Product Description

Gain the statistical tools and techniques you need to understand today's financial markets with the Second Edition of this critically acclaimed book.

Youll find a comprehensive and systematic introduction to financial econometric models and their applications in modeling and predicting financial time series data. This edition continues to emphasize empirical financial data and focuses on real-world examples. Youll master key aspects of financial time series, including volatility modeling, neural network applications, market microstructure and high-frequency financial data, continuous-time models and Ito's Lemma, Value at Risk, multiple returns analysis, financial factor models, and econometric modeling via computation-intensive methods.

This is an ideal textbook for MBA students and a key reference for researchers and professionals in business and finance. Order your copy today.

Product Details

• Amazon Sales Rank: #32880 in Books
• Published on: 2005-08-30
• Number of items: 1
• Binding: Hardcover
• 640 pages

Download Description
Analysis of Financial Time Series, Second Edition provides a comprehensive and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods.

Review
"…too wonderful [a] book to be missed by any one who works in time series analysis." (Journal of Statistical Computation and Simulation, October 2006)

"...an excellent account of financial time series...[for] students and especially to practitioners, who really need a book with enough...theoretical concepts...but also with plenty of intuitive insight of how exactly these models work…" (MAA Reviews, January 2, 2006)

Download Description
Analysis of Financial Time Series, Second Edition provides a comprehensive and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods.

Customer Reviews

good coverage
Professor Tsay is a student of the Wisconsin school of statisticians where he learned time series from Box and Tiao. He is an excellent lecturer and a good writer. i have attended one of the short courses he taught on time series. New models have been developed to deal with the special behavior of financial time series. Professor Tsay is always at the forefront of that research and teaches at Chicago in one of this country's top business schools. If I am current on this George Tiao is also there at present.

Excellent and detailed reference
The coverage of the topic is broad and deep. It is one of the few introductory books that devotes some space to transfer function modeling and does so intelligibly.
A must have for the novice as well as those more familiar with the topic that need a solid reference.

The best for Masters level, great all-around
This text is absolutely perfect for Masters students learning financial econometrics. There is a little theory, clear explanations, and quite a few real world examples. (I don't think any text would tell the reader what model to use when, because that's application-specific.) It assumes some knowledge of finance and basic econometrics/statistics, which is fair enough. To get more theory, Hamilton (1994) remains the authority, and Campbell, Lo, MacKinlay (1997) is a great introduction for PhD students, and generally an ideal companion volume to this one.