Forecast evaluation in daily commodities futures markets
by Periklis Gogas, Apostolos Serletis
International Journal of Financial Markets and Derivatives (IJFMD), Vol. 1, No. 2, 2010

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.

Online publication date: Sat, 03-Apr-2010

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