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]