Risk Spillovers between China's Climate Policy Uncertainty and Green Assets

Authors

  • Yonghui Meng Shanghai University, Shanghai, 200000, China

DOI:

https://doi.org/10.54691/qevy1k18

Keywords:

China's Climate Policy Uncertainty; Green Assets; Risk Spillovers.

Abstract

This paper uses a TVP-VAR-DY model to examine the dynamic risk spillover effects between China's climate policy uncertainty (CCPU) and green assets. Monthly data from 2017 to 2026 are selected, covering assets such as green power, CSI New Energy, Shanghai Stock Exchange Green Bond, WTI crude oil, and gold ETFs. The spillover effects among these variables are analyzed from both static and dynamic perspectives. The analysis shows that there are significant time-varying and asymmetric spillover effects between green assets and CCPU, especially during major climate events and policy adjustments. WTI crude oil has the most significant impact on CCPU, while gold ETFs have a positive spillover effect on green bonds and CSI New Energy. The results indicate that CCPU has a significant dynamic impact on green assets. Investor and policymakers should closely monitor policy changes to optimize asset allocation and enhance risk management capabilities.

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References

[1] Ding, S., Liang, Z., & Chen, J. (2023). Research on the spillover effects among climate policy uncertainty, energy, and metal markets from the time frequency perspective. Systems Engineering-Theory & Practice, 43(8), 2222–2235. https://doi.org/10.12011/SETP2022 2462

[2] Liu, Z., Ding, Z., & Duan, Z. (2023). Does climate policy uncertainty exacerbate extreme risk spillovers across energy markets? Systems Engineering-Theory & Practice, 43(6), 1651–1667. https://doi.org/10.12011/SETP2022 2280

[3] Zhang, Y., Guo, K., Ji, Q., & Zhao, W. (2023). Information spillover effect of climate shocks on Chinese asset returns. China Journal of Econometrics, 3(2), 426–442. https://doi.org/10.12012/CJoE2022 0125

[4] Ji, Q., Zhao, W., Zhang, D., & Guo, K. (2022). Climate risk perception and its impacts on financial markets: micro evidence from listed firms in China. China Journal of Econometrics, 2(3), 666–680.

[5] Ren, X., Li, J., He, F., & Lucey, B. (2023). Impact of climate policy uncertainty on traditional energy and green markets: Evidence from time varying granger tests. Renewable and Sustainable Energy Reviews, 173, 113058.

[6] Lei, H., Xue, M., & Ye, J. (2024). The nexus between ReFi, carbon, fossil energy, and clean energy assets: Quantile time–frequency connectedness and portfolio implications. Energy Economics, 132, 107456. https://doi.org/10.1016/j.eneco.2024.107456

[7] Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on time varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084

[8] Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66. https://doi.org/10.1016/j.ijforecast.2011.02.006

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Published

2026-10-25

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