- Forthcoming, Management Science

Abstract: Cyber risk is an important, emerging source of risk in the economy. To estimate its impact on the asset market, we use machine learning techniques to develop a firm-level measure of cyber risk. The measure aggregates information from a rich set of firm characteristics and shows superior ability to forecast future cyberattacks on individual firms. We find that firms with higher cyber risk earn higher average stock returns. When these firms underperform, cybersecurity experts tend to have higher concerns about cyber risk, and cybersecurity exchange-traded funds outperform. Further tests strengthen the identification of the cyber risk premium.


Abstract: Have retail investors become the ants that move the log? Social media has proved instrumental for effective coordination that might lead to extreme returns. To study this issue, I construct a novel crash risk measure by estimating ex-ante crash probabilities via logit and machine learning techniques. Stocks with high ex-ante crash risk tend to have lower returns, especially when lagged sentiment is high. Robinhood traders tend to over-buy high crash-risk stocks, consistent with the optimal expectations theory (Brunnermeier et al., 2007). By exploiting the staggered first appearances of ticker names on “Wallstreetbets”, I document a possible causal effect of correlated retail attention on crash risk. This effect is significantly more substantial for smaller stocks. To further bolster the finding, I exploit the entire history of Reddit to construct a novel instrument and show that social transmission is likely to cause elevated crash risk.  

Abstract: Social capital refers to “networks, norms, and trust that facilitate action and cooperation for mutual benefit” (Putnam, 1995). We propose a novel firm-level time-varying social capital measure based on firms’ 10-K filings that captures the firm’s operational exposure to social capital and examine its impact on equity prices. This measure is positively and significantly correlated with future returns, above and beyond the effects of governance indices. A zero-cost portfolio that is long in high and short in low social-capital firms earns a risk-adjusted annual return of 6.41%, with a T-statistic over. 3. Investors do not fully incorporate the benefits of a firm’s exposure to social capital in equity prices. Firms with greater exposure to high social capital regions are more likely to have positive earnings surprises and are associated with higher post-earnings announcement drifts. Our results are robust to using newer measures of social capital (Chetty et al., 2022a,b).