We employ several machine learning models to analyze the returns of millions of retail investors in India. Neural networks outperform other machine learning models and OLS in uniquely predicting both good and bad out-of-sample performance. Behavioral biases exert a more important influence on returns than holding-weighted firm characteristics.

Contrary to the view that green investors accept lower returns for sustainable investment, our account-level data from a major Indian bank show the opposite: investors with greener portfolios achieve superior risk-adjusted returns. We hypothesize, and empirically verify, that green investments help investors mitigate detrimental behavioral biases such as the disposition effect and under-diversification. Alternative mechanisms related to stock selection ability, aggregate demand shocks, and risk mitigation do not explain the findings.

This study examines the local economic impacts of the opioid epidemic by focusing on commercial real estate loan performance. Leveraging exogenous variation in physicians per capita and staggered adoption of opioid-misuse prevention legislation, we find that opioid abuse decreases net operating income and increases vacancy rates, leading to a rise in loan defaults. We provide evidence that opioid abuse disrupts local economies through reduced business sales and lower neighborhood desirability.

We analyze how an information and communication technology shock resolves information frictions in a major consumer credit market. Using granular spatial variation in broadband diffusion, we find that high-speed internet access enables consumers to save an average of 327 to 738 dollars on mortgage broker fees. The effect is more pronounced for well-educated, high-FICO, and high-income customers, and in areas with a more competitive broker market ex ante. Greater bargaining power and lower search costs appear to be the main mechanisms.

This study examines the impact of geopolitical risk exposure on the cost of capital faced by U.S.-listed multinational companies. We find that firms with subsidiaries more exposed to geopolitical risk face higher bank loan costs. The result is robust across alternative specifications and measures, and holds under identification strategies based on a Bartik-style instrument and differences-in-differences around the 2014 and 2022 Russia-Ukraine conflicts. Operational flexibility and currency risk help explain the findings.

We propose a novel stock-level measure of the tightness of margin constraints by decomposing a stock's cash-collateral requests in the short-selling market into two components: co-movements with the market and idiosyncratic movements. Consistent with the notion that co-collateral tightens margin requirements, we find that co-collateral reduces short-selling activity and is associated with a positive return premium. The premium peaks during crisis periods and is unexplained by traditional asset-pricing factors or simple mispricing stories.