Working Papers

The recent meme stock saga has drawn attention to the growing role of social networks in capital markets. In this paper, the authors summarize the latest research that uses large scale, representative, real-world social network data to study social networks' influences on trading, liquidity, and valuations of stocks. Institutional investors invest more heavily in stocks if there are strong social ties between the geographic locations of the institution's headquarters and the firm's headquarters. Further, a firm's social ties to large institutional investors reduce its cost of capital, increase its valuation, and strengthen its liquidity. Social networks help to timely disseminate important news releases into prices, but also trigger belief divergence and generate persistent excess trading. Moreover, social interactions can amplify investors' behavioral biases and contribute to retail investors' attraction to lottery-type stocks. The authors provide additional examples to further illustrate why the roles of social networks are of particular importance to market participants.

The recent meme stock saga has drawn attention to the growing role of social networks in capital markets. In this paper, the authors summarize the latest research that uses large scale, representative, real-world social network data to study social networks' influences on trading, liquidity, and valuations of stocks. Institutional investors invest more heavily in stocks if there are strong social ties between the geographic locations of the institution's headquarters and the firm's headquarters. Further, a firm's social ties to large institutional investors reduce its cost of capital, increase its valuation, and strengthen its liquidity. Social networks help to timely disseminate important news releases into prices, but also trigger belief divergence and generate persistent excess trading. Moreover, social interactions can amplify investors' behavioral biases and contribute to retail investors' attraction to lottery-type stocks. The authors provide additional examples to further illustrate why the roles of social networks are of particular importance to market participants.

We identify the crucial role social networks play in crowdfunding markets. Investors are 50% more likely to fund projects that their social network peers support and are 11.2% more likely to fund projects from regions to which they have strong social ties, given a one standard deviation change in the variables. Peer effects complement platform design choices and the effect of social ties, and social ties transmit information about economic conditions in project locations. Further, the investor-level effects aggregate and affect project funding successes. Our findings suggest that social networks increase investor awareness, disseminate information, and have real impacts on capital allocations.

Using social network data from Facebook, we show that earnings announcements made by firms located in counties with higher investor social network centrality attract more attention from both retail and institutional investors. For such firms, the immediate price and volume reactions to earnings announcements are stronger, and post-announcement drift is weaker. Such firms have lower post-announcement persistence of return volatility but higher persistence in investor attention and trading volume. These effects are stronger for small firms, firms with poor analyst and media coverage, and for stocks with salient returns. Our evidence suggests a dual role of social networks-they facilitate the incorporation of public information into prices, but also trigger persistent excessive trading.

Political science research finds that individuals exhibit partisan bias, which results in unduly favorable economic expectations when their partisanship aligns with that of the US president. We examine whether partisan bias is present in management earnings forecasts, where CEOs have strong incentives to provide high-quality forecasts. We find that firms with CEOs whose partisanship aligns with that of the US president issue more optimistically biased management earnings forecasts than CEOs whose partisanship is unknown or not aligned with that of the US president. Our results suggest that CEOs fall prey to partisan bias, which results in suboptimal forecasting behavior. In cross-sectional analyses, we find that this forecast over-optimism is attenuated when CEOs are of higher ability. Additionally, we find that investors fail to discount the news in forecasts issued by CEOs whose partisanship aligns with that of the US president and that post-forecast abnormal returns are lower for these firms.

Social networks are associated with the demand for and supply of consumer and small business loans originated on lending marketplaces. Loan demand increases substantially with past borrowing activities of geographically distant but socially connected areas, with an elasticity of 0.21. Borrower-area social proximity to deposits increases funding likelihood by 5.61% and improves ex-post loan performance. We establish causality with granular instrumental variables obtained from natural disasters (demand-side) and financial adviser misconduct (supply-side). The results suggest social networks improve capital allocation by increasing the awareness of alternative lending platforms and facilitating the transmission of less accessible information complementary to loan-specific data.

While a rapidly growing body of research underscores the influence of social capital on financial decisions and economic developments, objective data-based measurements of social capital are lacking. We introduce average credit scores as an indicator of a community's social capital and present evidence that this measure is consistent with, but richer and more robust than, those used in the existing literature, such as electoral participation, blood donations, and survey-based measures. Merging unique proprietary credit score data with two nationwide representative household surveys, we show that households residing in communities with higher social capital are more likely to invest in stocks, even after controlling for a rich set of socioeconomic, preferential, neighborhood, and demographic characteristics. Notably, such a relationship is robustly observed only when social capital is measured using community average credit scores. Consistent with the notion that social capital and trust promote stock investment, we find the following: first, the association between average credit score and stock ownership is more pronounced among the lower educated; second, social capital levels of the county where one grew up appear to have a lasting influence on future stock investment; and third, investors who did not own stocks before have a greater chance of entering the stock market a few years after they relocate to higher-score communities.

