Published Papers

Fraud indicators in the Paycheck Protection Program (PPP) COVID relief program are highly geographically concentrated. Zip codes and counties with high rates of suspicious PPP loans exhibit strong social connections to one another with evidence of fraud spreading spatially over time through social connections. Individuals in suspicious social media groups have higher rates of PPP fraud, and socially connected zip codes frequently use the same specific FinTech lenders, consistent with social connections influencing particular loan decisions. Our findings suggest that more proactive data analysis in fraud prevention, detection, and prosecution is needed to prevent the social spread of fraudulent schemes.

Can social norms give rise to distorted information in China? We observe that China's leading social norm related to alcohol consumption and social drinking enhance earnings management. An analysis of toxic alcohol scandals supports a causal interpretation. Further evidence suggests that the influence of alcohol may come from the negative externality that it creates, which is propagated by corporate leaders and cannot be attenuated by market-oriented institutions. Our results reveal a social norm externality that may have important normative implications.

As emerging FinTech platforms face pressure in efficiently managing credit risk, the human emotional spectrum of FinTech platform borrowers within social media becomes a potential source for gaining insight into and evaluating their financial behaviors. Collaborating with an Asian FinTech platform, we investigate the impact of social media emotions on a platform's loan-approval decisions and repayment-reminder interventions before due dates. We demonstrate that anger at the pre-approval stage has a U-shaped relationship with platform borrowers' default probability. We reveal what we call "a bright side of anger" with respect to curbing financial credit risk: moderate intensity of anger at the pre-approval stage suggests a lower loan default probability. We also find that the average happiness tendency of platform delinquent borrowers' at the pre-maturity stage becomes informative and valuable, as it shows a U-shaped relationship with loan default; as for anger, it does not work therein. Furthermore, our field experiment indicates that a positive-expectation reminder is useful for prompting repayment when delinquent borrowers are in strong emotional intensities, regardless of anger or happiness. However, a negative-consequence reminder results in a higher default probability for delinquent borrowers who maintain high immediate happiness before the loan maturity dates. We draw on the classical appraisal theory of emotions and the feelings-as-information theory to interpret our findings. We offer non-trivial theoretical and practical implications to support FinTech platform credit risk decision-making by investigating the value of social media emotions and advocating for cross-functional coordination between debt approval and debt collection departments.

We measure popular sentiment toward finance by applying a large language model to millions of books published in eight countries over hundreds of years. We extensively validate this measure both internally and externally. We document persistent differences in finance sentiment across countries despite ample time-series variation. Books written in the languages of more capitalist countries discuss finance in a more positive context. Finance sentiment is correlated with survey-based measures of financial market participation and income inequality. Finance sentiment declines one year before rather than after financial crises. Positive shocks to finance sentiment are followed by higher output and credit growth.

Using a semisupervised topic model on 7 million New York Times articles spanning 160 years, we test whether topics of media discourse predict future stock market excess returns to test rational and behavioral hypotheses about market valuation of disaster risk. Media discourse data address the challenge of sample size even when disasters are rare. Our methodology avoids look-ahead bias and addresses semantic shifts. Our discourse topics positively predicts market excess returns, with War having an out-of-sample R^2 of 1.35%. We call this effect the war return premium. The war return premium has increased in more recent time periods.

We identify the crucial role social networks play in crowdfunding markets. Investors are 50% more likely to fund projects that their peers support and are 11.2% more likely to fund projects from regions where they share strong social ties, given a one-standard-deviation change in the variables. More influential peers exert a greater influence, especially in the case of riskier projects, and the peer effects are amplified in crowdfunding platforms that prioritize transparency and accountability. Social ties transmit information about economic conditions in project locations, and they complement the influence of peer effects. Furthermore, the social network effects affect project funding outcomes and can be particularly valuable in mitigating the adverse effects of natural disasters. Our findings suggest that social networks play a significant role in crowdfunding markets by increasing investor awareness, disseminating information, and ultimately influencing capital allocations.

