The Econometrics of Financial Markets
Author: John Y. Campbell, Andrew W. Lo, A. Craig MacKinlay, Andrew Y. Lo, Archie Craig MacKinlay
List Price: $85.00
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ISBN: 0691043019
Publisher: Princeton Univ Pr (09 December, 1996)
Sales Rank: 35,662
Average Customer Rating: 4.27 out of 5
Customer Reviews
Rating: 4 out of 5
Applied Financial econometrics exponent
It is a good book, but there are some aspects which I find lacking in the book which could be helpful. For example, brief outline answers to some of the problems at the end of the chapter will help most readers no doubt. Also, a more comprehensive cover on the rational bubbles and GARCH type models for asset returns will help no doubt, as well as problems that may arise during implementation. This book is aimed at the advance graduate student who is pretty proficient in theoretical finance and advance econometric issues already.
Rating: 4 out of 5
A classic book on financial econometrics
This is really a classic book on financial econometrics. I like the design of the book. The content is also pretty up-to-date. A little bit advanced - requires solid background in econometrics, analysis, statistics, and some stochastic calculus. The only problem I have is the authors did not provide background data, so it's really hard for people to do self-study like me. If the authors could include a preferred computer program (i.e. Matlab, GAUSS, EViews, etc.) with codes and data, that will make the book a true bible of financial econometrics.
Rating: 1 out of 5
Spend your money on something better
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.
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