Authors: Periklis Gogas, Apostolos Serletis
Addresses: Department of International Economic Relations and Development, Democritus University of Thrace, 69100 Komotini Campus, Greece. ' Department of Economics, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
Abstract: In this paper, we use recent advances in the financial econometrics literature to model the time-varying conditional variance in five energy markets – crude oil, gasoline, heating oil, propane, and natural gas – using daily data over the period from January 3, 1994 to September 23, 2008. We estimate autoregressive conditional heteroscedasticity (ARCH) and generalised ARCH (GARCH) models using a variety of error densities (the normal, Student-t, and generalised error distribution) and diagnostic checks. We use the models to perform static and dynamic forecasts over different horizons and compare their performance to that of a random walk model.
Keywords: energy markets; forecasting; autoregressive conditional heteroscedasticity; derivatives; ARCH; commodities futures markets; financial econometrics; crude oil; gasoline; heating oil; propane; natural gas.
International Journal of Financial Markets and Derivatives, 2010 Vol.1 No.2, pp.155 - 168
Published online: 03 Apr 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article