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Nonparametric Assessment of Hedge Fund Performance

Author

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  • Caio Almeida

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Kim Ardison

    (FGV-EPGE - Universidad de Brazil)

  • René Garcia

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

We propose a new class of performance measures for Hedge Fund (HF) returns based on a family of empirically identifiable stochastic discount factors (SDFs). The SDF-based measures incorporate no-arbitrage pricing restrictions and naturally embed information about higher-order mixed moments between HF and benchmark factors returns. We provide a full asymptotic theory for our SDF estimators to test for the statistical significance of each fund's performance and for the relevance of individual benchmark factors within each proposed measure. We apply our methodology to a panel of 4815 individual hedge funds. Our empirical analysis reveals that fewer funds have a statistically significant positive alpha compared to the Jensen's alpha obtained by the traditional linear regression approach. Moreover, the funds' rankings vary considerably between the two approaches. Performance also varies between the members of our family because of a different fund exposure to higher-order moments of the benchmark factors, highlighting the potential heterogeneity across investors in evaluating performance. (C) 2019 Elsevier B.V. All rights reserved.

Suggested Citation

  • Caio Almeida & Kim Ardison & René Garcia, 2020. "Nonparametric Assessment of Hedge Fund Performance," Post-Print hal-02550789, HAL.
    • Handle: RePEc:hal:journl:hal-02550789
    DOI: 10.1016/j.jeconom.2019.08.002
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    More about this item

    Keywords

    Hedge funds; Admissible performance measures; Nonparametric estimation; Higher-order moments;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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