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

Xiaohang Ren, Ya Xiao, Feng He and Giray Gözgör

Quantitative Finance, 2024, vol. 24, issue 5, 627-642

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.

Date: 2024
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://hdl.handle.net/10.1080/14697688.2024.2339374 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:quantf:v:24:y:2024:i:5:p:627-642

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20

DOI: 10.1080/14697688.2024.2339374

Access Statistics for this article

Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral

More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().