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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 - 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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    1. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, January.
    2. Norvaisa, Rimas, 1993. "The central limit theorem for empirical and quantile processes in some Banach spaces," Stochastic Processes and their Applications, Elsevier, vol. 46(1), pages 1-27, May.
    3. Gourieroux, C. & Jasiak, J., 2008. "Dynamic quantile models," Journal of Econometrics, Elsevier, vol. 147(1), pages 198-205, November.
    4. Bawa, Vijay S., 1978. "Safety-First, Stochastic Dominance, and Optimal Portfolio Choice," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 13(2), pages 255-271, June.
    5. Haley, M. Ryan & McGee, M. Kevin, 2006. "Tilting safety first and the Sharpe portfolio," Finance Research Letters, Elsevier, vol. 3(3), pages 173-180, September.
    6. Getmansky, Mila & Lo, Andrew W. & Makarov, Igor, 2004. "An econometric model of serial correlation and illiquidity in hedge fund returns," Journal of Financial Economics, Elsevier, vol. 74(3), pages 529-609, December.
    7. Ghislain Yanou, 2008. "Extension of random matrix theory to the L-moments for robust portfolio allocation," Documents de travail du Centre d'Economie de la Sorbonne bla08103, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    8. Bruce Jones & Ričardas Zitikis, 2003. "Empirical Estimation of Risk Measures and Related Quantities," North American Actuarial Journal, Taylor & Francis Journals, vol. 7(4), pages 44-54.
    9. Elamir, Elsayed A. H. & Seheult, Allan H., 2003. "Trimmed L-moments," Computational Statistics & Data Analysis, Elsevier, vol. 43(3), pages 299-314, July.
    10. Burgstahler, David & Dichev, Ilia, 1997. "Earnings management to avoid earnings decreases and losses," Journal of Accounting and Economics, Elsevier, vol. 24(1), pages 99-126, December.
    11. Vytaras Brazauskas & Bruce L. Jones & Ricardas Zitikis, 2007. "Robustification and performance evaluation of empirical risk measures and other vector-valued estimators," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 175-199.
    12. Ghislain Yanou, 2008. "Extension of Random Matrix Theory to the L-moments for Robust Portfolio Allocation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00349205, HAL.
    13. Bruce L. Jones & Ricardas Zitikis, 2005. "Testing for the order of risk measures: an application of L-statistics in actuarial science," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 193-211.
    14. Karvanen, Juha, 2006. "Estimation of quantile mixtures via L-moments and trimmed L-moments," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 947-959, November.
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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. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    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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