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Performance Evaluation and Conditioning Information: The case of Hedge Funds

Author

Listed:
  • Harry. M Kat

    (ICMA Centre, University of Reading)

  • Joelle Miffre

    (EDHEC Business School (France))

Abstract

In this paper we investigate whether there are any significant differences in the ability of constant and time-varying expected return asset pricing models to detect superior performance in hedge funds. Our results strongly suggest that the static models traditionally employed to measure and evaluate hedge fund performance are misspecified. Allowing for conditioning information to predict changes in the risk and performance measures of hedge funds increases the statistical significance of the performance evaluation. In addition, incorrectly assuming constant expected returns appears to lead to underestimation of the abnormal performance of hedge funds

Suggested Citation

  • Harry. M Kat & Joelle Miffre, 2002. "Performance Evaluation and Conditioning Information: The case of Hedge Funds," ICMA Centre Discussion Papers in Finance icma-dp2002-10, Henley Business School, University of Reading.
  • Handle: RePEc:rdg:icmadp:icma-dp2002-10
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    File URL: http://www.icmacentre.ac.uk/pdf/discussion/DP2002-10.pdf
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    References listed on IDEAS

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    Cited by:

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    3. Darolles, Serge & Gourieroux, Christian, 2010. "Conditionally fitted Sharpe performance with an application to hedge fund rating," Journal of Banking & Finance, Elsevier, vol. 34(3), pages 578-593, March.
    4. Gregoriou, Greg N. & Racicot, François-Éric & Théoret, Raymond, 2021. "The response of hedge fund tail risk to macroeconomic shocks: A nonlinear VAR approach," Economic Modelling, Elsevier, vol. 94(C), pages 843-872.
    5. Gregory Connor & Lisa R. Goldberg & Robert A. Korajczyk, 2010. "Portfolio Risk Analysis," Economics Books, Princeton University Press, edition 1, number 9224.
    6. Lambert, Marie & Platania, Federico, 2020. "The macroeconomic drivers in hedge fund beta management," Economic Modelling, Elsevier, vol. 91(C), pages 65-80.

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