We review an empirical literature that studies how political polarization affects financial decisions. We first discuss the degree of partisan segregation in finance and corporate America, the mechanisms through which partisanship may influence financial decisions, and available data sources to infer individuals' partisan leanings. We then describe and discuss the empirical evidence. Our review suggests an economically large and often growing partisan gap in the financial decisions of households, corporate executives, and financial intermediaries. Partisan alignment between individuals explains team and financial relationship formation, with initial evidence suggesting that high levels of partisan homogeneity may be associated with economic costs. We conclude by proposing several promising directions for future research.

This paper examines how beliefs and preferences drive identity-conforming consumption or investments. We introduce a theory that explains how identity distorts individuals' beliefs about potential outcomes and imposes psychic costs on benefiting from identity- incongruent sources. We substantiate our theoretical foundation through two lab-in- field experiments on soccer betting in Kenya and the UK, where participants either had established affiliations with the teams involved or assumed a neutral stance. The results indicate that soccer fans have overoptimistic beliefs about match outcomes that align with their identity and bet significantly higher amounts on those than on outcomes of comparable games where they are neutral. After accounting for individuals' beliefs and risk preferences, our structural estimates reveal that participants undervalue gains from identity-incongruent assets by 9% to 27%. Our counterfactual simulations imply that identity-specific beliefs account for 30% to 44% of the investment differences between neutral observers and supporters, with the remainder being due to identity preferences.

We investigate the impact of peer interaction on the quality of financial decision making in a laboratory experiment. Face-to-face communication with a randomly assigned peer significantly improves the quality of subsequent private decisions even though simple mimicry would have the opposite effect. We present evidence that the mechanism involves general conceptual learning (because the benefits of communication extend to previously unseen tasks), and that the most effective learning relationships are horizontal rather than vertical (because people with weak skills benefit most when their partners also have weak skills). The benefits of demonstrably effective financial education do not propagate to peers.

We examine the contagion of investment ideas in a multiperiod setting in which investors are more likely to transmit their ideas to other investors after experiencing higher payoffs in one of two investment styles with different return distributions. We show that heterogeneous investment styles are able to coexist in the long run, implying a greater diversity than predicted by traditional theory. We characterize the survival and popularity of styles in relation to the distribution of security returns. In addition, we demonstrate that psychological effects such as conformist preference can lead to oscillations and bubbles in the choice of style. These results remain robust under a wide class of replication rules and endogenous returns. They offer empirically testable predictions, and provide new insights into the persistence of the wide range of investment strategies used by individual investors, hedge funds, and other professional portfolio managers.

We examine an undercover Securities and Exchange Commission (SEC) investigation into the manipulation of financial news on social media. While fraudulent news had a direct positive impact on retail trading and prices, revelation of the fraud by the SEC announcement resulted in significantly lower retail trading volume on all news, including legitimate news, on these platforms. For small firms, volume declined by 23.5% and price volatility dropped by 1.3%. We find evidence consistent with concerns of fraud causing the decline in trading activity and price volatility, which we interpret through the lens of social capital, and attempt to rule out alternative explanations. The results highlight the indirect consequences of fraud and its spillover effects that reduce the social network's impact on information dissemination, especially for small, opaque firms.

After the run on Silicon Valley Bank (SVB) in March 2023, U.S. regional banks entered a period of significant distress. We quantify social media's role in this distress using comprehensive Twitter data. During the SVB run period, banks with high pre-existing exposure to Twitter lost 4.3 percentage points more stock market value. Moreover, Twitter pre-exposure interacts significantly with classical run risks to predict greater run severity and greater deposit outflows during Q1-2023, effects unexplained by other banking or market characteristics. At the hourly frequency during the run, high Twitter attention over the past four hours predicts stock market losses, especially for banks with high run risks. By contrast, we find that negative Twitter sentiment does not amplify bank run risks. Rather, our evidence points to a distinctive role of Twitter attention, particularly when tweets are retweeted broadly.