Analysis of Financial Time Series  
Financial Econometrics  

RUEY S. TSAY  
University of Chicago  
Contents  
Preface  xi  
1. Financial Time Series and Their Characteristics  1  
1.1 Asset Returns, 2   
1.2 Distributional Properties of Returns, 6   
1.3 Processes Considered, 17   
2. Linear Time Series Analysis and Its Applications  22  
2.1 Stationarity, 23   
2.2 Correlation and Autocorrelation Function, 23   
2.3 White Noise and Linear Time Series, 26   
2.4 Simple Autoregressive Models, 28   
2.5 Simple Moving-Average Models, 42   
2.6 Simple ARMA Models, 48   
2.7 Unit-Root Nonstationarity, 56   
2.8 Seasonal Models, 61   
2.9 Regression Models with Time Series Errors, 66   
2.10  Long-Memory Models, 72   
Appendix A.  Some SCA Commands, 74   
3. Conditional Heteroscedastic Models  79  
3.1 Characteristics of Volatility, 80   
3.2 Structure of a Model, 81   
3.3 The ARCH Model, 82   
3.4 The GARCH Model, 93   
3.5 The Integrated GARCH Model, 100   
3.6 The GARCH-M Model, 101   
3.7 The Exponential GARCH Model, 102   
 vii  
x  CONTENTS  
10. Markov Chain Monte Carlo Methods with Applications  395  
10.1  Markov Chain Simulation, 396   
10.2  Gibbs Sampling, 397   
10.3  Bayesian Inference, 399   
10.4  Alternative Algorithms, 403   
10.5  Linear Regression with Time-Series Errors, 406   
10.6  Missing Values and Outliers, 410   
10.7  Stochastic Volatility Models, 418   
10.8  Markov Switching Models, 429   
10.9  Forecasting, 438   
10.10  Other Applications, 441   
Index   445  

[此贴子已经被作者于2008-9-18 15:22:20编辑过]