Density Forecasts of Crude-Oil Prices Using Option-Implied and ARCH-Type Models

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  • Leonidas Tsiaras, Denmark
  • Esben Høg, Denmark

The predictive accuracy of competing crude-oil price forecast densities is investigated for the 1994-2006 period. Moving beyond standard ARCH models that rely exclusively on past returns, we examine the benefits of utilizing the forward-looking information that is embedded in the prices of derivative contracts. Risk-neutral densities, obtained from panels of crude-oil option prices, are adjusted to reflect real-world risks using either a parametric or a non-parametric calibration approach. The relative performance of the models is evaluated for the entire support of the density, as well as for regions and intervals that are of special interest for the economic agent. We find that non-parametric adjustments of risk-neutral density forecasts perform significantly better than their parametric counterparts. Goodness-of-fit tests and out-of-sample likelihood comparisons favor forecast densities obtained by option prices and non-parametric calibration methods over those constructed using historical returns and simulated ARCH processes.

Original languageEnglish
Publication year2009
Publication statusPublished - 2009
Event15th International Conference on Computing in Economics and Finance - Sydney, Australia
Duration: 15 Jul 200917 Jul 2009


Conference15th International Conference on Computing in Economics and Finance

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