Impact of the China's new energy market on carbon price fluctuation risk: Evidence from seven pilot carbon markets

Since China implemented its carbon trading mechanism, trading risks arising from unstable carbon prices have significantly reduced its emission-reduction efficiency. Unlike traditional research, which focuses on the impact of fossil fuels on carbon prices, this study emphasises risk spillovers from new energy markets amidst large-scale renewable energy deployment. Moreover, to address subjectivity in variable selection and overfitting issues in carbon price determinants, the LASSO algorithm is integrated with the multivariate GARCH model. Using daily carbon quota prices from seven Chinese pilot markets (2014–2022), factors driving carbon price volatility are systematically identified, and the heterogeneous influence of new energy markets on carbon market risks is rigorously analysed. The results indicate that new energy market volatility significantly contributes to carbon price fluctuations. A 1 % increase in the CNI New Energy Index induces co-movement in carbon prices: Hubei (+0.08 %), Beijing (+0.01 %) and Shenzhen (+0.06 %), while Shanghai exhibits inverse sensitivity (−0.19 %). Prices in Guangdong, Tianjin and Chongqing show minimal responsiveness. Additionally, the correlation between new energy markets and carbon markets exhibits temporal heterogeneity. Furthermore, the asymmetric leverage effect suggests that negative news in new energy markets has a more significant impact on carbon markets than positive news. This study advances theoretical understanding of carbon price dynamics and offers practical insights for enhancing risk management frameworks in emissions trading systems.

Authors

Publication Details

Journal
Energy Strategy Reviews
Published
2025-04-12
DOI
https://doi.org/10.1016/j.esr.2025.101718
Citations
5
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
15.66

Funders

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article

Impact of the China's new energy market on carbon price fluctuation risk: Evidence from seven pilot carbon markets

Yi‐Ming Wei, Chang-Jing Ji, Shipeng Yan, Qiao‐Mei Liang et al.
5 citations
Energy Strategy Reviews
Market Dynamics and Volatility
15.66
article

Impact of the China's new energy market on carbon price fluctuation risk: Evidence from seven pilot carbon markets

Yi‐Ming Wei, Chang-Jing Ji, Shipeng Yan, Qiao‐Mei Liang, Xiangyu Wang, Yi Chen, Dehua Li, Ran Pu
article en
5 citations

Abstract

Since China implemented its carbon trading mechanism, trading risks arising from unstable carbon prices have significantly reduced its emission-reduction efficiency. Unlike traditional research, which focuses on the impact of fossil fuels on carbon prices, this study emphasises risk spillovers from new energy markets amidst large-scale renewable energy deployment. Moreover, to address subjectivity in variable selection and overfitting issues in carbon price determinants, the LASSO algorithm is integrated with the multivariate GARCH model. Using daily carbon quota prices from seven Chinese pilot markets (2014–2022), factors driving carbon price volatility are systematically identified, and the heterogeneous influence of new energy markets on carbon market risks is rigorously analysed. The results indicate that new energy market volatility significantly contributes to carbon price fluctuations. A 1 % increase in the CNI New Energy Index induces co-movement in carbon prices: Hubei (+0.08 %), Beijing (+0.01 %) and Shenzhen (+0.06 %), while Shanghai exhibits inverse sensitivity (−0.19 %). Prices in Guangdong, Tianjin and Chongqing show minimal responsiveness. Additionally, the correlation between new energy markets and carbon markets exhibits temporal heterogeneity. Furthermore, the asymmetric leverage effect suggests that negative news in new energy markets has a more significant impact on carbon markets than positive news. This study advances theoretical understanding of carbon price dynamics and offers practical insights for enhancing risk management frameworks in emissions trading systems.

Energy Strategy ReviewsVol. 59
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 2%
Market Dynamics and Volatility
15.66
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