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Modeling and forecasting the volatility of petroleum futures prices

Sang Hoon Kang and Seong-Min Yoon ()

Energy Economics, 2013, vol. 36, issue C, 354-362

Abstract: We investigate volatility models and their forecasting abilities for three types of petroleum futures contracts traded on the New York Mercantile Exchange (West Texas Intermediate crude oil, heating oil #2, and unleaded gasoline) and suggest some stylized facts about the volatility of these futures markets, particularly in regard to volatility persistence (or long-memory properties). In this context, we examine the persistence of market returns and volatility simultaneously using the following ARFIMA–GARCH-class models: ARIMA–GARCH, ARFIMA–GARCH, ARFIMA–IGARCH, and ARFIMA–FIGARCH. Although the ARFIMA–FIGARCH model better captures long-memory properties of returns and volatility, the out-of-sample analysis indicates no unique model for all three types of petroleum futures contracts, suggesting that investors should be careful when measuring and forecasting the volatility (risk) of petroleum futures markets.

Keywords: DM test; Forecasting ability; Long memory; Persistence; Petroleum futures (search for similar items in EconPapers)
JEL-codes: C32 C52 G17 Q40 (search for similar items in EconPapers)
Date: 2013
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Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

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