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书名：Modelling Financial Time Series with S-PLUS

作者：Eric Zivot & Jiahui Wang

Contents:

1. S and S-PLUS

1.1 Intoduction

1.2 S Objects

1.3 Modeling Functions in S+FinMetrics

1.4 S-PLUS Resources

2. Time Series Specification, Manipulation and Visualization in S-PLUS

2.1 Introduction

2.2 The Specification of "Time Series" Objects in S-PLUS

2.3 Time Series Manipulation in S-PLUS

2.4 Visualization Time Series in S-PLUS

3. Time Series Concepts

3.1 Introduction

3.2 Univariate Time Series

3.3 Univariate Nonstationary Time Series

3.4 Long Memory Time Series

3.5 Multivariate Time Series

4. Unit Root Test

4.1 Introduction

4.2 Testing for Nonstationarity and Stationarity

4.3 Autoregressive Unit Root Tests

4.4 Stationarity Tests

5. Modeling Extreme Values

5.1 Introduction

5.2 Modeling Maxima and Worst Cases

5.3 Modeling Extreme Over High Thresholds

5.4 Hill's Non-parametric Estimator of Tail Index

6. Time Series Regression Modeling

6.1 Introduction

6.2 Time Series Regression Model

6.3 Time Series Regression Using the S+FinMetrics Function OLS

6.4 Dynamic Regression

6.5 Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimate

6.6 Recursive Least Squares Estimation

7. Univariate GARCH Modeling

7.1 Introduction

7.2 The Basic ARCH Model

7.3 The GARCH Model and Its Properties

7.4 GARCH Modeling Using S+FinMetrics

7.5 GARCH Model Extensions

7.6 GARCH Model Selection and Comparison

7.7 GARCH Model Prediction

7.8 GARCH Model Simulation

8. Long Memory Time Series Modeling

8.1 Introduction

8.2 Long Memory Time Series

8.3 Statistical Tests for Long Memory

8.4 Estimation of Long Memory Parameter

8.5 Estimation of FARIMA and SEMIFA Models

8.6 Long Memory GARCH Models

8.7 Prediction from Long Memory Models

9. Rolling Analysis of Time Series

9.1 Introduction

9.2 Rolling Descriptive Statistics

9.3 Technical Analysis Indicator

9.4 Rollling Regression

10. Systems of Regression Equations

10.1 Introduction

10.2 Systems of Regression Equations

10.3 Linear Seemingly Unrelated Regressions

10.4 Nonlinear Seemingly Unrelated Regression Models

11. Vector Autoregressive Models for Multivariate Time Series

11.1 Introduction

11.2 The Stationary Vector Autoregressive Models

11.3 Forecasting

11.4 Structure Analysis

11.5 An Extended Example

11.6 Bayesian Vector Autoregression

12. Cointegration

12.1 Introduction

12.2 Spurious Regression and Cointegration

12.3 Residual-Based Tests for Cointegration

12.4 Regression-Based Estimates of Cointegrating Vectors and Error Correction Models

12.5 VAR Models and Cointegration

13. Multivariate GARCH Modeling

13.1 Introduction

13.2 Expotentially Weirhted Covariance Estimate

13.3 Diagnol VEC Model

13.4 Multivariate GARCH Modeling in FinMetrics

13.5 Multivariate GARCH Model Extensions

13.6 Multivariate GARCH Prediction

13.7 Custom Estimation of GARCH Model

13.8 Multivariate GARCH Model Simulation

14. State Space Models

14.1 Introduction

14.2 State Space Representation

14.3 Algorithms

14.4 Estimation of State Space Models

14.5 Simulation Smoothing

15. Factor Models for Asset Returns

15.1 Introduction

15.2 Factor Models Specification

15.3 Macroeconomic Factor Models for Returns

15.4 Fundalmental Factor Models

15.5 Statistical Factor Models for Returns

16. Term Structure of Interest Rates

16.1 Introduction

16.2 Discount, Spot and Forward Rates

16.3 Qudratic and Cubic Spline Interpolation

16.4 Smoothing Spline Interpolation

16.5 Nelson-Siegel Function

17. Robust Change Detection

17.1 Introduction

17.2 REGARIMA Models

17.3 Robust Fitting of REGARIMA Models

17.4 Prediction Using REGARIMA Models

17.5 Controling Robust Fitting of REGARIMA Models

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[此贴子已经被作者于2006-2-16 0:55:13编辑过]