Granular Environmental Variables and Stock Returns

Individual environmental variables may contain information obscured in aggregate environmental scores for return forecasting. We apply machine learning methods to granular environmental variables and find that a long-short portfolio that longs stocks with high forecasted returns and sells stocks with low forecasted returns earns about one percent per month. Stocks with high forecasted returns are associated with strong environmental operational performance. Variables related to Scope 3 emissions are neglected risks. The long-short portfolio performs better when climate concerns in the media are more intense