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.
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Availability of data and materials
The data that support the findings of this study are available from Refinitiv’s Lipper Fund Research, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are, however, available from the authors upon reasonable request and with permission of Refinitiv.
The Mann–Whitney test is a non-parametric statistical test that tests the null hypothesis that the averages of two groups are equal.
DMUs refer to hedge funds and equities in our case.
TASS started keeping defunct funds inside their database only after January 1994. Before that date, defunct funds were completely deleted. Therefore, to avoid survivorship bias, we only include funds that were launched as from January 1994.
Those are mainly series of different share classes of the same fund.
An analysis with value-weighted returns is also conducted and the findings are similar.
As stated above, DEA scores measure the distance that separates each unit from the efficient frontier. Hence, the lower the DEA score, the closer the unit is to the efficient frontier.
This might be due to the small sample size of the DSB category.
The NBER defines the financial crisis as starting in December 2007 and lasting until June 2009.
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We would like to express our gratitude to Thomson Reuters for providing us with data on hedge funds. We are also grateful for the helpful comments and suggestions made by the editor Markus Schmid, Caroline Buts, Catherine Dehon, Pascal François, Laurent Gheeraert, Federico Platania, Olivier Scaillet, and two anonymous referees.
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Hassouni, A., Pirotte, H. Beyond mean–variance: assessing hedge fund performance in a non-parametric world. Financ Mark Portf Manag 36, 473–488 (2022). https://doi.org/10.1007/s11408-022-00409-8