Summary of Project Plan

In classical models of information in asset markets, people learn from others only indirectly by observing market prices or quantities observed in markets. There is growing evidence that more direct forms of social interaction, such as conversation, also affect the decisions of economic agents. An open question is whether and how social interactions improve market efficiency.

Models of rational learning with social information transmission suggest that social interactions improve market efficiency. However, social interactions can also create free-riding incentives that discourage private information production. Furthermore, in models with imperfectly rational investors, social interactions can propagate incorrect beliefs or naive trading strategies, reducing information efficiency.

I plan to provide insight into these important questions by using a novel dataset of Facebook social connections. Given Facebook’s scale and the relative representativeness of its user body, the data provide a comprehensive measure of the geographic structure of social networks. Specifically, I am interested in the following questions. How do social networks affect the diffusion of information, price reactions, and investors' trading behaviors? What’s the relationship between a firm’s geographic locations in the social network and its valuation? Do social connections affect capital allocation in crowdfunding marketplaces? To what extent do social ties across regions where firms are located reveal a new dimension of these firms' fundamental comovements that previous studies have not identified? Do social interactions facilitate the spillover of innovation and the propagation of technology shocks across firms?

To address these questions, I plan to employ a rich set of data that include regional demographic and socioeconomic indicators, information from corporate balance sheets, financial market indicators, detailed trading records of stocks, as well as data from social network platforms and internet search engines. Through carefully designed empirical analysis, my research attempts to improve our understanding of social networks' role in economics and financial markets. The research also aims to provide policy implications regarding market designs that harvest social networks' power and promote allocation efficiency.

The proposed project aligns well with the statutory goals of the Keynes Fund in that it will shed light into the important question of how social networks contribute to “sources and consequences of failure of market efficiency,” and in particular, “capital market mispricing.” The proposed project will also speak to the “interactions between the financial markets and the real economy,” and therefore has the potential to “extend the frontiers of traditional economics.”

Media

An article related to this research was published in the Financial Times on December 9, 2021: 'Meme Mania is Reshaping US Markets'. Professor Peng worked through a vast digital database of stock trading flows and social media networks to study the phenomena of “lottery stocks”.