New 'Stylized Facts' About Hedge Funds and Database Selection Bias
University of Oulu ; Imperial College Business School, Centre for Hedge Fund Research
Imperial College Business School; University of Oxford, Oxford-Man Institute of Quantitative Finance
University of Oulu
This paper presents new stylized facts about hedge fund performance and database selection biases based on a novel database aggregation. By highlighting economically important effects of database selection bias on previously documented results we aim to improve the ability of researchers in this literature to compare results across different studies. We carefully motivate and test a set of eight hypotheses regarding the impact of database selection biases on stylized facts. We document significant positive risk-adjusted performance of the average fund while differences in its magnitude are due to differences in fund size, domicile and data biases, but not differences in fund risk exposures. Measures of misreporting and return smoothing by funds are similar across different databases. Performance persistence results are sensitive to share restrictions, rebalancing frequency, fund size and weighting scheme as well as more pronounced biases in certain databases. Hedge funds with greater managerial incentives, smaller funds and younger funds outperform while multivariate analysis shows that funds imposing lockups do not deliver significantly higher risk-adjusted returns. Several stylized facts are sensitive to the choice of the database which highlights the importance of using a consolidated database that is more representative of the aggregate industry.
Number of Pages in PDF File: 84
Keywords: Hedge fund performance, persistence, sample selection bias, managerial skill
JEL Classification: G11, G12, G23working papers series
Date posted: January 22, 2012 ; Last revised: November 22, 2012
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