dc.contributor.author | Miri, Farhad | |
dc.date.accessioned | 2014-12-15T11:40:06Z | |
dc.date.available | 2014-12-15T11:40:06Z | |
dc.date.issued | 2014-12-15 | |
dc.identifier.uri | http://hdl.handle.net/2077/37769 | |
dc.description.abstract | This thesis investigates and compares the relationship between the inflow of new investment into open-end equity U.S. mutual funds and their historical performance among the top performer funds. Using a piecewise linear regression and applying the Fama and MacBeth (1973) two stages estimation method on the fund data over the period between January 2004 and December 2014, it was found that the level of convexity within top performer is more extreme than what is usually observed as a convexity in the flow-performance relation among the whole industry players. The difference is irrespective of the performance measurement and is both statistically and economically significant. The results obtained suggest that the competition among the mutual funds is not just about being better than average but is rather about winning the “competition”. Fund managers can achieve marked additional inflow related to their peers by securing their position among top 10% of the industry in terms of performance. A positive significant relation between Morningstar rating and fund flow, was also documented. | sv |
dc.language.iso | eng | sv |
dc.relation.ispartofseries | Master Degree Project | sv |
dc.relation.ispartofseries | 2014:117 | sv |
dc.subject | Mutual Funds | sv |
dc.subject | Flow-Performance relationship | sv |
dc.subject | Convexity | sv |
dc.subject | Competition | sv |
dc.subject | Morning Star | sv |
dc.subject | Panel Data | sv |
dc.subject | Piecewise linear regression | sv |
dc.title | Competition in the American Mutual Fund Industry. An empirical study | sv |
dc.type | Text | |
dc.setspec.uppsok | SocialBehaviourLaw | |
dc.type.uppsok | H2 | |
dc.contributor.department | University of Gothenburg/Graduate School | eng |
dc.contributor.department | Göteborgs universitet/Graduate School | swe |
dc.type.degree | Master 2-years | |