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Multi-Time and Multi-Moment Nonparametric Frontier-Based Fund Rating: Proposal and Buy-and-Hold Backtesting Strategy

Author

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  • Kristiaan Kerstens

    (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)

  • Paolo Mazza

    (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)

  • Tiantian Ren

    (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

    (KU Leuven - Catholic University of Leuven = Katholieke Universiteit Leuven)

Abstract

This contribution introduces new frontier models to rate mutual funds that can simultaneously handle multiple moments and multiple times. These new models are empirically applied to hedge fund data, since this category of funds is known to be subject to non-normal return distributions. We define a simple buy-and-hold backtesting strategy to test for the impact of multiple moments and multiple times separately and jointly. The empirical results demonstrate that the proposed frontier models perform better than most financial performance measures and existing frontier models in selecting promising funds.

Suggested Citation

  • Kristiaan Kerstens & Paolo Mazza & Tiantian Ren & Ignace van de Woestyne, 2022. "Multi-Time and Multi-Moment Nonparametric Frontier-Based Fund Rating: Proposal and Buy-and-Hold Backtesting Strategy," Post-Print hal-03833261, HAL.
    • Handle: RePEc:hal:journl:hal-03833261
    DOI: 10.1016/j.omega.2022.102718
    Note: View the original document on HAL open archive server: https://lilloa.hal.science/hal-03833261v1
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Helu Xiao & Qing Wang & Tiantian Ren & Zhongbao Zhou, 2025. "Efficiency analysis of funding resources for rural revitalization in China based on the concept of sustainable development: evidence from parallel DEA with shared inputs/outputs and Tobit models," Operational Research, Springer, vol. 25(3), pages 1-44, September.
    5. Ren, Tiantian & Wang, Na & Xiao, Helu & Zhou, Zhongbao, 2024. "Efficiency of funding to rural revitalization and regional heterogeneity of technologies in China: Dynamic network nonconvex metafrontiers," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).

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    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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