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- Product code: 22228
- ISBN: 0471690740,
ISBN13: 9780471690740,
640 pages, hardback
Published by John Wiley & Sons Inc on 2005
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Description of Analysis of Financial Time Series |
Gain the statistical tools and techniques you need to understand today's financial markets with the Second Edition of this critically acclaimed book. You'll 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. You'll master key aspects of financial time series, including volatility modeling, neural network applications, market microstructure and high frequency financial data, continuous time models and Itos 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.
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Reviews"…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
| Contents of Analysis of Financial Time Series |
1. Financial Time Series and Their Characteristics
2. Linear Time Series Analysis and Its Applications
3. Conditional Heteroscedastic Models
4. Nonlinear Models and Their Applications
5. High-Frequency Data Analysis and Market Microstructure
6. Continuous-Time Models and Their Applications
7. Extreme Values, Quantile Estimation, and Value at Risk
8. Multivariate Time Series Analysis and Its Applications
9. Principal Component Analysis and Factor Models
10. Multivariate Volatility Models and Their Applications
11. State-Space Models and Kalman Filter
12. Markov Chain Monte Carlo Methods
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About Ruey S. Tsay |
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.
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