Analysis of Financial Time Series (Wiley Series in Probability and Statistics)

Ruey S. Tsay

ISBN 10: 0471690740 / ISBN 13: 9780471690740

Published by John Wiley and Sons Ltd, United Kingdom, Chicester, 2005

About this Item

This title 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; and, Bayesian inference in finance methods. This new edition is a thoroughly revised and updated text, including the addition of S-Plus(r) 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; and, 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. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Seller Inventory # GOR006747594

Bibliographic Details

• Title: Analysis of Financial Time Series (Wiley Series in Probability and Statistics)
• Publisher: John Wiley and Sons Ltd, United Kingdom, Chicester
• Publication Date: 2005
• Language: English
• ISBN 10: 0471690740
• ISBN 13: 9780471690740
• Binding: Paperback
• Edition: 2nd Edition
• Condition: Very Good
• Weight: 989 grams

About this title

Synopsis

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-PlusŪ 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.