Analysis of Financial Time Series [Hardcover]

Ruey S. Tsay (Author)

Book Description

Publication Date: October 15, 2001 | ISBN-10: 0471415448 | ISBN-13: 978-0471415442 | Edition: 1

Fundamental topics and new methods in time series analysis

Analysis of Financial Time Series provides a comprehensive and systematic introduction to financial econometric models and their application 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. Timely topics and recent results include:

• Value at Risk (VaR)
• High-frequency financial data analysis
• Markov Chain Monte Carlo (MCMC) methods
• Derivative pricing using jump diffusion with closed-form formulas
• VaR calculation using extreme value theory based on a non-homogeneous two-dimensional Poisson process
• Multivariate volatility models with time-varying correlations

Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance, Analysis of Financial Time Series offers an in-depth and up-to-date account of these vital methods.

Editorial Reviews

Review

“…in my view, this is the number one reference for a course on financial econometrics...” (Statistical Papers, Vol.45, No.4, October 2004)

“…covers classical and new topics of financial econometrics…lots of examples, exercises and references at each chapter…” (Zentralblatt Math, Vol.1037, No.12, 2004)

"A textbook for graduate students of business or of mathematics with a business orientation." (Reference & Research Book News, May 2002)

"...an introductory book intended to provide a comprehensive and systematic account of financial econometric models and their application to modeling and prediciont..." (Quarterly of Applied Mathematics, Vol. LX, No. 2, June 2002)

"...an insightful and timely text…compelling reading...I would strongly consider using this text.." (Journal of Financial Research, Fall 2002)

"Always looking for a newer and better book, I will certainly enjoy having Analysis of Financial Time Series as my new primary resource." (Technometrics, Vol. 44, No. 4, November 2002)

From the Back Cover

Fundamental topics and new methods in time series analysis

Analysis of Financial Time Series provides a comprehensive and systematic introduction to financial econometric models and their application 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. Timely topics and recent results include:
* Value at Risk (VaR)
* High-frequency financial data analysis
* Markov Chain Monte Carlo (MCMC) methods
* Derivative pricing using jump diffusion with closed-form formulas
* VaR calculation using extreme value theory based on a non-homogeneous two-dimensional Poisson process
* Multivariate volatility models with time-varying correlations

Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance, Analysis of Financial Time Series offers an in-depth and up-to-date account of these vital methods.

See all Editorial Reviews

Product Details

• Hardcover: 472 pages
• Publisher: Wiley-Interscience; 1 edition (October 15, 2001)
• Language: English
• ISBN-10: 0471415448
• ISBN-13: 978-0471415442
• Product Dimensions: 9.5 x 6.4 x 1.1 inches
• Shipping Weight: 1.7 pounds
• Average Customer Review: 4.2 out of 5 stars  See all reviews (14 customer reviews)
• Amazon Best Sellers Rank: #238,282 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

41 of 42 people found the following review helpful:

3.0 out of 5 stars Broad coverage, but not for the faint-hearted, July 4, 2006

By 

Gadgester "No Time, No Money" (Mother Earth) - See all my reviews
(HALL OF FAME REVIEWER)   

This review is from: Analysis of Financial Time Series (Wiley Series in Probability and Statistics) (Hardcover)

Written by a University of Chicago professor, this book comprehensively covers times series topics relative to investment and trading-oriented finance (i.e., Wall Street money-making machines). Treatment is generally clear and thorough, but an advanced math and stat background is an absolute prerequisite for understanding the materials.

S-Plus/R code is given, but strangely, there is very little on *why* and
*when* one uses each of the techniques. Under what cirmcustances should I use or not use GARCH? What exactly is PCA good for in real-world applications? These important questions are not answered, in other words, you don't get a sense of the real-world context for these topics.

31 of 36 people found the following review helpful:

5.0 out of 5 stars good coverage, February 22, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Analysis of Financial Time Series (Wiley Series in Probability and Statistics) (Hardcover)

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 correct George Tiao is also there at present.

This is the second edition of a popular text. Financial time series play an ever more important role in our lives during these turbulant economic times. Tsay cover the tradition Box-Jenkins models but these models are not always appropriate for financial data. So he also introduces the GARCH models and some nonlinear models. The book includes some models that I am not familiar with. I have done research in time series but never with financial data. There is some theory involving stochastic differential equations that explains some of the turbulant behavior of financial series. The text by J. Michael Steele provides thorough coverage to this theory.

Tsay also deals with the pesky problem of outliers. A very practical problem that is often ignored in other econometric texts. He also has a chapter on Bayesian approaches. Some computing in SPlus is also included in this revision of the text.

27 of 31 people found the following review helpful:

4.0 out of 5 stars A very practical book, June 12, 2002

By 

"yin_luo" (Toronto, ON CANADA) - See all my reviews

This review is from: Analysis of Financial Time Series (Hardcover)

This is not a reference book, and it's not about "big" theory either. It's pretty practical, and good for self study. You should have access to some econometric/statistical software (i.e. EViews, S-Plus, etc.) to fully understand this book.