Volatility forecasting for crude oil futures

Massimiliano Marzo and Paolo Zagaglia

No 2007:9, Research Papers in Economics from Stockholm University, Department of Economics

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, Student’s 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 regulators’ preferences. EGARCH models display the best performance in this case.

Keywords: GARCH models; kurtosis; oil prices; forecasting (search for similar items in EconPapers)
JEL-codes: C22 G19 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2007-06-21
New Economics Papers: this item is included in nep-ene, nep-ets, nep-for and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Journal Article: Volatility forecasting for crude oil futures (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:sunrpe:2007_0009

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