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Frontier-based vs. traditional mutual fund ratings: A first backtesting analysis

Author

Listed:
  • Olivier Brandouy

    (Sorbonne Graduate Business School - IAE Paris - Sorbonne Business School, GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique)

  • Kristiaan Kerstens

    (Department of Economics - IESEG School of Managementg, LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - ULCO - Université du Littoral Côte d'Opale - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Ignace Van De Woestyne

Abstract

We explore the potential benefits of a series of existing and new non-parametric convex and non-convex frontier-based fund rating models to summarize the information contained in the moments of the mutual fund price series. Limiting ourselves to the traditional mean-variance portfolio setting, we test in a simple backtesting setup whether these efficiency measures fare any better than more traditional financial performance measures in selecting promising investment opportunities. The evidence points to a remarkable superior performance of these frontier models compared to most, but not all traditional financial performance measures.

Suggested Citation

  • Olivier Brandouy & Kristiaan Kerstens & Ignace Van De Woestyne, 2015. "Frontier-based vs. traditional mutual fund ratings: A first backtesting analysis," Post-Print hal-01533555, HAL.
    • Handle: RePEc:hal:journl:hal-01533555
    DOI: 10.1016/j.ejor.2014.11.010
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    Cited by:

    1. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    2. Eduard Gabriel Ceptureanu & Sebastian Ceptureanu & Claudiu Herteliu, 2021. "Evidence regarding external financing in manufacturing MSEs using partial least squares regression," Annals of Operations Research, Springer, vol. 299(1), pages 1189-1202, April.
    3. Martin Branda, 2016. "Mean-value at risk portfolio efficiency: approaches based on data envelopment analysis models with negative data and their empirical behaviour," 4OR, Springer, vol. 14(1), pages 77-99, March.
    4. Zhou, Zhongbao & Jin, Qianying & Xiao, Helu & Wu, Qian & Liu, Wenbin, 2018. "Estimation of cardinality constrained portfolio efficiency via segmented DEA," Omega, Elsevier, vol. 76(C), pages 28-37.
    5. Kerstens, Kristiaan & Mazza, Paolo & Ren, Tiantian & Van de Woestyne, Ignace, 2022. "Multi-Time and Multi-Moment Nonparametric Frontier-Based Fund Rating: Proposal and Buy-and-Hold Backtesting Strategy," Omega, Elsevier, vol. 113(C).
    6. Jin, Qianying & Basso, Antonella & Funari, Stefania & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2024. "Evaluating different groups of mutual funds using a metafrontier approach: Ethical vs. non-ethical funds," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1134-1145.
    7. 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.
    8. Sepideh Kaffash & Marianna Marra, 2017. "Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds," Annals of Operations Research, Springer, vol. 253(1), pages 307-344, June.
    9. Ren, Tiantian & Kerstens, Kristiaan & Kumar, Saurav, 2024. "Risk-aversion versus risk-loving preferences in nonparametric frontier-based fund ratings: A buy-and-hold backtesting strategy," European Journal of Operational Research, Elsevier, vol. 319(1), pages 332-344.
    10. Adam, Lukáš & Branda, Martin, 2021. "Risk-aversion in data envelopment analysis models with diversification," Omega, Elsevier, vol. 102(C).
    11. 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.
    12. Xiao, Helu & Zhou, Zhongbao & Ren, Teng & Liu, Wenbin, 2022. "Estimation of portfolio efficiency in nonconvex settings: A free disposal hull estimator with non-increasing returns to scale," Omega, Elsevier, vol. 111(C).
    13. Lin, Ruiyue & Liu, Qian, 2021. "Multiplier dynamic data envelopment analysis based on directional distance function: An application to mutual funds," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1043-1057.
    14. Pornanong Budsaratragoon & Boonlert Jitmaneeroj, 2021. "Fund Ratings of Socially Responsible Investing (SRI) Funds: A Precautionary Note," Sustainability, MDPI, vol. 13(14), pages 1-25, July.
    15. Lin, Ruiyue & Li, Zongxin, 2020. "Directional distance based diversification super-efficiency DEA models for mutual funds," Omega, Elsevier, vol. 97(C).

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