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Mutual Funds Flows and the “Sheriff of Nottingham” Effect

In: Artificial Economics

Author

Listed:
  • Lucia Milone

    (University Ca’ Foscari of Venice)

  • Paolo Pellizzari

    (University Ca’ Foscari of Venice)

Abstract

Investors in mutual funds appear to reward disproportionately the best performing funds with large inflows while, at the same time, avoid to withdraw similar amounts from the poorly managed funds. We show that this peculiar flat-convex shape of the flow-performance curve for mutual funds can be generally explained by a model where profit chasing customers punish the bad funds by switching a fraction of their wealth to the best ones (“Sheriff of Nottingham” effect). In the absence of external flows, the model provably produces a constant curve when the standard deviation of excess returns is much larger than the level of the returns. This for the most part explains the apparent insensitivity of flows to below-average returns. The introduction of exogenous injections of money invested in the top funds complete the model and provides a realistic increase in the flows of the funds yielding above-average returns. We finally show by simulation that our results are robust to variations in the values of the parameters of the model.

Suggested Citation

  • Lucia Milone & Paolo Pellizzari, 2009. "Mutual Funds Flows and the “Sheriff of Nottingham” Effect," Lecture Notes in Economics and Mathematical Systems, in: Cesáreo Hernández & Marta Posada & Adolfo López-Paredes (ed.), Artificial Economics, chapter 0, pages 117-128, Springer.
  • Handle: RePEc:spr:lnechp:978-3-642-02956-1_10
    DOI: 10.1007/978-3-642-02956-1_10
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    References listed on IDEAS

    as
    1. Lettau, Martin, 1997. "Explaining the facts with adaptive agents: The case of mutual fund flows," Journal of Economic Dynamics and Control, Elsevier, vol. 21(7), pages 1117-1147, June.
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    3. Anthony W. Lynch & David K. Musto, 2003. "How Investors Interpret Past Fund Returns," Journal of Finance, American Finance Association, vol. 58(5), pages 2033-2058, October.
    4. Jonathan B. Berk & Ian Tonks, 2007. "Return Persistence and Fund Flows in the Worst Performing Mutual Funds," NBER Working Papers 13042, National Bureau of Economic Research, Inc.
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    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Robert Kosowski & Allan Timmermann & Russ Wermers & Hal White, 2006. "Can Mutual Fund “Stars” Really Pick Stocks? New Evidence from a Bootstrap Analysis," Journal of Finance, American Finance Association, vol. 61(6), pages 2551-2595, December.
    8. Guercio, Diane Del & Tkac, Paula A., 2008. "Star Power: The Effect of Monrningstar Ratings on Mutual Fund Flow," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(4), pages 907-936, December.
    9. W. Brian Arthur & Paul Tayler, "undated". "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Computing in Economics and Finance 1997 57, Society for Computational Economics.
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    Cited by:

    1. Ron Bird & Paolo Pellizzari & Danny Yeung & Paul Woolley, 2012. "The Strategic Implementation of an Investment Process in a Funds Management Firm," Working Paper Series 17, The Paul Woolley Centre for Capital Market Dysfunctionality, University of Technology, Sydney.

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    More about this item

    Keywords

    Mutual Fund; Constant Curve; Hedge Fund; Excess Return; Good Fund;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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