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Financial Econometrics: Problems, Models, and Methods., by Christian Gourieroux, Joann Jasiak
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Financial econometrics is a great success story in economics. Econometrics uses data and statistical inference methods, together with structural and descriptive modeling, to address rigorous economic problems. Its development within the world of finance is quite recent and has been paralleled by a fast expansion of financial markets and an increasing variety and complexity of financial products. This has fueled the demand for people with advanced econometrics skills.
For professionals and advanced graduate students pursuing greater expertise in econometric modeling, this is a superb guide to the field's frontier. With the goal of providing information that is absolutely up-to-date--essential in today's rapidly evolving financial environment--Gourieroux and Jasiak focus on methods related to foregoing research and those modeling techniques that seem relevant to future advances. They present a balanced synthesis of financial theory and statistical methodology. Recognizing that any model is necessarily a simplified image of reality and that econometric methods must be adapted and applied on a case-by-case basis, the authors employ a wide variety of data sampled at frequencies ranging from intraday to monthly. These data comprise time series representing both the European and North American markets for stocks, bonds, and foreign currencies. Practitioners are encouraged to keep a critical eye and are armed with graphical diagnostics to eradicate misspecification errors.
This authoritative, state-of-the-art reference text is ideal for upper-level graduate students, researchers, and professionals seeking to update their skills and gain greater facility in using econometric models. All will benefit from the emphasis on practical aspects of financial modeling and statistical inference. Doctoral candidates will appreciate the inclusion of detailed mathematical derivations of the deeper results as well as the more advanced problems concerning high-frequency data and risk control. By establishing a link between practical questions and the answers provided by financial and statistical theory, the book also addresses the needs of applied researchers employed by financial institutions.
- Sales Rank: #765684 in Books
- Brand: Brand: Princeton University Press
- Published on: 2001-11-01
- Original language: English
- Number of items: 1
- Dimensions: 9.52" h x 1.44" w x 6.45" l, 1.94 pounds
- Binding: Hardcover
- 464 pages
- Used Book in Good Condition
About the Author
Christian Gourieroux is Director of the Laboratory for Finance and Insurance at the Center for Research in Economics and Statistics (CREST) in Paris. He is the coauthor of Statistics and Econometric Models. Simulation Based Econometric Methods, and Time Series and Dynamic Models Joann Jasiak is Associate Professor in the Department of Economics, York University, Toronto.
Most helpful customer reviews
17 of 21 people found the following review helpful.
Sloppy
By Kindle Customer
This book is not completely useless. It does tell you something about models that are used in finance. But the title misleads: there is a lot of description of models, but not much on estimation and inference procedures.
There is a general air of editorial sloppiness in a combination of factual errors, grammatical slips, awkward language and inscrutable logic. For example, on p.36 a process is defined to be I(1) iff its first difference is a weak white noise. And on p.172 there is this: "It is likely the asset prices to [sic] follow a nonstationary process, whereas the dividends and the excess gains are stationary processes." Huh? In the discussion of the consumption-based CAPM money and a price level are inexplicably included. Things of this kind recur through out.
39 of 47 people found the following review helpful.
Victor, try Google
By A Customer
(Forget the stars; I'm just posting the Table of Contents)
Table of Contents
Preface vii
1. Introduction 1
2. Univariate Linear Models: The AR(1) process and Its Extensions 17
3. Multivariate Linear Models: VARMA Representation 53
4. Simultaneity, Recursivty, and Casuality Analysis 81
5. Persistence and Cointegration 105
6. Conditional Heteroscedasticity: Nonlinear Autoaggressive Models, ARCH Models, Stochastic Volatility Models 117
7. Expection and Present Value Models 151
8. Intertemporal Behavior and the Method of Moments 173
9. Dynamic Factor Models 195
10. Dynamic Qualitative Proceses 219
11. Diffusion Models 241
12. Estimation of Diffusion Models 285
13. Econometrics of Derivatives 317
14. Dynamic Models for High-Freguency data 351
15. Market Indexes 247
16. Management of Extreme Risks 427
References 451
Index 477
12 of 13 people found the following review helpful.
A great introduction to financial econometrics
By Krzysztof Wolyniec
The book introduces a number of topics that usually can be only found in papers. For example, the treatment of the econometrics of derivatives, although not very extensive, is excellent. In this regard the book is vastly superior to Cambell and Lo's book. Overall, the book covers a wealth of topics in very accesible and concise manner. Probably, the best introduction to modern financial econometrics for practitioners.
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