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Do Big Investors’ Trades Have Predictive Power? A Note on Istanbul Stock Market

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  • Numan Ülkü

Abstract

The net buying (selling) volume of the most net buyer (seller) brokers over a unit period is a widely followed piece of information in Istanbul Stock Market, which most market commentaries inaccurately refer to as “the net money in- or outflow”. It is, in fact, a proxy for big investors’ trading. In this note, we test whether this information has predictive value, whether market participants’ emphasis on this information is justified, or just an illusion. By doing so, we add to the literature on the relationship between big investors’ trading and stock returns, using a unique information set. Results suggest a significant contemporaneous association between the “net inflow” and current returns, but little predictive value

Suggested Citation

  • Numan Ülkü, 2008. "Do Big Investors’ Trades Have Predictive Power? A Note on Istanbul Stock Market," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 2(1), pages 85-108.
  • Handle: RePEc:bdd:journl:v:2:y:2008:i:1:p:85-108
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    References listed on IDEAS

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    1. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W., 1992. "The impact of institutional trading on stock prices," Journal of Financial Economics, Elsevier, vol. 32(1), pages 23-43, August.
    2. Keim, Donald B. & Madhavan, Ananth, 1995. "Anatomy of the trading process Empirical evidence on the behavior of institutional traders," Journal of Financial Economics, Elsevier, vol. 37(3), pages 371-398, March.
    3. Lang, Larry H P & Litzenberger, Robert H & Madrigal, Vicente, 1992. "Testing Financial Market Equilibrium under Asymmetric Information," Journal of Political Economy, University of Chicago Press, vol. 100(2), pages 317-348, April.
    4. Numan Ulku, 2001. "Behavioral Finance Theories and the Price Behavior of the ISE Around the Start of the Disinflation Programme," Istanbul Stock Exchange Review, Research and Business Development Department, Borsa Istanbul, vol. 5(17), pages 93-124.
    5. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    6. Chan, Louis K. C. & Lakonishok, Josef, 1993. "Institutional trades and intraday stock price behavior," Journal of Financial Economics, Elsevier, vol. 33(2), pages 173-199, April.
    7. Lee, Yi-Tsung & Lin, Ji-Chai & Liu, Yu-Jane, 1999. "Trading patterns of big versus small players in an emerging market: An empirical analysis," Journal of Banking & Finance, Elsevier, vol. 23(5), pages 701-725, May.
    8. 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.
    9. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    10. John R. Nofsinger & Richard W. Sias, 1999. "Herding and Feedback Trading by Institutional and Individual Investors," Journal of Finance, American Finance Association, vol. 54(6), pages 2263-2295, December.
    11. Sias, Richard W. & Starks, Laura T., 1997. "Return autocorrelation and institutional investors," Journal of Financial Economics, Elsevier, vol. 46(1), pages 103-131, October.
    12. Patrick J. Dennis & Deon Strickland, 2002. "Who Blinks in Volatile Markets, Individuals or Institutions?," Journal of Finance, American Finance Association, vol. 57(5), pages 1923-1949, October.
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    More about this item

    Keywords

    The Relationship Between Big Investors’ Trading and Returns; Predictive Value of Large Trades; Market Microstructure; Istanbul Stock Market;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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