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Non-Parametric Frontier Estimates of Mutual Fund Performance Using C- and L-Moments: Some Specification Tests

Author

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  • Kerstens, Kristiaan

    (IESEG School of Management, F-59000 Lille, France)

  • Mounir, Amine

    (Hogeschool-Universiteit Brussel (HUB), Belgium)

  • Van de Woestyne, Ignace

    (Hogeschool-Universiteit Brussel (HUB), Belgium)

Abstract

There is a burgeoning literature using non-parametric frontier methods to measure mutual fund performance. These articles measure the relationship between the various characteristics (mainly return information and some costs of ownership) of these specialized financial products to establish a ranking using some efficiency measure. We argue in favor of the use of the shortage function, which is compatible with general investor preferences, and question some of the often maintained hypotheses in this line of research. The empirical part employs a large database of US and European mutual funds to offer extensive tests of the underlying modeling assumptions using various frontier estimators.

Suggested Citation

  • Kerstens, Kristiaan & Mounir, Amine & Van de Woestyne, Ignace, 2010. "Non-Parametric Frontier Estimates of Mutual Fund Performance Using C- and L-Moments: Some Specification Tests," Working Papers 2010/10, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
  • Handle: RePEc:hub:wpecon:201010
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    10. Andreu, Laura & Serrano, Miguel & Vicente, Luis, 2019. "Efficiency of mutual fund managers: A slacks-based manager efficiency index," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1180-1193.
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    14. Carlos P. Barros & Qi Bin Liang & Nicolas Peypoch, 2014. "Technical Efficiency in the Angolan Banking Sector with the B-convexity Model," South African Journal of Economics, Economic Society of South Africa, vol. 82(3), pages 443-454, September.
    15. Basso, Antonella & Funari, Stefania, 2014. "Constant and variable returns to scale DEA models for socially responsible investment funds," European Journal of Operational Research, Elsevier, vol. 235(3), pages 775-783.
    16. Brandouy, Olivier & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2015. "Frontier-based vs. traditional mutual fund ratings: A first backtesting analysis," European Journal of Operational Research, Elsevier, vol. 242(1), pages 332-342.
    17. Laurens Cherchye & Bram De Rock & Dieter Saelens, 2024. "Nonparametric analysis of financial portfolio performance," Working Papers ECARES 2024-08, ULB -- Universite Libre de Bruxelles.
    18. Zhou, Zhongbao & Gao, Meng & Xiao, Helu & Wang, Rui & Liu, Wenbin, 2021. "Big data and portfolio optimization: A novel approach integrating DEA with multiple data sources," Omega, Elsevier, vol. 104(C).
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    20. J. Carlos Matallín-Sáez & Amparo Soler-Domínguez & Emili Tortosa-Ausina, 2013. "Does active management add value? New evidence from a quantile regression," Working Papers 2013/01, Economics Department, Universitat Jaume I, Castellón (Spain).
    21. Wanke, Peter & Barros, Carlos P. & Faria, João R., 2015. "Financial distress drivers in Brazilian banks: A dynamic slacks approach," European Journal of Operational Research, Elsevier, vol. 240(1), pages 258-268.
    22. Galagedera, Don U.A. & Fukuyama, Hirofumi & Watson, John & Tan, Eric K.M., 2020. "Do mutual fund managers earn their fees? New measures for performance appraisal," European Journal of Operational Research, Elsevier, vol. 287(2), pages 653-667.
    23. Aminah Shari, 2015. "The Performance of Unit Trust Industry in Malaysia," Information Management and Business Review, AMH International, vol. 7(4), pages 46-54.
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