Beyond mean–variance: assessing hedge fund performance in a non-parametric world

Afrae Hassouni () and Hugues Pirotte Speder
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Afrae Hassouni: Université Libre de Bruxelles (ULB), SBS-EM

Financial Markets and Portfolio Management, 2022, vol. 36, issue 4, No 3, 473-488

Abstract: Abstract This paper uses Data Envelopment Analysis (DEA) to compare the performance of hedge funds to that of equities. The analysis covers the period from January 1999 to December 2013 and shows that under a mean–variance DEA, hedge funds significantly outperform equities. However, this outperformance is no longer significant when skewness and kurtosis are integrated. The DEA technique is particularly interesting for assessing hedge fund performance because of its flexibility and its non-parametric property: DEA allows to easily add additional attributes to the analysis and assesses performance relative to the sample under analysis without requiring any benchmark.

Keywords: Hedge funds; Directional DEA; Performance; Non-parametric efficient frontier (search for similar items in EconPapers)
JEL-codes: C14 C44 C67 G11 G23 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:kap:fmktpm:v:36:y:2022:i:4:d:10.1007_s11408-022-00409-8

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DOI: 10.1007/s11408-022-00409-8

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