Three Essays in Institutional Trading and Corporate Finance
My dissertation is comprised of three chapters. In this first chapter, I study the effect of social connections on mutual fund investors' information production and accuracy of their signals. While connected investors have access to information in their social network (information diffusion effect), social connections also reduce their incentives to acquire costly information, since they can free ride on connected peers ("free riding on friends" effect). I find this negative "free riding on friends" effect of social connections dominates information diffusion effect in the mutual fund industry, using fund managers' connections built upon their prior career experiences. First, I find that connected funds are more likely to hold the same stocks and to trade in the same direction, relative to unconnected funds. Second, I find that funds with lower network centrality earn higher alphas, even after controlling for other fund and manager characteristics. A one-standard-deviation increase in eigenvector centrality predicts a decrease of 29-37 basis points in annualized fund alphas. Third, when I define a stock-level variable PMC (Peripheral minus Central) as the difference in average portfolio weights between peripheral funds and central funds, I find that stocks with higher PMC have significantly higher abnormal stock returns. A one-standard-deviation increase in PMC predicts an increase of 1.48%-1.52% in the next quarter risk-adjusted returns (annualized). Finally, I find that PMC predicts firms' future earnings surprises. In the second chapter, co-authored with Thomas Chemmanur, Yingzhen Li, and Jie Xie, we propose a "noisy signaling" hypotheses of open market share repurchase (OMSR) programs, where the equity market equilibrium that prevails after OMSR program announcements is a partial pooling rather than a fully separating equilibrium. We argue that two complementary mechanisms, namely, actual share repurchases by firms and information production by institutions, serve to reduce the residual equity market information asymmetry facing firms subsequent to OMSR program announcements. We test the implications of this noisy signaling hypothesis using transaction-level data on trading by institutions and by a subsample of identified hedge funds, and find strong support for the above hypothesis. In the third chapter, co-authored with Thomas Chemmanur, and Jiekun Huang, we analyze how the geographical locations of institutions affect their investments in IPOs and various characteristics of the IPOs that they invest in. We argue that institutions geographically close to each other may free-ride on each other's information when evaluating IPOs, resulting in IPOs dominated by geographically clustered institutions reflecting less accurate information signals compared to those dominated by geographically dispersed institutions. We find that the equity holdings of institutions in IPOs are influenced more by the investments made by neighboring institutions. We show that an increase in the geographical dispersion of the institutions investing in an IPO is associated with higher IPO price revisions, higher firm valuations at offering and secondary market, larger IPO initial returns, greater long-run post-IPO stock returns lower information asymmetry facing an IPO firm in the equity market. Finally, the predictive power of institutional trading post-IPO for subsequent long-run stock returns and earnings surprises for the first fiscal-year end after the IPO is greater for geographically isolated institutions compared to those that are geographically clustered.