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Conditionally fitted Sharpe performance with an application to hedge fund rating


  • Serge Darolles

    () (DRM-Finance - DRM - Dauphine Recherches en Management - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique)

  • Christian Gourieroux

    (CREST - Centre de Recherche en Économie et Statistique - INSEE - ENSAE ParisTech - École Nationale de la Statistique et de l'Administration Économique)


We define a battery of Sharpe performance measures, which differ by the information taken into account in their computation, but also by the potential use of the fund by the investor. Four advantages of Sharpe performance based rating are especially important for the investor. First, the performance measures correspond to the standard measures used for mutual funds and known by retail investors. Second, we can compare the numerical results, even if they are obtained with different assumptions. Third, the rankings are based on regression analysis and easy to compute. Fourth, we can easily use these performance measures in the design of an optimal basket of hedge funds. Finally, we can use the performance measures to partition the set of funds into homogenous segments.

Suggested Citation

  • Serge Darolles & Christian Gourieroux, 2010. "Conditionally fitted Sharpe performance with an application to hedge fund rating," Post-Print halshs-00677727, HAL.
  • Handle: RePEc:hal:journl:halshs-00677727
    DOI: 10.1016/j.jbankfin.2009.08.025
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    References listed on IDEAS

    1. Zakamouline, Valeri & Koekebakker, Steen, 2009. "Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1242-1254, July.
    2. Vikas Agarwal, 2004. "Risks and Portfolio Decisions Involving Hedge Funds," Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 63-98.
    3. Chen, Zhiwu & Knez, Peter J, 1996. "Portfolio Performance Measurement: Theory and Applications," Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 511-555.
    4. Dybvig, Philip H & Ross, Stephen A, 1985. " The Analytics of Performance Measurement Using a Security Market Line," Journal of Finance, American Finance Association, vol. 40(2), pages 401-416, June.
    5. Wayne E. Ferson & Andrew F. Siegel, 2009. "Testing Portfolio Efficiency with Conditioning Information," Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2535-2558, July.
    6. Levy, Haim & Levy, Moshe, 2009. "The safety first expected utility model: Experimental evidence and economic implications," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1494-1506, August.
    7. Haim Levy, 1972. "Portfolio Performance and the Investment Horizon," Management Science, INFORMS, vol. 18(12), pages 645-653, August.
    8. Jobson, J. D. & Korkie, Bob, 1982. "Potential performance and tests of portfolio efficiency," Journal of Financial Economics, Elsevier, vol. 10(4), pages 433-466, December.
    9. Ferson, Wayne E & Schadt, Rudi W, 1996. " Measuring Fund Strategy and Performance in Changing Economic Conditions," Journal of Finance, American Finance Association, vol. 51(2), pages 425-461, June.
    10. Bawa, Vijay S., 1975. "Optimal rules for ordering uncertain prospects," Journal of Financial Economics, Elsevier, vol. 2(1), pages 95-121, March.
    11. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    12. Gourieroux, C. & Jouneau, F., 1999. "Econometrics of efficient fitted portfolios," Journal of Empirical Finance, Elsevier, vol. 6(1), pages 87-118, January.
    13. Jha, Ranjini & Korkie, Bob & Turtle, Harry J., 2009. "Measuring performance in a dynamic world: Conditional mean-variance fundamentals," Journal of Banking & Finance, Elsevier, vol. 33(10), pages 1851-1859, October.
    14. Farinelli, Simone & Ferreira, Manuel & Rossello, Damiano & Thoeny, Markus & Tibiletti, Luisa, 2008. "Beyond Sharpe ratio: Optimal asset allocation using different performance ratios," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2057-2063, October.
    15. Christian Pedersen & Stephen Satchell, 2002. "On the foundation of performance measures under asymmetric returns," Quantitative Finance, Taylor & Francis Journals, vol. 2(3), pages 217-223.
    16. Jonathan Ingersoll & Ivo Welch, 2007. "Portfolio Performance Manipulation and Manipulation-proof Performance Measures," Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1503-1546, 2007 17.
    17. Darolles, Serge & Gourieroux, Christian & Jasiak, Joann, 2009. "L-performance with an application to hedge funds," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 671-685, September.
    18. Rajna Gibson & Sébastien Gyger, 2007. "The Style Consistency of Hedge Funds," European Financial Management, European Financial Management Association, vol. 13(2), pages 287-308.
    19. Treynor, Jack L & Black, Fischer, 1973. "How to Use Security Analysis to Improve Portfolio Selection," The Journal of Business, University of Chicago Press, vol. 46(1), pages 66-86, January.
    20. Nandita Das, 2003. "Hedge Fund Classification using K-means Clustering Method," Computing in Economics and Finance 2003 284, Society for Computational Economics.
    21. Grauer, Robert R. & Janmaat, Johannus A., 2009. "On the power of cross-sectional and multivariate tests of the CAPM," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 775-787, May.
    22. Eling, Martin & Schuhmacher, Frank, 2007. "Does the choice of performance measure influence the evaluation of hedge funds?," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2632-2647, September.
    23. Agarwal, Vikas & Boyson, Nicole M. & Naik, Narayan Y., 2009. "Hedge Funds for Retail Investors? An Examination of Hedged Mutual Funds," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(02), pages 273-305, April.
    24. 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, Reading University.
    25. Son-Nan Chen & Cheng F. Lee, 1986. "The Effects of the Sample Size, the Investment Horizon and Market Conditions on the Validity of Composite Performance Measures: A Generalization," Management Science, INFORMS, vol. 32(11), pages 1410-1421, November.
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    Cited by:

