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

Author

Listed:
  • Mohamed El Hedi Arouri

    (LEO, University of Orleans and EDHEC Business School Rue de Blois - BP 6739, 45067 Orléans Cedex 2, France)

  • Amine Lahiani

    (LEO, University of Orleans and EDHEC Business School Rue de Blois - BP 6739, 45067 Orléans Cedex 2, France)

  • Khuong Nguyen Duc

    (Professor of Finance, ISC Paris School of Management 22 Boulevard du Fort de Vaux, 75848 Paris cedex 17, France)

Abstract

This paper investigates whether structural breaks and long memory are relevant features in modeling and forecasting the conditional volatility of oil spot and futures prices using three GARCH-type models, i.e., linear GARCH, GARCH with structural breaks and FIGARCH. By relying on a modified version of Inclan and Tiao (1994)’s iterated cumulative sum of squares (ICSS) algorithm, our results can be summarized as follows. First, we provide evidence of parameter instability in five out of twelve 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 forecasting models accommodating for structural break characteristics of the data often outperform the commonly used short-memory linear volatility models. It is however worth no at the long memory evidence found in the in-sample period is not strongly supported by the out-of-sample forecasting exercise.

Suggested Citation

  • Mohamed El Hedi Arouri & Amine Lahiani & Khuong Nguyen Duc, 2010. "Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models," Working Papers 13, Development and Policies Research Center (DEPOCEN), Vietnam.
  • Handle: RePEc:dpc:wpaper:1310
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    More about this item

    Keywords

    oil markets; volatility forecasting; long memory; structural breaks; GARCH; RiskMetrics;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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