Nonparameteric Estimation merits a grand total of 9 pages and Neural networks merits 7 pages in Chapter 12.

The chapter on Microstructure, virtue of the book being published in 1997 is thoroughly dated. Even for its 1997 publication the chapter is thoroughly lacking. It is neither a survey nor a exposition of theory or practial uses of microstructure theory. Today there are excellent theoretical and practical books devoted to every topic covered in this book.

Save your money for one of those.

10 of 10 people found the following review helpful:

1.0 out of 5 stars CML: An Unnecessary Addition to a Saturated Literature, January 29, 2007

By	Mark Twain "Al" (Chicago, IL) - See all my reviews

I was also skeptical of the negative reviews surrounding this book ("CML"). However after buying and reading this book, I now believe they had merit.

Simply stated, this book does not cater to its readers. If you have the prerequisites that the authors demand, then this book is comprehensive but ultimately below what ought to challenge you. And if you don't, then I guarantee you will be very lost. Unlike many similar volumes, CML is not self-contained (nor does it claim to be). And unlike many books that build a self-contained "model" of asset pricing dynamics, CML is full of literature-specific jargon and inconsistent notation. In fact much of this notation changes intrachapter.

Suppose you are a reader at the level CML insist their readers be. Then all the better to spend more time understanding Duffie's "Dynamic Asset Pricing," or Cochrane's veritable tour-de-force, "Asset Pricing." Both books are more contemporary and also at a better level for the readers CLM had in mind.

If you don't have the requisite knowledge, please ignore CML and try Luenenberger and Casella/Berger, as well as Greene for econometric-specific stats, Hamilton for time-series. You will not regret these purchases.

CML claims to fill a gaping hole in the secondary literature. But in reality, CML sits right in the middle of two types of readers, and caters effectively to none.