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Do Noise Traders Influence Stock Prices?

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  • Kelly, Morgan

Abstract

This paper tests a smart money-noise trader model directly by comparing its predictions with the behavior of actual investors. It assumes that individual probability of being a noise trader is diminishing in income: high income households are smart money, lower income households are noise traders, with passive investors in between. Market data behave as predicted: high participation by the general population is a negative predictor of one year returns and is associated with low participation by very high income groups. The implications for the equity premium puzzle of the low returns earned by noise traders are discussed. Copyright 1997 by Ohio State University Press.

Suggested Citation

  • Kelly, Morgan, 1997. "Do Noise Traders Influence Stock Prices?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(3), pages 351-363, August.
    • Handle: RePEc:mcb:jmoncb:v:29:y:1997:i:3:p:351-63
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    14. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
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    Cited by:

    1. Cizek, P., 2007. "General Trimmed Estimation : Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaces DP 2007-1)," Other publications TiSEM eeccf622-dd18-41d4-a2f9-b, Tilburg University, School of Economics and Management.
    2. Kelly, Morgan, 1997. "Do Noise Traders Influence Stock Prices?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(3), pages 351-363, August.
    3. Čížek, Pavel, 2008. "General Trimmed Estimation: Robust Approach To Nonlinear And Limited Dependent Variable Models," Econometric Theory, Cambridge University Press, vol. 24(6), pages 1500-1529, December.
    4. Chen, Zhenhua & Liu, Zhenya & Teka, Hanen & Zhang, Yifan, 2022. "Smart money in China's A-share market: Evidence from big data," Research in International Business and Finance, Elsevier, vol. 61(C).
    5. Cizek, P., 2004. "Asymptotics of Least Trimmed Squares Regression," Discussion Paper 2004-72, Tilburg University, Center for Economic Research.
    6. Lee, Wayne Y. & Jiang, Christine X. & Indro, Daniel C., 2002. "Stock market volatility, excess returns, and the role of investor sentiment," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2277-2299.
    7. Bohl, Martin T. & Schuppli, Michael & Siklos, Pierre L., 2010. "Stock return seasonalities and investor structure: Evidence from China's B-share markets," China Economic Review, Elsevier, vol. 21(1), pages 190-201, March.
    8. Kling, Gerhard & Gao, Lei, 2008. "Chinese institutional investors' sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(4), pages 374-387, October.
    9. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
    10. Bohl, Martin T. & Schuppli, Michael & Siklos, Pierre L., 2010. "Stock return seasonalities and investor structure: Evidence from China's B-share markets," China Economic Review, Elsevier, vol. 21(1), pages 190-201, March.
    11. repec:zbw:bofitp:2009_020 is not listed on IDEAS
    12. Pavlo Blavatskyy & Ganna Pogrebna, 2010. "Reevaluating evidence on myopic loss aversion: aggregate patterns versus individual choices," Theory and Decision, Springer, vol. 68(1), pages 159-171, February.

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    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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