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Forecast evaluation in daily commodities futures markets

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  • Periklis Gogas
  • Apostolos Serletis

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.

Suggested Citation

  • Periklis Gogas & Apostolos Serletis, 2010. "Forecast evaluation in daily commodities futures markets," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 1(2), pages 155-168.
    • Handle: RePEc:ids:ijfmkd:v:1:y:2010:i:2:p:155-168
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