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Environmental sustainability and stock returns

Author

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

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.

Suggested Citation

  • Brown, William O. & Gao, Xiaoli & Han, Yufeng & Huang, Dayong & Wang, Fang, 2026. "Environmental sustainability and stock returns," Journal of Financial Markets, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:finmar:v:79:y:2026:i:c:s1386418125000461
    DOI: 10.1016/j.finmar.2025.101006
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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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