My dissertation consists of two essays on mutual funds. The first essay examines the role of extreme positive returns on future fund flows using maximum style-adjusted daily returns (hereafter MAX) over the previous month. My results suggest that there is a positive and significant relation between MAX and future fund flows. The results are robust to controls for fund performance, fund size, age, turnover, fund fees, volatility, and skewness of fund returns. Of particular interest, this relation exits only in retail funds. Moreover, MAX is persistent from one month to the next, but MAX-based investment strategies are associated with lower risk-adjusted returns than investors could have achieved in otherwise similar funds. Overall, my analysis suggests that mutual fund investors are attracted to maximum style-adjusted daily returns, which is in line with the theoretical argument that investors exhibit a preference for lottery-like payoffs. These investors are successful in achieving a lottery-like return profile, but this strategy is costly in terms of expected returns
The second essay studies the effect of recent and long-term mutual fund performance on future fund flows. I document that investors' response to recent performance depends on average long-term performance. In particular, a recent loser fund experiences outflows only if its longer-term performance is also poor. Similarly, recent good performance leads to more inflows only if the fund has also good long-run performance. In contrast, investors ignore recent performance if it provides a signal that conflicts with the longer-term signal. This implies that good fund managers with a longer-term focus will find it easier to attract future inflows than managers with a short-term horizon.
| Identifer | oai:union.ndltd.org:uoregon.edu/oai:scholarsbank.uoregon.edu:1794/12455 |
| Date | January 2012 |
| Creators | Genc, Egemen, Genc, Egemen |
| Contributors | Boehmer, Ekkehart |
| Publisher | University of Oregon |
| Source Sets | University of Oregon |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Rights | All Rights Reserved. |
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