ESG and the Stock Market: Is ESG Exposure Systematic?

• 成果类型: Article; Early Access
• 署名作者: Chu, Liya; Wang, Kent; Zhang, Bohui; Zhou, Guofu
• 署名单位: Xi'an Jiaotong University; The Chinese University of Hong Kong, Shenzhen; The Chinese University of Hong Kong, Shenzhen; Washington University (WUSTL)
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2024.07169
• 发表日期: 2026
• 关键词: esg; Return predictability; partial least square; Neural Networks; model complexity

摘要

We study the relation between firms' environmental, social, and governance (ESG) performance and the aggregate stock market returns. Based on 38 individual ESG measures, we construct a market-level ESG index. With both the traditional predictive regression approach and two recently developed machine-learning methods, we find that the ESG index has strong and positive predictive power on the market both in-and out-of-sample, and both the cash flow and discount rate channels are the economic drivers of predictability. Our results are robust to a number of controls and set-ups. Our novel finding on the significant market-wide impact of the ESG provides support for the economy-wide importance of the ESG risk and for the central role played by governments.