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Crude oil volatility forecasting: Insights from a novel time-varying parameter GARCH-MIDAS model

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  • Peng, Lijuan
  • Liang, Chao
  • Yang, Baoying
  • Wang, Lu

Abstract

Stationary GARCH-MIDAS models encounter challenges in effectively capturing the dynamic impact of realized volatility on crude oil price volatility. This study introduces a novel time-varying parameter GARCH-MIDAS (TVP-GARCH-MIDAS) model to address these challenges and intricately capture the evolving dynamics between variables. The empirical results underscore the superior precision of the TVP-GARCH-MIDAS model in reflecting the influence of realized volatility on crude oil price volatility over time. In comparison to the stationary GARCH-MIDAS and MS-GARCH-MIDAS models, the proposed model exhibits outstanding out-of-sample forecasting performance and has excellent economic significance. This study provides valuable insights for investors and policy-makers, supporting better risk management and more effective investment strategy formulation.

Suggested Citation

  • Peng, Lijuan & Liang, Chao & Yang, Baoying & Wang, Lu, 2024. "Crude oil volatility forecasting: Insights from a novel time-varying parameter GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 94(C).
    • Handle: RePEc:eee:reveco:v:94:y:2024:i:c:s1059056024004052
    DOI: 10.1016/j.iref.2024.103413
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    More about this item

    Keywords

    Crude oil price; GARCH-MIDAS; Volatility forecasting;
    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
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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