Comparative forecasting performance of symmetric and asymmetric conditional volatility models of an exchange rate

DOI10.1016/J.ECONLET.2003.09.028zbMath1254.91633OpenAlexW3121417446MaRDI QIDQ1927469

Ercan Balaban

Publication date: 1 January 2013

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1842/1833

zbMATH Keywords

heteroscedasticityforecastingexchange ratesforecast evaluationsymmetric/asymmetric volatility clustering

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Point estimation (62F10) Economic time series analysis (91B84) Statistical methods; economic indices and measures (91B82)

Related Items (1)

Forecasting volatility with support vector machine-based GARCH model

Cites Work

• Are the GARCH models best in out-of-sample performance!
• ARCH modeling in finance. A review of the theory and empirical evidence
• Forecasting exchange rate volatility using conditional variance models selected by information criteria
• Forecasting exchange rate volatility.

This page was built for publication: Comparative forecasting performance of symmetric and asymmetric conditional volatility models of an exchange rate