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Volatility forecasting of Chinese energy market: Which uncertainty have better performance?

Author

Listed:
  • Zhang, Jiaming
  • Xiang, Yitian
  • Zou, Yang
  • Guo, Songlin

Abstract

This paper examines the effects of seven uncertainty indices on Chinese energy price volatility and analyses the influencing factors using the extended GARCH-MIDAS model. Our in-sample analysis shows that energy market volatility is negatively impacted by global and Chinese economic policy uncertainty (GEPU, CNEPU), the geopolitical risk act index (GPRA), and the climate policy uncertainty index (CPU). Out-of-sample forecasting results demonstrate that the CPU is a major cause of energy volatility in China, and our extended model exhibits higher forecast accuracy. Additionally, we discover that the CPU has a greater capacity for energy volatility during periods of low volatility, while high energy volatility is often associated with GPR. Finally, the outbreak of the Russia-Ukraine conflict resulted in a decline in the predictive capacity of the CPU while causing a boost in the EPU's predictive power.

Suggested Citation

  • Zhang, Jiaming & Xiang, Yitian & Zou, Yang & Guo, Songlin, 2024. "Volatility forecasting of Chinese energy market: Which uncertainty have better performance?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    • Handle: RePEc:eee:finana:v:91:y:2024:i:c:s1057521923004684
    DOI: 10.1016/j.irfa.2023.102952
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    Citations

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    Cited by:

    1. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.

    More about this item

    Keywords

    Chinese energy market; Uncertainty index; 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
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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