A Direct and Full-Information Estimation of the Distribution of Skill in the Mutual Fund Industry
Angie Andrikogiannopoulou and
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Filippos Papakonstantinou: Imperial College London
No 14-42, Swiss Finance Institute Research Paper Series from Swiss Finance Institute
We propose a novel approach to estimating the cross-sectional distribution of skill in the mutual fund industry, the proportion of funds with zero, negative, and positive alpha, and the skill of individual funds. We model the distribution of skill with a point mass at zero and two components, one with negative and one with positive support, and we tackle model specification uncertainty. We find that the skill distribution is highly non-normal, exhibiting heavy tails and negative skewness, and that while 14% of funds generate positive alpha, 76% have negative alpha; these results yield significantly different asset allocation decisions than previous estimates. Furthermore, portfolios formed using our methodology outperform those formed using alternative methodologies.
Keywords: Mutual Funds; Skill; Performance; Specification Uncertainty; Point Mass; Bayesian Estimation (search for similar items in EconPapers)
JEL-codes: G11 G23 C11 C52 C58 (search for similar items in EconPapers)
Pages: 59 pages
Date: 2014-06, Revised 2014-12
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp1442
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