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Reassessing False Discoveries in Mutual Fund Performance: Skill, Luck, or Lack of Power?

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  • ANGIE ANDRIKOGIANNOPOULOU
  • FILIPPOS PAPAKONSTANTINOU

Abstract

Barras, Scaillet, and Wermers propose the false discovery rate (FDR) to separate skill (alpha) from luck in fund performance. Using simulations with parameters informed by the data, we find that this methodology is conservative and underestimates the proportion of nonzero‐alpha funds. For example, 65% of funds with economically large alphas of ±2% are misclassified as zero alpha. This bias arises from the low signal‐to‐noise ratio in fund returns and the resulting low statistical power. Our results question FDR's applicability in performance evaluation and other domains with low power, and can materially change the conclusion that most funds have zero alpha.

Suggested Citation

  • Angie Andrikogiannopoulou & Filippos Papakonstantinou, 2019. "Reassessing False Discoveries in Mutual Fund Performance: Skill, Luck, or Lack of Power?," Journal of Finance, American Finance Association, vol. 74(5), pages 2667-2688, October.
    • Handle: RePEc:bla:jfinan:v:74:y:2019:i:5:p:2667-2688
    DOI: 10.1111/jofi.12784
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    Cited by:

    1. Keith Cuthbertson & Dirk Nitzsche & Niall O’Sullivan, 2023. "UK mutual funds: performance persistence and portfolio size," Journal of Asset Management, Palgrave Macmillan, vol. 24(4), pages 284-298, July.
    2. Michel Verlaine, 2022. "Behavioral finance and the architecture of the asset management industry," Journal of Economic Surveys, Wiley Blackwell, vol. 36(5), pages 1454-1476, December.
    3. Kong, Dongmin & Zhao, Zhao, 2024. "Overseas exposures, global events, and mutual fund performance," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 848-863.
    4. Alan Crane & Kevin Crotty, 2020. "How Skilled Are Security Analysts?," Journal of Finance, American Finance Association, vol. 75(3), pages 1629-1675, June.
    5. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2022. "Mutual fund performance persistence: Factor models and portfolio size," International Review of Financial Analysis, Elsevier, vol. 81(C).
    6. Christiansen, Charlotte & Grønborg, Niels S. & Nielsen, Ole L., 2020. "Mutual fund selection for realistically short samples," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 218-240.
    7. Heath, Davidson & Ringgenberg, Matthew C. & Samadi, Mehrdad & Werner, Ingrid M., 2019. "Reusing Natural Experiments," Working Paper Series 2019-21, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    8. Ardia, David & Bluteau, Keven & Tran, Thien Duy, 2022. "How easy is it for investment managers to deploy their talent in green and brown stocks?," Finance Research Letters, Elsevier, vol. 48(C).
    9. Campbell R. Harvey & Yan Liu, 2020. "False (and Missed) Discoveries in Financial Economics," Journal of Finance, American Finance Association, vol. 75(5), pages 2503-2553, October.
    10. Cheng, Tingting & Yan, Cheng & Yan, Yayi, 2021. "Improved inference for fund alphas using high-dimensional cross-sectional tests," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 57-81.
    11. Huang, Haitao & Jiang, Lei & Leng, Xuan & Peng, Liang, 2023. "Bootstrap analysis of mutual fund performance," Journal of Econometrics, Elsevier, vol. 235(1), pages 239-255.
    12. Psaradellis, Ioannis & Laws, Jason & Pantelous, Athanasios A. & Sermpinis, Georgios, 2023. "Technical analysis, spread trading, and data snooping control," International Journal of Forecasting, Elsevier, vol. 39(1), pages 178-191.
    13. Clare, Andrew & Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2021. "How skilful are US fixed-income fund managers?," International Review of Financial Analysis, Elsevier, vol. 74(C).
    14. Zhang, Junsheng & Peng, Zezhi & Zeng, Yamin & Yang, Haisheng, 2023. "Do big data mutual funds outperform?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    15. Moraes, Fernando & Cavalcante-Filho, Elias & De-Losso, Rodrigo, 2021. "Unskilled fund managers: Replicating active fund performance with few ETFs," International Review of Financial Analysis, Elsevier, vol. 78(C).
    16. Hassanniakalager, Arman & Baker, Paul L. & Platanakis, Emmanouil, 2024. "A False Discovery Rate approach to optimal volatility forecasting model selection," International Journal of Forecasting, Elsevier, vol. 40(3), pages 881-902.
    17. Campbell R. Harvey & Yan Liu, 2020. "False (and Missed) Discoveries in Financial Economics," Papers 2006.04269, arXiv.org.
    18. Timothy B. Riley, 2021. "Portfolios of actively managed mutual funds," The Financial Review, Eastern Finance Association, vol. 56(2), pages 205-230, May.
    19. Timmermann, Allan & Qu, Ritong & Zhu, Yinchu, 2019. "Do Any Economists Have Superior Forecasting Skills?," CEPR Discussion Papers 14112, C.E.P.R. Discussion Papers.
    20. Sermpinis, Georgios & Hassanniakalager, Arman & Stasinakis, Charalampos & Psaradellis, Ioannis, 2021. "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).

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