An International Comparison of Implied, Realized and GARCH Volatility Forecasts

Journal of Futures Markets, Forthcoming

98 Pages Posted: 26 Mar 2016 Last revised: 20 Apr 2016

See all articles by Apostolos Kourtis

Apostolos Kourtis

University of East Anglia (UEA) - Norwich Business School

Raphael N. Markellos

University of East Anglia (UEA) - Norwich Business School

Lazaros Symeonidis

University of East Anglia (UEA) - Norwich Business School

Date Written: March 24, 2016

Abstract

We compare the predictive ability and economic value of implied, realized and GARCH volatility models for 13 equity indices from 10 countries. Model ranking is similar across countries, but varies with the forecast horizon. At the daily horizon, the Heterogeneous Autoregressive model offers the most accurate predictions while an implied volatility model that corrects for the volatility risk premium is superior at the monthly horizon. Widely used GARCH models have inferior performance in almost all cases considered. All methods perform significantly worse over the 2008-09 crisis period. Finally, implied volatility offers significant improvements against historical methods for international portfolio diversification.

Keywords: Implied Volatility, Realized Volatility, Volatility Risk Premium, Financial Crisis, International Diversification

JEL Classification: G15; G17; G01; G11

Suggested Citation

Kourtis, Apostolos and Markellos, Raphael N. and Symeonidis, Lazaros, An International Comparison of Implied, Realized and GARCH Volatility Forecasts (March 24, 2016). Journal of Futures Markets, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2754190

Apostolos Kourtis

University of East Anglia (UEA) - Norwich Business School ( email )

Norwich
NR4 7TJ
United Kingdom

Raphael N. Markellos (Contact Author)

University of East Anglia (UEA) - Norwich Business School ( email )

Norwich
NR4 7TJ
United Kingdom

Lazaros Symeonidis

University of East Anglia (UEA) - Norwich Business School ( email )

Norwich
NR4 7TJ
United Kingdom

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