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- W2912404882 abstract "This paper proposes a new methodology to evaluate fund performance. We assume that each fund alpha is drawn from one of several distributions based on their skill levels (e.g., good, neutral, or bad). For a sample of observed funds, the composite distribution of alpha is thus a mixture of the underlying distributions. We use the EM algorithm to infer the proportion of funds at different skill levels and estimate the conditional probability each fund is of a skill type given estimated alpha. When applying our approach to hedge funds over 1994-2009, we find that about 50% of funds have positive skill. Superior funds identified by our approach persistently deliver high out-of-sample alphas over the next three years. Meanwhile, while investors chase past performance, inflows do not reduce funds’ performance in the near future." @default.
- W2912404882 created "2019-02-21" @default.
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- W2912404882 date "2011-01-01" @default.
- W2912404882 modified "2023-09-24" @default.
- W2912404882 title "Hedge Funds: The Good, the (Not-So) Bad, and the Ugly" @default.
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- W2912404882 doi "https://doi.org/10.2139/ssrn.1787296" @default.
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