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) 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.
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.
Book Info
Provides a comprehensive and systematic introduction to financial econometric models and their application to modeling and prediction of financial time series data. --This text refers to an out of print or unavailable edition of this title.
From the Back Cover
Provides statistical tools and techniques needed to understand today's financial markets
The Second Edition of this critically acclaimed text provides a comprehensive and systematic introduction to financial econometric models and their applications in modeling and predicting financial time series data. This latest edition continues to emphasize empirical financial data and focuses on real-world examples. Following this approach, readers will 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.
The author begins with the basic characteristics of financial time series data, setting the foundation for the three main topics:
* Analysis and application of univariate financial time series
* Return series of multiple assets
* Bayesian inference in finance methods
This new edition is a thoroughly revised and updated text, including the addition of S-Plus® commands and illustrations. Exercises have been thoroughly updated and expanded and include the most current data, providing readers with more opportunities to put the models and methods into practice. Among the new material added to the text, readers will find:
* Consistent covariance estimation under heteroscedasticity and serial correlation
* Alternative approaches to volatility modeling
* Financial factor models
* State-space models
* Kalman filtering
* Estimation of stochastic diffusion models
The tools provided in this text aid readers in developing a deeper understanding of financial markets through firsthand experience in working with financial data. This is an ideal textbook for MBA students as well as a reference for researchers and professionals in business and finance.
About the Author
RUEY S. TSAY, PHD, is H. G. B. Alexander Professor of Econometrics and Statistics, Graduate School of Business, University of Chicago. Dr. Tsay is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics.

