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The Changing Nature of Institutional Stock Investing


  • Blume, Marshall E.
  • Keim, Donald B.


We document that institutional investors, particularly hedge funds, decreased their holdings of larger stocks from 1980 to 2010 and increased their holdings of smaller stocks. Since 1990 institutions have underweighted, relative to market weights, those stocks that make up the largest 40 percent of the value of the market, and since 2006 have overweighted the stocks that make up the smallest 20 percent of the market. The contrary findings in the literature that institutions overweight larger stocks and underweight smaller stocks (e.g., Gompers and Metrick (2001) and Bennett et al. (2003)) are due to the use of a linear relation between institutional ownership and the logarithm of market value. In fact, we show that this relation is nonlinear and resembles an inverted U. We discuss three factors that may have contributed to these changes in institutional holdings: better understanding of diversification; growing awareness of the small stock premium; and less efficient pricing of smaller stocks relative to larger stocks.

Suggested Citation

  • Blume, Marshall E. & Keim, Donald B., 2017. "The Changing Nature of Institutional Stock Investing," Critical Finance Review, now publishers, vol. 7(1), pages 1-41, March.
  • Handle: RePEc:now:jnlcfr:104.00000033

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    1. repec:eee:jfinec:v:126:y:2017:i:1:p:171-199 is not listed on IDEAS
    2. repec:eee:corfin:v:45:y:2017:i:c:p:342-359 is not listed on IDEAS
    3. repec:eee:jeborg:v:148:y:2018:i:c:p:46-65 is not listed on IDEAS

    More about this item


    Institutional investors; Institutional stock ownership; SEC 13F filings; Hedge funds; Gfficient pricing;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models


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