Network Analysis of Volatility Spillovers Between Environmental, Social, and Governance (ESG) Rating Stocks: Evidence from China
Tian, Miao; Li, Shuhuai; Cao, Xianghan; Wang, Guizhou (2025-05-12)
Tian, Miao
Li, Shuhuai
Cao, Xianghan
Wang, Guizhou
MDPI
12.05.2025
Tian, M., Li, S., Cao, X., & Wang, G. (2025). Network Analysis of Volatility Spillovers Between Environmental, Social, and Governance (ESG) Rating Stocks: Evidence from China. Mathematics, 13(10), 1586. https://doi.org/10.3390/math13101586
https://creativecommons.org/licenses/by/4.0/
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
https://creativecommons.org/licenses/by/4.0/
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202506034101
https://urn.fi/URN:NBN:fi:oulu-202506034101
Tiivistelmä
Abstract
In the globalized economic system, environmental, social, and governance (ESG) factors have emerged as critical dimensions for assessing non-financial performance and ensuring the long-term sustainable development of businesses, influencing corporate behavior, investor expectations, and regulatory landscapes. This article applies the VAR-DY network analysis method to construct a large-scale financial volatility spillover network covering all Chinese stocks. It explores the risk transmission paths among different ESG-rated groups and analyzes the patterns and impacts of risk transmission during extreme market volatility. The study finds that as ESG ratings decrease from AAA to C, the network’s average shortest path length and average connectedness strength decreases, indicating that highly rated companies play a central role in the network and maintain their ESG ratings through close connections, positively affecting market stability. However, analyses of the 2015 Chinese stock market crash and the COVID-19 pandemic show a general increase in volatility spillover effects. Notably, the direction of risk spillover in relation to ESG ratings was opposite in these two events, reflecting differences in the underlying drivers of market volatility. This suggests that under extreme market conditions, traditional risk management tools need to be optimized by incorporating ESG factors to better address risk contagion.
In the globalized economic system, environmental, social, and governance (ESG) factors have emerged as critical dimensions for assessing non-financial performance and ensuring the long-term sustainable development of businesses, influencing corporate behavior, investor expectations, and regulatory landscapes. This article applies the VAR-DY network analysis method to construct a large-scale financial volatility spillover network covering all Chinese stocks. It explores the risk transmission paths among different ESG-rated groups and analyzes the patterns and impacts of risk transmission during extreme market volatility. The study finds that as ESG ratings decrease from AAA to C, the network’s average shortest path length and average connectedness strength decreases, indicating that highly rated companies play a central role in the network and maintain their ESG ratings through close connections, positively affecting market stability. However, analyses of the 2015 Chinese stock market crash and the COVID-19 pandemic show a general increase in volatility spillover effects. Notably, the direction of risk spillover in relation to ESG ratings was opposite in these two events, reflecting differences in the underlying drivers of market volatility. This suggests that under extreme market conditions, traditional risk management tools need to be optimized by incorporating ESG factors to better address risk contagion.
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