We investigate the cross-sectional pricing of the exposure to pollution news for individual stocks. We employ the Latent Dirichlet Allocation (LDA) model to quantify the news coverage of environment-related news in the New York Times from 1980 to 2023. Using the news coverage of environmental-related time series, we estimate betas with respect to the latter and study the pricing in the cross-section of stock returns. We find that stocks in the highest pollution news beta quintile earn significantly higher stock returns than those in the lowest quintile. This outperformance survives risk-adjustment. In contrast, betas with respect to the other environment-related topics are not consistently priced. Consistent with intuition, we find that the relationship of pollution news and stock returns depends on the level of media sentiment. We find a significantly positive pollution news premium only when the news sentiment is sufficiently high.
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Budras et al. (2026) studied this question.
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