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Forecasting volatility of crude oil markets

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  • Kang, Sang Hoon
  • Kang, Sang-Mok
  • Yoon, Seong-Min

Abstract

This article investigates the efficacy of a volatility model for three crude oil markets -- Brent, Dubai, and West Texas Intermediate (WTI) -- with regard to its ability to forecast and identify volatility stylized facts, in particular volatility persistence or long memory. In this context, we assess persistence in the volatility of the three crude oil prices using conditional volatility models. The CGARCH and FIGARCH models are better equipped to capture persistence than are the GARCH and IGARCH models. The CGARCH and FIGARCH models also provide superior performance in out-of-sample volatility forecasts. We conclude that the CGARCH and FIGARCH models are useful for modeling and forecasting persistence in the volatility of crude oil prices.

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Bibliographic Info

Article provided by Elsevier in its journal Energy Economics.

Volume (Year): 31 (2009)
Issue (Month): 1 (January)
Pages: 119-125

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Handle: RePEc:eee:eneeco:v:31:y:2009:i:1:p:119-125

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Web page: http://www.elsevier.com/locate/eneco

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Keywords: Persistence Long memory CGARCH FIGARCH;

References

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