Forecasting volatility in European stock markets with non-linear GARCH models

Arbeitspapier

This paper investigates the forecasting performance of three popular variants of the non-linear GARCH models, namely VS-GARCH, GJR-GARCH and Q-GARCH, with the symmetric GARCH(1,1) model as a benchmark. The application involves ten European stock price indexes. Forecasts produced by each non-linear GARCH model and each index are evaluated using a common set of classical criteria, as well as forecast combination techniques with constant and non-constant weights. With respect to the standard GARCH specification, the non-linear models generally lead to better forecasts in terms of both smaller forecast errors and lower biases. In-sample forecast combination regressions are better than those from single Mincer-Zarnowitz regressions. The out-of-sample performance of combining forecasts is less satisfactory, irrespective of the type of weights adopted.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Nota di Lavoro ; No. 98.2002

Classification and Topics

• Classification: Wirtschaft ; General Economics: General ; Econometric and Statistical Methods and Methodology: General ; Econometric Modeling: General ; General Financial Markets: General (includes Measurement and Data)
• Subject: Volatility ; GARCH ; forecast evaluation ; Aktienmarkt ; Börsenkurs ; Volatilität ; Prognose ; ARCH-Modell ; Europa

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Forte, Gianfranco ; Manera, Matteo
• Event: Veröffentlichung
• (who): Fondazione Eni Enrico Mattei (FEEM)
• (where): Milano
• (when): 2002

Further information

• Handle: http://hdl.handle.net/10419/119703
• Last update: 10.03.2025, 11:41 AM CET