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Asymmetric Risk Spillover between Energy Markets and Uncertainties of Economic Policy, Infectious Disease and Geopolitical Risk

Author

Listed:
  • Chuan GUO

    (School of Economics and Management, Bengbu University, Bengbu, China)

  • Yiyun FENG

    (School of Economics and Management, Bengbu University, Bengbu, China)

Abstract

The paper studies the asymmetric risk spillover effect among crude oil, natural gas and uncertainties of economic policy, infectious disease as well as geopolitical risk. We utilize a time-frequency domain spillover framework and an asymmetric spillover method. We find a weak volatility connectedness between crude oil and natural gas on average over the sample period. The spillover effect within the network is found to be highly event-dependent, reaching peaks during major geopolitical and economic events including the Gulf war, the 2007-08 global financial crisis and COVID-19 epidemic. Asymmetric spillover analysis indicates that the risk connectedness under downside markets tends to be stronger, supporting the evidence of asymmetry in spillovers. From the frequency domain analysis, we observe that spillovers are dominated by the long-run components in most periods. Furthermore, of the three uncertainties, infectious disease uncertainty transmits the highest level of long-term risk to energy markets, especially during the COVID-19. The research will be valuable to investors for risk management and governments for policy making.

Suggested Citation

  • Chuan GUO & Yiyun FENG, 2025. "Asymmetric Risk Spillover between Energy Markets and Uncertainties of Economic Policy, Infectious Disease and Geopolitical Risk," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 63-80, April.
    • Handle: RePEc:rjr:romjef:v::y:2025:i:1:p:63-80
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    References listed on IDEAS

    as
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    Cited by:

    1. Olfa El Aoun, 2026. "Market-specific connectedness behaviors across quantiles and frequencies connectedness patterns among G7 markets, commodities, bitcoin, and interest rate spread," Digital Finance, Springer, vol. 8(1), pages 1-45, March.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F30 - International Economics - - International Finance - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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