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The contagion of extreme risks between fossil and green energy markets: evidence from China

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  • Xiaohang Ren
  • Ya Xiao
  • Feng He
  • Giray Gozgor

Abstract

This paper combines the Generalized Autoregressive Conditional Heteroskedasticity-Extreme Value Theory-Value at Risk (GARCH-EVT-VaR) method in conjunction with the Time-Varying Parameter Diebold-Yilmaz (TVP-VAR-DY) model to investigate the contagion of extreme risks between fossil and green energy markets in China. Specifically, the study concentrates on coal, crude oil, and natural gas markets as representative sectors for fossil energy, while green bonds, investments, green power, and associated new energy markets are chosen as representatives for the green energy sector. Our analysis reveals that extreme events can rapidly propagate risks between fossil and green energy markets, particularly during significant shifts in the external environment. Notably, green energy markets exhibit greater susceptibility to severe risks compared to their fossil energy counterparts, indicative of their instability and immaturity. Moreover, the analysis highlights the green bond market's heightened sensitivity to extreme risks, with green investments playing a pivotal role in propagating such risks throughout the system. These insights underscore the intricate dynamics of risk contagion between fossil and green energy markets, emphasizing the need for comprehensive risk management strategies in both sectors.

Suggested Citation

  • Xiaohang Ren & Ya Xiao & Feng He & Giray Gozgor, 2024. "The contagion of extreme risks between fossil and green energy markets: evidence from China," Quantitative Finance, Taylor & Francis Journals, vol. 24(5), pages 627-642, May.
    • Handle: RePEc:taf:quantf:v:24:y:2024:i:5:p:627-642
    DOI: 10.1080/14697688.2024.2339374
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    Cited by:

    1. Ren, Xiaohang & Fu, Chenjia & Jin, Chenglu & Li, Yuyi, 2024. "Dynamic causality between global supply chain pressures and China's resource industries: A time-varying Granger analysis," International Review of Financial Analysis, Elsevier, vol. 95(PA).

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