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ESG行业中的风险传染研究:一种基于信息熵的网络方法。

Research on Risk Contagion in ESG Industries: An Information Entropy-Based Network Approach.

作者信息

Hu Chenglong, Guo Ranran

机构信息

Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei 230026, China.

出版信息

Entropy (Basel). 2024 Feb 27;26(3):206. doi: 10.3390/e26030206.

Abstract

Sustainable development is a practical path to optimize industrial structures and enhance investment efficiency. Investigating risk contagion within ESG industries is a crucial step towards reducing systemic risks and fostering the green evolution of the economy. This research constructs ESG industry indices, taking into account the possibility of extreme tail risks, and employs VaR and CoVaR as measures of tail risk. The TENET network approach is integrated to to capture the structural evolution and direction of information flow among ESG industries, employing information entropy to quantify the topological characteristics of the network model, exploring the risk transmission paths and evolution patterns of ESG industries in an extreme tail risk event. Finally, Mantel tests are conducted to examine the existence of significant risk spillover effects between ESG and traditional industries. The research finds strong correlations among ESG industry indices during stock market crash, Sino-US trade frictions, and the COVID-19 pandemic, with industries such as the COAL, CMP, COM, RT, and RE playing key roles in risk transmission within the network, transmitting risks to other industries. Affected by systemic risk, the information entropy of the TENET network significantly decreases, reducing market information uncertainty and leading market participants to adopt more uniform investment strategies, thus diminishing the diversity of market behaviors. ESG industries show resilience in the face of extreme risks, demonstrating a lack of significant risk contagion with traditional industries.

摘要

可持续发展是优化产业结构、提高投资效率的现实途径。研究环境、社会和治理(ESG)行业内部的风险传染是降低系统性风险、推动经济绿色转型的关键一步。本研究构建了ESG行业指数,考虑到极端尾部风险的可能性,并采用风险价值(VaR)和条件风险价值(CoVaR)作为尾部风险的度量。整合了TENET网络方法来捕捉ESG行业之间的结构演变和信息流方向,利用信息熵量化网络模型的拓扑特征,探索极端尾部风险事件中ESG行业的风险传播路径和演变模式。最后,进行Mantel检验以考察ESG与传统行业之间是否存在显著的风险溢出效应。研究发现,在股市崩盘、中美贸易摩擦和新冠疫情期间,ESG行业指数之间存在很强的相关性,煤炭(COAL)、计算机(CMP)、通信(COM)、房地产(RT)和可再生能源(RE)等行业在网络内的风险传播中发挥关键作用,将风险传递给其他行业。受系统性风险影响,TENET网络的信息熵显著下降,降低了市场信息不确定性,导致市场参与者采取更趋同的投资策略,从而减少了市场行为的多样性。ESG行业在面对极端风险时表现出韧性,与传统行业之间未显示出显著的风险传染。

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