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An examination of the factors influencing mutual fund performance

Sherman, Meadhbh (2012). An examination of the factors influencing mutual fund performance. (Unpublished Doctoral thesis, City Univeristy London)


This study looks at some factors influencing mutual fund performance. Fund management location, family status and asset allocation and timing ability are examined. Using monthly returns on 4545 funds from Morningstar from January 1970 to June 2010, the study examines whether location influences the return a fund generates. It is found that U.S. managed funds outperform European managed funds, regardless of market invested in. This can be seen in terms of higher mean alpha, and statistically significant outperformance. A comparison is also carried out between the performance of family funds and non-family funds. Using the recursive portfolio technique and Rhodes utility based measure of persistence, the persistence of funds that are in a family are compared to those that do not belong to a family. A second hypothesis is also examined here, analyzing whether fund managers make their risk decision to influence performance for the second part of the year based on their performance in the first part of the year. It can be concluded that family status, family size or market does not affect persistence in performance. The study found that family rank has an impact on the risk adjustment behaviour of fund managers. The fact that the coefficient is negative suggests that managers are not behaving strategically. When markets are examined individually, fund managers within families compete in the U.S. and behave strategically in Europe. Finally, using asset allocation data on balanced funds, the study examines the skill of balanced fund managers to time particular asset classes. It is found that there is little timing ability present, across all markets and models.

Publication Type: Thesis (Doctoral)
Subjects: H Social Sciences > HG Finance
Departments: Bayes Business School > Finance
Doctoral Theses
Bayes Business School > Bayes Business School Doctoral Theses
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