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Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models

Mohamed Arouri (), Amine Lahiani, Aldo Lévy and Duc Khuong Nguyen

Energy Economics, 2012, vol. 34, issue 1, 283-293

Abstract: This paper extends previous studies by investigating the relevance of structural breaks and long memory in modeling and forecasting the conditional volatility of oil spot and futures prices using a variety of GARCH-type models. Our results can be summarized as follows. First, we provide evidence of parameter instability in five out of nine GARCH-based conditional volatility processes for energy prices. Second, long memory is effectively present in all the series considered and a FIGARCH model seems to better fit the data, but the degree of volatility persistence diminishes significantly after adjusting for structural breaks. Finally, the out-of-sample analysis shows that volatility models accommodating instability and long memory characteristics of the data provide the best volatility forecasts for most cases.

Keywords: Oil markets; Volatility forecasting; Long memory; Structural breaks; GARCH-class models (search for similar items in EconPapers)
JEL-codes: C22 C53 F47 G17 Q47 Q43 (search for similar items in EconPapers)
Date: 2012
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Related works:
Working Paper: Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models (2012)
Working Paper: Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models (2010) Downloads
Working Paper: Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models (2010) Downloads
Working Paper: Forecasting the Conditional Volatility of Oil Spot andFutures Prices with Structural Breaksand Long Memory Models (2010) Downloads
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