Empirical studies on volatility in international stock markets / by Eugenie M.J.H. Hol.

Format:

Book

Author/Creator:

Hol, Eugenie M. J. H.

Series:

Dynamic modeling and econometrics in economics and finance ; v. 6.

Dynamic modeling and econometrics in economics and finance ; v. 6

Language:

English

Subjects (All):

Options (Finance)--Mathematical models.

Options (Finance).

Stock price forecasting--Mathematical models.

Stock price forecasting.

Securities--Prices--Mathematical models.

Securities.

Stochastic analysis.

Physical Description:

xiv, 161 pages : illustrations ; 25 cm.

Place of Publication:

Dordrecht ; Boston : Kluwer Academic, [2003]

Contents:

2. Asset Return Volatility Models 7

2.1 Empirical Stylised Facts of Stock Index Return Series 8

2.2 Time-Varying Volatility Models 12

2.2.1 GARCH Models 13

2.2.2 SV Models 16

2.3 Empirical Applications of Time-Varying Volatility Models 19

3. The Stochastic Volatility in Mean Model: Empirical evidence from international stock markets 27

3.2 The Stochastic Volatility in Mean Model 28

3.3 Some Theory on the Relationship between Returns and Volatility 30

3.4 Data 33

3.5 Estimation Results for the SVM Model and Some Diagnostics 36

3.6 Some Comparisons with GARCH-M Estimation Results 42

4. Forecasting with Volatility Models 49

4.1 Volatility Models and Their Forecasts 49

4.2 An Empirical Study of Six International Stock Indices 52

4.2.1 Data and Methodology 54

4.2.2 Forecasting Results 58

5. Implied Volatility 63

5.1 The Black-Scholes Option Pricing Model 63

5.2 Forecasting with Implied Volatility: Empirical evidence 67

6. Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility 71

6.2 Model Specifications 73

6.3 Data Description and Empirical In-Sample Results 77

6.3.1 Data 77

6.3.2 Empirical In-Sample Results 81

6.4 Volatility Forecasting Methodology 84

6.4.1 Stochastic Volatility Model Forecasts 84

6.4.2 SVX[superscript +] and SIV Model Forecasts 85

6.4.3 Measuring Predictive Forecasting Ability 85

6.4.4 Intraday Volatility 87

6.5 Out-of-Sample Results 89

6.5.1 The Parameters Estimates of the SV Model 89

6.5.2 Empirical Out-of-Sample Forecasting Results 91

7. Stock Index Volatility Forecasting with High Frequency Data 99

7.2 Stock Return Data and Volatility 101

7.2.1 Data 101

7.2.2 Intraday Volatility 103

7.3 Realised Volatility Models 108

7.3.1 Unobserved Components OU Type Stochastic Volatility Models 108

7.3.2 ARFIMA Models 110

7.4 Daily Time-Varying Volatility Models 112

7.4.1 Daily SV Model 112

7.4.2 Daily SV Model with Intraday Volatility 114

7.4.3 Daily GARCH(1,1) Model 115

7.4.4 Daily GARCH(1,1) Model with Intraday Volatility 116

7.5 Forecasting Methodology and Evaluation Criteria 117

7.5.1 Forecasting Methodology 117

7.5.2 Evaluation Criteria 117

7.6 Empirical Results 119

7.6.1 In-Sample Results 119

7.6.2 Out-of-Sample Results 122

A. Estimation of the SVM Model 135

A.1 Model 135

A.2 Likelihood Evaluation Using Importance Sampling 136

A.3 Approximating Gaussian Model Used For Importance Sampling 137

A.4 Monte Carlo Evidence of Estimation Procedure 139

B. Estimation of the SVX Models 145

B.1 The SVX Model in State Space Form 145

B.2 Parameter Estimation by Simulated Maximum Likelihood 146

B.3 Computational Implementation 147

C. Data and Programs 149.

Notes:

Includes bibliographical references (pages 151-157) and index.

ISBN:

1402075197

OCLC:

52358465