Research Papers in Economics, Department of Economics, Stockholm University
Volatility forecasting for crude oil futures
() and Paolo Zagaglia
Abstract: This paper studies the forecasting properties of linear
GARCH models for closing-day futures prices on crude oil, first position,
traded in the New York Mercantile Exchange from January 1995 to November
2005. In order to account for fat tails in the empirical distribution of
the series, we compare models based on the normal, Studentís t and
Generalized Exponential distribution. We focus on out-of-sample
predictability by ranking the models according to a large array of
statistical loss functions. The results from the tests for predictive
ability show that the GARCH-G model fares best for short horizons from one
to three days ahead. For horizons from one week ahead, no superior model
can be identified. We also consider out-of-sample loss functions based on
Value-at-Risk that mimic portfolio managers and regulatorsí preferences.
EGARCH models display the best performance in this case.
Keywords: GARCH models; kurtosis; oil prices; forecasting; (follow links to similar papers)
JEL-Codes: C22; G19; (follow links to similar papers)
33 pages, June 21, 2007
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