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Long Memory in Oil and Refined Products Markets

  • Kyongwook Choi
  • Shawkat Hammoudeh

We test for the presence of long memory in daily oil and refined products prices absolute return, squared return and conditional volatility, using several parametric and semiparametric methods. This study finds strong evidence of long memory (LM) in the daily absolute and squared spot and futures returns for crude oil, gasoline and heating oil but at different degrees. The FIGARCH model also demonstrates strong evidence of LM for volatility for most of oil and products prices returns, with also different resilience levels. Structural breaks have only the partial effects of slightly reducing persistence for just absolute and squared returns. Examining the forecasting behavior of two competing models, the less parsimonious ARFIMA which satisfies the LM property, and the parsimonious ARMA with short-term processes, the ARFIMA model provides significantly better out-of-sample forecasts at all forecasting horizons for all three petroleum types.

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Article provided by International Association for Energy Economics in its journal The Energy Journal.

Volume (Year): Volume 30 (2009)
Issue (Month): Number 2 ()
Pages: 97-116

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Handle: RePEc:aen:journl:2009v30-02-a05
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