The study aims to verify whether the consideration of a risk measure based on environmental, social, and governance (ESG) factors can reduce the difference between the ex-ante financial risk and ex-post volatility of financial assets. The statistical models are run on 17,996 firm-year observations (3332 active firms from 55 countries and 10 industries, listed on the ECPI Global Ethical Equity index) in 2007–2015. According to our main results, the forecasting effectiveness of traditional financial risk measures can be improved by integrating financial risk with an ESG risk measure that considers the ESG entropy. We found that the dispersion of ESG scores within a country, sector and year is a risk factor that would be helpful in predicting the volatility of financial assets. Other similar long-run risk measures, such as issuers' credit ratings, do not reveal the same forecasting power. By reducing unexpected volatility, especially in the medium term, the ESG risk measure provides investors and fund managers with a useful metric for decision making.

中文翻译：

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通过将金融风险与环境、社会和治理风险相结合来预测波动性

该研究旨在验证考虑基于环境、社会和治理 (ESG) 因素的风险措施是否可以减少金融资产的事前金融风险和事后波动性之间的差异。统计模型基于 2007-2015 年的 17,996 家公司年度观察结果（来自 55 个国家和 10 个行业的 3332 家活跃公司，在 ECPI 全球道德股票指数中列出）。根据我们的主要结果，通过将金融风险与考虑 ESG 熵的 ESG 风险度量相结合，可以提高传统金融风险度量的预测有效性。我们发现，一个国家、行业和年份内 ESG 得分的分散性是一个有助于预测金融资产波动性的风险因素。其他类似的长期风险衡量指标，例如发行人的信用评级，不显示相同的预测能力。通过减少意外波动，尤其是在中期，ESG 风险衡量指标为投资者和基金经理提供了一个有用的决策指标。