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A flow-based explanation for return predictability

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  • Lou, Dong

Abstract

This paper proposes and tests an investment-flow based explanation for three empirical findings on return predictability - the persistence of mutual fund performance, the 'smart money' effect, and stock price momentum. Since mutual fund managers generally scale up or down their existing positions in response to investment flows, and the portfolios of funds receiving capital generally differ from those that lose capital, investment flows to mutual funds can cause signicant demand shocks in individual stocks. Moreover, given that mutual fund flows are largely predictable from past fund performance and past flows, this paper further establishes that flow-induced price pressure is predictable. Finally, this paper shows that such flow-based return predictability can fully account for mutual fund performance persistence and the 'smart money' effect, and can partially explain stock price momentum.

Suggested Citation

  • Lou, Dong, 2009. "A flow-based explanation for return predictability," LSE Research Online Documents on Economics 29310, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:29310
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    File URL: http://eprints.lse.ac.uk/29310/
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    References listed on IDEAS

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    1. Dimitri Vayanos & Paul Woolley, 2013. "An Institutional Theory of Momentum and Reversal," The Review of Financial Studies, Society for Financial Studies, vol. 26(5), pages 1087-1145.
    2. Chen, Hsiu-Lang & Jegadeesh, Narasimhan & Wermers, Russ, 2000. "The Value of Active Mutual Fund Management: An Examination of the Stockholdings and Trades of Fund Managers," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(3), pages 343-368, September.
    3. Wermers, Russ & Yao, Tong & Zhao, Jane, 2007. "The investment value of mutual fund portfolio disclosure," CFR Working Papers 06-09, University of Cologne, Centre for Financial Research (CFR).
    4. Teo, Melvyn & Woo, Sung-Jun, 2004. "Style effects in the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 74(2), pages 367-398, November.
    5. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    6. Jonathan B. Berk & Richard C. Green, 2004. "Mutual Fund Flows and Performance in Rational Markets," Journal of Political Economy, University of Chicago Press, vol. 112(6), pages 1269-1295, December.
    7. Russ Wermers, 1999. "Mutual Fund Herding and the Impact on Stock Prices," Journal of Finance, American Finance Association, vol. 54(2), pages 581-622, April.
    8. Nicolas P. B. Bollen, 2005. "Short-Term Persistence in Mutual Fund Performance," The Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 569-597.
    9. Warther, Vincent A., 1995. "Aggregate mutual fund flows and security returns," Journal of Financial Economics, Elsevier, vol. 39(2-3), pages 209-235.
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    Cited by:

    1. Miguel Antón & Christopher Polk, 2014. "Connected Stocks," Journal of Finance, American Finance Association, vol. 69(3), pages 1099-1127, June.
    2. Kang, Johnny & Pekkala, Tapio & Polk, Christopher & Ribeiro, Ruy, 2011. "Stock prices under pressure: how tax and interest rates drive returns at the turn of the tax year," LSE Research Online Documents on Economics 43096, London School of Economics and Political Science, LSE Library.
    3. Darrell Duffie & Bruno Strulovici, 2012. "Capital Mobility and Asset Pricing," Econometrica, Econometric Society, vol. 80(6), pages 2469-2509, November.
    4. Dong Lou & Hongjun Yan & Jinfan Zhang, 2013. "Anticipated and Repeated Shocks in Liquid Markets," The Review of Financial Studies, Society for Financial Studies, vol. 26(8), pages 1891-1912.
    5. Clemens Sialm & T. Mandy Tham, 2016. "Spillover Effects in Mutual Fund Companies," Management Science, INFORMS, vol. 62(5), pages 1472-1486, May.

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    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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