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L-performance with an application to hedge funds

Author

Listed:
  • Serge Darolles

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

  • Christian Gourieroux

    (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique)

  • Joann Jasiak

    (Department of Mathematics and Statistics [Toronto] - York University [Toronto])

Abstract

This paper introduces a new parametric fund performance measure, called the L-performance. The L-performance is an alternative to the Sharpe performance, which is commonly used in practice despite its inability to account for skewness and heavy tails of unconditional return distributions. The L-performance improves upon the Sharpe measure in this respect. Technically, it resembles the Sharpe measure in that it is defined as a ratio of the first- and second-order moments, which are the trimmed L-moments instead of the conventional (power) moments. The trimming parameters allow for focusing the L-performance on specific risk levels of interest, according to financial risk criteria. For illustration, a set of L-performances is computed for a variety of hedge funds. The empirical study shows the use of L-performance for fund ranking and return smoothing (manipulation) control.

Suggested Citation

  • Serge Darolles & Christian Gourieroux & Joann Jasiak, 2009. "L-performance with an application to hedge funds," Post-Print halshs-00677730, HAL.
    • Handle: RePEc:hal:journl:halshs-00677730
    DOI: 10.1016/j.jempfin.2009.05.003
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    References listed on IDEAS

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    3. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand B. Maillet, 2014. "A Survey On The Four Families Of Performance Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 28(5), pages 917-942, December.
    4. Carole Bernard & Massimiliano Caporin & Bertrand Maillet & Xiang Zhang, 2023. "Omega Compatibility: A Meta-analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 493-526, August.
    5. Kim, Woo Chang & Fabozzi, Frank J. & Cheridito, Patrick & Fox, Charles, 2014. "Controlling portfolio skewness and kurtosis without directly optimizing third and fourth moments," Economics Letters, Elsevier, vol. 122(2), pages 154-158.
    6. Jules Sadefo Kamdem & Zoulkiflou Moumouni, 2020. "Comparison of Some Static Hedging Models of Agricultural Commodities Price Uncertainty," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 631-655, September.
    7. López-Díaz, Miguel & Sordo, Miguel A. & Suárez-Llorens, Alfonso, 2012. "On the Lp-metric between a probability distribution and its distortion," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 257-264.
    8. Hachmi Ben Ameur & Fredj Jawadi & Abdoulkarim Idi Cheffou & Wael Louhichi, 2018. "Measurement errors in stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 287-306, March.
    9. Philippe Bernard & Najat El Mekkaoui De Freitas & Bertrand B. Maillet, 2022. "A financial fraud detection indicator for investors: an IDeA," Annals of Operations Research, Springer, vol. 313(2), pages 809-832, June.
    10. 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.
    11. Anna E. Olkova, 2017. "Mutual Funds Performance Assessment Techniques: Comparative Analysis," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 3, pages 85-95, June.
    12. Andrea Bastianin, 2020. "Robust measures of skewness and kurtosis for macroeconomic and financial time series," Applied Economics, Taylor & Francis Journals, vol. 52(7), pages 637-670, February.
    13. Zoulkiflou Moumouni & Jules Sadefo-Kamdem, 2019. "New models of commodity risk hedging according to the behavior of economic decision-makers or Rollover Strategies," Working Papers hal-02417459, HAL.
    14. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    15. Serge Darolles & Christian Gouriéroux, 2013. "The Effects of Management and Provision Accounts on Hedge Fund Returns - Part I : The High Water Mark Scheme," Working Papers 2013-22, Center for Research in Economics and Statistics.

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