    1. Guo, Biao & Xiao, Yugu, 2016. "A note on why doesn't the choice of performance measure matter?," Finance Research Letters, Elsevier, vol. 16(C), pages 248-254.
    2. Bertrand Maillet & Michele Costola & Massimiliano Caporin & Gregory Jannin, 2015. "On the (Ab)Use of Omega?," Working Papers 2015:02, Department of Economics, University of Venice "Ca' Foscari".
    3. Brandouy, Olivier & Briec, Walter & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2010. "Portfolio performance gauging in discrete time using a Luenberger productivity indicator," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1899-1910, August.
    4. Kerstens, Kristiaan & Mounir, Amine & de Woestyne, Ignace Van, 2011. "Non-parametric frontier estimates of mutual fund performance using C- and L-moments: Some specification tests," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1190-1201, May.
    5. Giannikis, Dimitrios & Vrontos, Ioannis D., 2011. "A Bayesian approach to detecting nonlinear risk exposures in hedge fund strategies," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1399-1414, June.
    6. Sadefo Kamdem, J. & Mbairadjim Moussa, A. & Terraza, M., 2012. "Fuzzy risk adjusted performance measures: Application to hedge funds," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 702-712.
    7. Rachida Hennani & Michel Terraza, 2012. "Value-at-Risk stressée chaotique d’un portefeuille bancaire," Working Papers 12-23, LAMETA, Universtiy of Montpellier, revised Sep 2012.
    8. Angelidis, Timotheos & Tessaromatis, Nikolaos, 2010. "The efficiency of Greek public pension fund portfolios," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2158-2167, September.
    9. Bussière, Matthieu & Hoerova, Marie & Klaus, Benjamin, 2015. "Commonality in hedge fund returns: Driving factors and implications," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 266-280.
    10. Schuhmacher, Frank & Eling, Martin, 2012. "A decision-theoretic foundation for reward-to-risk performance measures," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2077-2082.
    11. Schuhmacher, Frank & Eling, Martin, 2011. "Sufficient conditions for expected utility to imply drawdown-based performance rankings," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2311-2318, September.
    12. Badrinath, S.G. & Gubellini, S., 2011. "On the characteristics and performance of long-short, market-neutral and bear mutual funds," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1762-1776, July.
    13. Christian Gouriéroux, 2008. "Bon ou mauvais usage des notations," Revue d'Économie Financière, Programme National Persée, vol. 7(1), pages 259-263.


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