Essays on Institutional Investors

Abstract

This dissertation comprises two self-contained essays on institutional investors. The first essay focuses on analyzing performance persistence of private equity funds, and the second essay establishes the connection between mutual funds' tracking errors and the magnitude of flow-induced trading.

In Chapter 1, I develop a learning model with managers' reputation concerns to shed new light on performance persistence for private equity (PE) funds. The model predicts: When the exogenous shock on fund performance is less volatile, performance persistence is more pronounced, the reputation mechanism works better, and fund managers have more incentive to control fund sizes. On the premise that buyout funds are subject to less volatile shocks than venture capital (VC) funds, I establish the hypothesis that the model mechanism is stronger among buyout funds. Using a comprehensive dataset of PE funds, I document evidence consistent with the hypothesis: (i) While buyout funds exhibit strong long-term (over ten years) performance persistence across different funds raised by the same manager, VC funds show weak short-run persistence. (ii) The size of a buyout manager's new fund is strongly related to the performance of his previous funds, whereas the size of a VC manager's new fund is highly associated with recent VC industry performance rather than the individual manager's. (iii) Top buyout managers raise smaller funds than they could have, while no such pattern is found for VC managers.

In Chapter 2, I propose and test that mutual funds' tracking errors measure the magnitude of flow-induced trading. Mutual funds tend to expand existing winning positions with capital inflows and liquidate losing positions to meet outflows. Such flow-induced trading behavior creates price pressures on stocks held by mutual funds, and leads to a pronounced momentum-reversal return pattern for mutual funds with high tracking errors: Funds in the top return quintile yield a benchmark-adjusted cumulative return of 12.68% in three years after the ranking period, whereas funds in the bottom return quintile yield a cumulative return of 5.98%. No such reversal pattern is detected among funds with low tracking errors. Further evidence reveals a dramatic change in mutual fund investors' behavior that is consistent with my finding: they no longer enthusiastically chase past winners with high tracking errors, and exhibit increasing interests in past losing funds with high tracking errors, suggesting at least some sophisticated investors have become aware of the strong return reversal pattern of high-tracking-error funds, and bet against their recent performance to make significant profits.