Investor sentiment spillover from air pollution: Cross-industry influences on stock markets

Abstract

This study employs the LASSO machine learning technique for robust causal inference. While air pollution is primarily linked to heavily polluting industries, we identify a pervasive sentiment spillover channel that transmits shocks to seemingly unrelated sectors. This occurs because pollution–induced negative sentiment alters investors’ risk appetite, prompting portfolio adjustments across various industries to express their green preferences. The spillover effects vary among industries due to differing sensitivities to pollution, and the energy sector is particularly impacted. We develop bilateral hedging strategies that incorporate the energy sector alongside other sectors, demonstrating that these strategies can effectively mitigate risks associated with pollution–induced sentiment. This risk mitigation is particularly effective when hedging the energy sector against industries more vulnerable to sentiment. These findings highlight the influence of sentiments related to specific sectors on the broader cross-section of stocks with implications for portfolio management and risk mitigation strategies.