4.7 Article

Modeling and forecasting the volatility of petroleum futures prices

Journal

ENERGY ECONOMICS
Volume 36, Issue -, Pages 354-362

Publisher

ELSEVIER
DOI: 10.1016/j.eneco.2012.09.010

Keywords

DM test; Forecasting ability; Long memory; Persistence; Petroleum futures

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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 ARF1MA-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. (C) 2012 Elsevier B.V. All rights reserved.

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