We study the relationship between the behavior of a CEO’s ancestors and firm performance. To do so, we collect detailed information on emigrants from Italian municipalities during the Age of Mass Migration (1892–1924) from Ellis Island ships lists. We adopt an epidemiological approach complemented with an instrumental variables strategy and find that Italian firms managed by a CEO who belongs to a family with past emigration experience tend to perform better and to be more productive. In line with an inter-generational transmission of attitudes hypothesis, we show a positive relationship between the emigration experience of a CEO’s ancestors and alternative measures of corporate risk-taking. In addition, we find a positive relationship between having an ancestor who emigrated during the Age of Mass Migration and FDI to the United States. We also provide evidence that these CEOs have better managerial practices.

In this paper, we use ChatGPT outages to provide early evidence on whether investors rely on generative artificial intelligence (GenAI) to perform professional tasks and the associated impact on stock price informativeness. We document a significant decline in stock trading volume during ChatGPT outages. The effect is stronger for firms with corporate news released immediately before or during the outages and for firms with higher ownership held by transient institutional investors. We then document declines in short-run price impact and return variance during the outage periods, consistent with reduced informed trading. Lastly, we document a positive effect of GenAI-assisted trading on long-run stock price informativeness. Overall, our findings indicate that a significant number of investors use ChatGPT in ways that influence their trading decisions and market outcomes. Future research can investigate the mechanisms underlying these GenAI effects and the potential risks of using GenAI for trading.

With the recent evolution of the cryptocurrency market, financial misconduct has become a major concern. Using on-chain data from the 500 most traded NFT (non-fungible token) collections, this study investigates wash trading in NFT markets. We first detect suspicious wash trades that form closed loops and then validate the prices of these trades using Benford’s Law. Excluding token-incentivized wash trades, we propose a conceptual model and argue that collusion between wash traders and insiders is the primary motivation of wash trading. Empirical analysis reveals that insiders tend to sell during or shortly after wash trading. This manipulation creates a pump-and-dump effect, causing losses for buyers during the pump phase. Our research reveals the underlying mechanisms of such misconduct and highlights the need for regulation in the cryptocurrency market.

This study examines the effects of firms' green innovation on their future financial and environmental performance. If pollution is primarily a manifestation of wasted resources, then investments in pollution prevention technologies can both reduce the environmental impact of production and improve financial performance. In contrast, investments in pollution control technologies likely reduce the environmental impact of production without improving financial performance. Using green patents to capture firms' investments in these two types of technologies, we find that the value of a firm's pollution prevention patents is positively associated with its future financial and environmental performance, and that the positive impact on future financial performance is achieved through improvements in sales growth and cost efficiency. In contrast, the value of a firm's pollution control patents is not associated with its future financial or environmental performance. Overall, these findings shed light on the future implications of green innovation.

Using high-frequency data on over 7 million import transactions, we study the disruptions to U.S. firms’ trade patterns and growth immediately following the initial COVID-19 trade shock. While large firms were not direct recipients of government fiscal support, they experienced fewer disruptions when located in counties where small businesses (SMEs) received government stimulus loans under the Paycheck Protection Program. These effects were largest in counties with greater share of SMEs and stronger input–output linkages between large firms and SMEs. Our results point to local spillovers between SMEs and large firms as being an important determinant of firm resiliency during crises.

This paper examines how the departure of star analysts influences the performance of their non-star peers. Using manually collected data from China, we observe that non-star analysts enhance their forecast accuracy after a star analyst leaves. This effect is particularly pronounced when non-star analysts have previously worked within hierarchical teams or when the departing star analyst held significant internal resources within the brokerage. Additionally, the performance improvements are more substantial in environments with greater promotion opportunities and in brokerages characterized by a collective organizational culture. To establish causality, we leverage the suspension and subsequent reform of the star analyst voting system as an exogenous shock. A difference-in-difference (DID) analysis demonstrates that brokerages more affected by this shock exhibit larger improvements in analyst forecast accuracy. These findings offer new insights into the celebrity effect, highlighting how changes in team structure and internal competition influence analyst performance.

A few highly successful firms (“superstar firms”) have captured large market shares and earned massive profits in recent decades. We examine whether superstar firms are associated with a greater likelihood of financial distress for firms exposed to them in product markets. Building on recent research, we identify superstars as firms with the highest markups in the industry and whose industry markup share increases over time. We then measure, with product similarity scores, a firm’s overall product market exposure to superstars. We document that firms with greater exposure are more likely to file for bankruptcy. We examine why superstar exposure is associated with bankruptcy and show that firms with the greater superstar exposure exhibit weaker financial performance and greater riskiness. Furthermore, we show that the association between superstar exposure and the likelihood of bankruptcy strengthens when superstars have greater market power.

While prior studies have examined whether financial analysts affect corporate innovation, there is little research on the mechanism through which this occurs. In this paper, we examine whether and how analysts' questions about innovation during site visits affect corporate innovation. Using a sample of corporate site visits in China, we find that when analysts ask questions about innovation during site visits, firms invest more in R&D in the future. Consistent with knowledge diffusion across firms, this association is stronger when analysts cover more firms in the same industry, when firms share similar technologies as industry peers, and when an innovation‐expert analyst is present at site visits. We also find that analysts' questions about innovation during site visits are positively associated with the quantity and quality of firms' patent applications in the future. Overall, we provide evidence that analysts can affect corporate innovation through their questions about firms' innovation activities.

Narcissism is a multifaceted personality trait that profoundly influences individuals' cognition, emotions, and actions. This study investigates the relationship between narcissistic CEOs and their engagement in opportunistic insider trading. Utilizing a quantitative measure of CEOs' narcissism derived from textual analysis, we find that CEOs with a higher level of narcissism engage in opportunistic insider trading more intensely. To mitigate endogeneity concerns, we employ various rigorous approaches, including matching, instrumental variable, Heckman's two-step sample selection model, and falsification tests. Through cross-sectional analysis, we find that the impact of CEOs' narcissism on opportunistic insider trading is more pronounced among CEOs with limited legal knowledge, facing weaker external and internal monitoring pressure, working at larger firms, and being male. In addition, we demonstrate that the insider trades of narcissistic CEOs are less profitable and less informative than those of non-narcissistic CEOs, as evidenced by subsequent stock performance.