This paper examines how social media informs corporate decisions by studying the decision of firm management to withdraw an announced merger. A standard deviation decline in abnormal social media sentiment following a merger announcement predicts a 0.64 percentage point increase in the likelihood of merger withdrawal (16.6% of the baseline rate). The informativeness of social media for merger withdrawals is not explained by abnormal price reactions or news sentiment. Consistent with learning from external information, we find that the social media signal is more informative after a firm adopts a corporate Twitter account, which offers a conduit for listening to investor feedback. In addition, most of the informativeness is driven by investors who reference fundamental information, not price trends, and is driven by longer tweets that likely contain investment analysis. The social media signal is also more informative for complex mergers in which analyst conference calls take a negative tone, driven by the Q&A portion of the call. Overall, these findings imply that social media is not a sideshow, but an important aspect of firm information environment.

Folklore is the collection of traditional beliefs, customs, and stories of a community passed through the generations by word of mouth. We introduce to economics a unique catalogue of oral traditions spanning approximately 1,000 societies. After validating the catalogue’s content by showing that the groups’ motifs reflect known geographic and social attributes, we present two sets of applications. First, we illustrate how to fill in the gaps and expand upon a group’s ethnographic record, focusing on political complexity, high gods, and trade. Second, we discuss how machine learning and human-classification methods can help shed light on cultural traits, using gender roles, attitudes towards risk, and trust as examples. Societies with tales portraying men as dominant and women as submissive tend to relegate their women to subordinate positions in their communities, both historically and today. More risk-averse and less entrepreneurial people grew up listening to stories where competitions and challenges are more likely to be harmful than beneficial. Communities with low tolerance towards antisocial behavior, captured by the prevalence of tricksters getting punished, are more trusting and prosperous today. These patterns hold across groups, countries, and second- generation immigrants. Overall, the results highlight the significance of folklore in cultural economics, calling for additional applications.

This study documents that CEOs’ expectations about firm performance are more negatively biased in periods when the White House is governed by the political party that the CEOs did not contribute to, relative to periods when the White House is occupied by the CEOs’ party. This negative bias holds as strongly toward the end of the year, suggesting that CEOs do not revise their priors in response to new information. The results are stronger for firms whose performance is more correlated with the general economic conditions, consistent with managers’ biased beliefs about the economy driving the results. Upon facing an opposing presidency, the sensitivity of CEOs’ capital investments to cash flow decreases, relative to their politically aligned years. By contrast, actual firm performance is largely unaffected. Overall, our results highlight the importance of political partisan bias in shaping managers’ expectations about firm performance.

We ask how social media impacts the role of short sellers in financial markets. We find some evidence consistent with manipulation. Prior to high short interest, a stock's social media tone is abnormally positive, but its traditional media tone is not. Once highly shorted, social media tone flips and is abnormally negative. Using the firm-by-firm introduction and temporary suspension of short selling in China as natural experiments, we find that both the volatility of social media tone and the number of posts increase when a firm becomes shortable, and then decrease when shorting was suspended. Highly shorted firms with pump-and-dump social media patterns also have pump-and-dump stock return patterns and abnormally high trading volume. Manipulative social media tone is more likely when there are more posts from active social media users, who are perhaps better able to influence other users. Our findings are consistent with the idea that social networks and social media can enable manipulation.

This study documents that CEOs' expectations about firm performance are more negatively biased in periods when the White House is governed by the political party that the CEOs did not contribute to, relative to periods when the White House is occupied by the CEOs' party. This negative bias holds as strongly toward the end of the year, suggesting that CEOs do not revise their priors in response to new information. The results are stronger for firms whose performance is more correlated with the general economic conditions, consistent with managers' biased beliefs about the economy driving the results. Upon facing an opposing presidency, the sensitivity of CEOs' capital investments to cash flow decreases, relative to their politically aligned years. By contrast, actual firm performance is largely unaffected. Overall, our results highlight the importance of political partisan bias in shaping