Work

Environmental sustainability and stock returns

Year: 2025

Type: article

Abstract: We apply machine learning methods to granular environmental variables and test if there is a strong positive relation between environmental sustainability and future stock returns. A long-short portfolio that longs stocks with high forecasted returns and sells stocks with low forecasted returns earns large abnormal returns, and it performs better when climate concerns in the media are more intense. Further diagnosis shows that various dimensions of environmental sustainability help return predictions. High forecasted returns are associated primarily with strong environmental operational performance. The return prediction based on a customized transformer model is similar.

Source: Journal of Financial Markets

DOI: 10.1016/j.finmar.2025.101006

Authors: William O. Brown, Xiaoli Gao, Yufeng Han, Dayong Huang, Fang Wang

Institutions: University of North Carolina at Greensboro, University of North Carolina at Charlotte, Central Washington University

Language: English

Topic: Sustainable Finance and Green Bonds

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDG: Climate action

Open Access status: hybrid

Estimated APC paid: $2,950