- Hardcover: 632 pages
- Publisher: Princeton University Press; 2nd ed. edition (December 9, 1996)
- Language: English
- ISBN-10: 0691043019
- ISBN-13: 978-0691043012
- Product Dimensions: 6.4 x 1.6 x 9.1 inches
- Shipping Weight: 2.2 pounds (View shipping rates and policies)
- Average Customer Review: 22 customer reviews
- Amazon Best Sellers Rank: #333,899 in Books (See Top 100 in Books)
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The Econometrics of Financial Markets 2nd ed. Edition
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"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
From the Publisher
The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduatelevel textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory.
Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing stateofthe art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.
Top customer reviews
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Nevertheless, it is still a formidable book. Best for specialists in the field.
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.
The book outline the econometrics of major finance issues, but doesnt give detailed descriptions of main results. As an example, the Maximum likelihood formulas for multifactor asset pricing models are simply shown, but they dont explain how they got there (the likelihood function), so additional effort is needed if one wants to modify something - [A Critic : If you need to work on the econometrics of something yourself you dont need to buy the book, just learn finance and econometrics and put it together yourself !!]
The book maybe useful as a reference on many subjects, but to actually implement the models (as a practictioner or analyst) you will most likely need additional knowledge/books on a given subject. They also dont show any kind of algorithms/computing techniques or codes to do implement it, so you must be skilled enough at computing to crack it.
As an improving suggestion, the authors should reduce the number of chapters/subjects, completing it with more detailed formulas and computer codes/guides to actual implementation.