IDEAS home Printed from https://ideas.repec.org/p/fmg/fmgdps/dp643.html
   My bibliography  Save this paper

A Flow-Based Explanation for Return Predictability

Author

Listed:
  • Dong Lou

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 significant demand shocks in individual stocks. Moreover, given that mutual fund ows 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

  • Dong Lou, 2009. "A Flow-Based Explanation for Return Predictability," FMG Discussion Papers dp643, Financial Markets Group.
  • Handle: RePEc:fmg:fmgdps:dp643
    as

    Download full text from publisher

    File URL: http://www.lse.ac.uk/fmg/workingPapers/discussionPapers/fmgdps/DP643PWC7.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. John Y. Campbell, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    2. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Tobias Adrian & Joshua Rosenberg, 2008. "Stock Returns and Volatility: Pricing the Short-Run and Long-Run Components of Market Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2997-3030, December.
    5. Olivier Blanchard & John Simon, 2001. "The Long and Large Decline in U.S. Output Volatility," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 32(1), pages 135-174.
    6. Mele, Antonio, 2007. "Asymmetric stock market volatility and the cyclical behavior of expected returns," Journal of Financial Economics, Elsevier, vol. 86(2), pages 446-478, November.
    7. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    8. Estrella, Arturo & Hardouvelis, Gikas A, 1991. " The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    9. Nicholas Barberis & Ming Huang & Tano Santos, 2001. "Prospect Theory and Asset Prices," The Quarterly Journal of Economics, Oxford University Press, vol. 116(1), pages 1-53.
    10. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters,in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
    11. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
    12. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters,in: Business Cycles, Indicators and Forecasting, pages 95-156 National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fmg:fmgdps:dp643. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (The FMG Administration). General contact details of provider: http://www.lse.ac.uk/fmg/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.