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How Many Good and Bad Funds are There, Really?

In: HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING

Author

Listed:
  • Wayne Ferson
  • Yong Chen

Abstract

Building on the work of Barras, Scaillet and Wermers (BSW, 2010), we propose a modified approach to inferring performance for a cross-section of investment funds. Our model assumes that funds belong to groups of different abnormal performance or alpha. Using the structure of the probability model, we simultaneously estimate the alpha locations and the fractions of funds for each group, taking multiple testing into account. Our approach allows for tests with imperfect power that may falsely classify good funds as bad, and vice versa. Examining both mutual funds and hedge funds, we find smaller fractions of zero-alpha funds and more funds with abnormal performance, compared with the BSW approach. We also use the model as prior information about the cross-section of funds to evaluate and predict fund performance.

Suggested Citation

  • Wayne Ferson & Yong Chen, 2020. "How Many Good and Bad Funds are There, Really?," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 108, pages 3753-3827, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789811202391_0108
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    Citations

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    Cited by:

    1. Chen, Yong & Kelly, Bryan & Wu, Wei, 2020. "Sophisticated investors and market efficiency: Evidence from a natural experiment," Journal of Financial Economics, Elsevier, vol. 138(2), pages 316-341.
    2. Wayne Ferson & Junbo L Wang, 2021. "A Panel Regression Approach to Holdings-Based Fund Performance Measures [Multiperiod performance persistence analysis of hedge funds]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 11(4), pages 695-734.

    More about this item

    Keywords

    Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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