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Caught On Tape: Predicting Institutional Ownership With Order Flow

  • John Campbell

    (Harvard)

  • Tarun Ramadorai

    (Oxford)

  • Tuomo Vuolteenaho

    (Harvard)

Many questions about institutional trading behavior can only be answered if one can track institutional equity ownership continuously, yet institutional ownership data are only available on quarterly reporting dates. We infer institutional trading behavior from the “tape”, the Transactions and Quotes database of the New York Stock Exchange, by regressing quarterly changes in reported institutional ownership on quarterly buy and sell volume in different trade size categories. We find that institutions in aggregate demand liquidity, in that total buy (sell) volume predicts increasing (decreasing) institutional ownership. Institutions also tend to trade in large or very small sizes, in that buy (sell) volume at these sizes predicts increasing (decreasing) institutional ownership, while the pattern reverses at intermediate trade sizes that are favored by individuals. Our regression method predicts institutional ownership significantly better than the simple cutoff rules used in previous research.

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File URL: http://econwpa.repec.org/eps/fin/papers/0405/0405012.pdf
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Paper provided by EconWPA in its series Finance with number 0405012.

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Length: 36 pages
Date of creation: 06 May 2004
Date of revision:
Handle: RePEc:wpa:wuwpfi:0405012
Note: Type of Document - pdf; pages: 36
Contact details of provider: Web page: http://econwpa.repec.org

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  1. Randolph B. Cohen & Paul A. Gompers & Tuomo Vuolteenaho, 2002. "Who Underreacts to Cash-Flow News? Evidence from Trading between Individuals and Institutions," NBER Working Papers 8793, National Bureau of Economic Research, Inc.
  2. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2002. "Breadth of ownership and stock returns," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 171-205.
  3. Sugato Chakravarty, 2002. "Stealth-Trading: Which Traders' Trades Move Stock Prices?," Finance 0201003, EconWPA.
  4. Grinblatt, Mark & Keloharju, Matti, 2000. "The investment behavior and performance of various investor types: a study of Finland's unique data set," Journal of Financial Economics, Elsevier, vol. 55(1), pages 43-67, January.
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  7. 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.
  8. Tuomo Vuolteenaho, 2002. "What Drives Firm-Level Stock Returns?," Journal of Finance, American Finance Association, vol. 57(1), pages 233-264, 02.
  9. Mark Grinblatt & Matti Keloharju, 2000. "What Makes Investors Trade?," Yale School of Management Working Papers ysm146, Yale School of Management, revised 01 Nov 2001.
  10. Paul A. Gompers & Andrew Metrick, 1998. "Institutional Investors and Equity Prices," NBER Working Papers 6723, National Bureau of Economic Research, Inc.
  11. Daniel, Kent, et al, 1997. " Measuring Mutual Fund Performance with Characteristic-Based Benchmarks," Journal of Finance, American Finance Association, vol. 52(3), pages 1035-58, July.
  12. Easley, David & O'Hara, Maureen & Saar, Gideon, 2001. "How Stock Splits Affect Trading: A Microstructure Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(01), pages 25-51, March.
  13. Lee, Charles M C & Ready, Mark J, 1991. " Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-46, June.
  14. Finucane, Thomas J., 2000. "A Direct Test of Methods for Inferring Trade Direction from Intra-Day Data," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(04), pages 553-576, December.
  15. Russ Wermers, 1999. "Mutual Fund Herding and the Impact on Stock Prices," Journal of Finance, American Finance Association, vol. 54(2), pages 581-622, 04.
  16. Lee, Charles M. C. & Radhakrishna, Balkrishna, 2000. "Inferring investor behavior: Evidence from TORQ data," Journal of Financial Markets, Elsevier, vol. 3(2), pages 83-111, May.
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