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Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models?

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  • Zhang, Yue-Jun
  • Yao, Ting
  • He, Ling-Yun
  • Ripple, Ronald

Abstract

GARCH-type models are frequently used to forecast crude oil price volatility, and whether we should consider multiple regimes for the GARCH-type models is of great significance for the forecasting work but does not have a final conclusion yet. To that end, this paper estimates and forecasts crude oil price volatility using three single-regime GARCH (i.e., GARCH, GJR-GARCH and EGARCH) and two regime-switching GARCH (i.e., MMGARCH and MRS-GARCH) models. Furthermore, the Model Confidence Set (MCS) procedure is employed to evaluate the forecasting performance. The in-sample results show that the MRS-GARCH model provides higher estimation accuracy in weekly data. However, the out-of-sample results show the limited significance of considering the regime switching. Overall, our results indicate that the incorporation of regime switching does not perform significantly better than the single-regime GARCH models. The findings are proved to be robust to both daily and weekly data for WTI and Brent over different time horizons.

Suggested Citation

  • Zhang, Yue-Jun & Yao, Ting & He, Ling-Yun & Ripple, Ronald, 2019. "Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 302-317.
  • Handle: RePEc:eee:reveco:v:59:y:2019:i:c:p:302-317
    DOI: 10.1016/j.iref.2018.09.006
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    More about this item

    Keywords

    Crude oil market; Volatility forecasting; GARCH; Regime switching; MCS;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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