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

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  • Paolo Capelli
  • Federica Ielasi
  • Angeloantonio Russo

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.

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  • Paolo Capelli & Federica Ielasi & Angeloantonio Russo, 2021. "Forecasting volatility by integrating financial risk with environmental, social, and governance risk," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(5), pages 1483-1495, September.
  • Handle: RePEc:wly:corsem:v:28:y:2021:i:5:p:1483-1495
    DOI: 10.1002/csr.2180
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