Working Paper: CEPR ID: DP13618
Authors: Juha Joenväärä; Mikko Kaupila; Robert Kosowski; Pekka Tolonen
Abstract: This paper proposes a novel database merging approach and re-examines the fundamental questions regarding hedge fund performance. Before drawing conclusions about fund performance, we form an aggregate database by exploiting all available information across and within seven commercial databases so that widest possible data coverage is obtained and the effect of data biases is mitigated. Average performance is significantly lower but more persistent when these conclusions are inferred from aggregate database than from some of the individual commercial databases. Although hedge funds deliver performance persistence, an average fund or industry as a whole do not deliver significant risk-adjusted net-of-fee returns while the gross-of-fee returns remain significantly positive. Consistent with previous literature, we find a significant association between fund-characteristics related to share restrictions as well as compensation structure and risk-adjusted returns.
Keywords: hedge fund performance; persistence; sample selection bias; managerial skill
JEL Codes: G11; G12; G23
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
Cause | Effect |
---|---|
average hedge fund performance from aggregate database (G23) | average hedge fund performance from individual databases (G23) |
individual databases (C81) | positive selection bias (C52) |
hedge funds (G23) | performance persistence (C41) |
average fund (G23) | significant risk-adjusted net-of-fee returns (G11) |
gross-of-fee returns (G12) | significant positive (C29) |
tighter share restrictions (G34) | risk-adjusted returns (G12) |
certain compensation structures (M52) | risk-adjusted returns (G12) |
diseconomies of scale (F12) | risk-adjusted returns (G12) |
fund size (G23) | risk-adjusted returns (G12) |
fund age (I22) | risk-adjusted returns (G12) |
capital flows (F32) | risk-adjusted returns (G12) |