Forecasting volatility by integrating financial risk with environmental, social, and governance risk

TLDR

The study tests whether incorporating an ESG‑based risk measure narrows the gap between ex‑ante financial risk and realized asset volatility. The authors estimate statistical models on 17,996 firm‑year observations from 3,332 active firms across 55 countries and 10 industries listed on the ECPI Global Ethical Equity index during 2007–2015. Adding ESG risk—especially ESG entropy and dispersion across country, sector, and year—enhances volatility forecasting, outperforming traditional financial risk measures and credit ratings, and reducing medium‑term unexpected volatility.

Abstract

Abstract 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.