污染与业绩：投资者在阴天做更糟糕的交易吗？（英）-48页

Summary

Background and Objective

This study investigates the relationship between air pollution and individual investors' stock trading behavior and performance, hypothesizing that air pollution impairs cognitive function, leading to worse trading outcomes. Using account-level equity transaction data from 87,054 households across 34 Chinese cities, matched with air quality index (AQI) data from 2007 to 2014, the research examines this link after controlling for investor-specific and weather-related factors.

Methods

The analysis employs fixed-effects panel regressions with investor-year and date fixed effects to address potential confounders such as investor characteristics and local weather. Abnormal trade performance is measured over holding periods of 20–80 trading days using Fama-French three-factor models. The study assesses nonlinear effects of pollution severity and examines investment biases, including the disposition effect and attention-driven buying. Additional tests include manipulating AQI data and excluding persistent pollution days to ensure robustness.

Key Findings

Air pollution has a negative, monotonic effect on trade performance, with performance decreasing as pollution severity increases. For example, on days with severely polluted air (AQI > 300), abnormal performance is 59.57 basis points lower than on blue-sky days for a 40-trading-day holding period. Air pollution exacerbates investment biases, particularly the disposition effect (tendency to realize gains but avoid losses), and attention-driven buying behavior, leading to poorer performance. Excessive trading shows a modest increase but contributes less to the overall negative impact.

Economic Impact

The incremental underperformance due to air pollution accounts for approximately 6.80% of the average unconditional underperformance. At the national level, estimated annual losses from individual trading on hazy days amount to RMB 17.314 billion.

Robustness

Results remain significant after controlling for weather variables, adjusting for potentially manipulated AQI values, and analyzing persistent pollution scenarios. Excluding trades in local stocks does not alter the findings, suggesting the effect is driven by investors' exposure to local air quality, not firm-specific performance.

Conclusion

Air pollution negatively impacts trading performance through cognitive impairment, fueling behavioral biases. This adds to the literature on environmental economics and highlights the importance of air quality for financial decision-making, with implications for investor education and policy aimed at reducing pollution-related economic costs.