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Challenges for volatility forecasts of US fossil energy spot markets during the COVID-19 crisis

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  • Li, Zepei
  • Huang, Haizhen

Abstract

The outbreak of the COVID-19 pandemic led to a slowdown in the world's energy trade and changes in the use of energy resources. Meanwhile, global conditions are complex and can affect fossil energy spot markets, including crude oil, gasoline, heating oil, and natural gas. In this paper, we conduct comparative research to explore the impact of global conditions on fossil energy spot markets during the COVID-19 crisis based on the GARCH-MIDAS framework. We employ a 2010–2022 sample, which we cut off to investigate the differences before and after COVID-19. In-sample estimation shows that all global indicators are significant for forecasting the volatilities of these fossil energy spot prices. Out-sample forecasts reveal that GEPU and GECON outperform GPR and WIP for forecasting these four markets during the pre-COVID-19 period. After the crisis broke out, these global indicators can provide different forecasting information. Hence, this paper can be helpful for decision-makers to formulate and adjust pertinent policies and investments in the case of extreme emergencies in the future.

Suggested Citation

  • Li, Zepei & Huang, Haizhen, 2023. "Challenges for volatility forecasts of US fossil energy spot markets during the COVID-19 crisis," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 31-45.
    • Handle: RePEc:eee:reveco:v:86:y:2023:i:c:p:31-45
    DOI: 10.1016/j.iref.2023.02.004
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    More about this item

    Keywords

    Fossil energy; COVID-19; Volatility forecasting; Global indicators; GARCH-MIDAS;
    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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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