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Dynamic Volume-Return Relation of Individual Stocks

Author

Listed:
  • Guillermo Llorente
  • Roni Michaely
  • Gideon Saar
  • Jiang Wang

Abstract

We examine the dynamic relation between return and volume of individual stocks. Using a simple model in which investors trade to share risk or speculate on private information, we show that returns generated by risk-sharing trades tend to reverse themselves while returns generated by speculative trades tend to continue themselves. We test this theoretical prediction by analyzing the relation between daily volume and first-order return autocorrelation for individual stocks listed on the NYSE and AMEX. We find that the cross-sectional variation in the relation between volume and return autocorrelation is related to the extent of informed trading in a manner consistent with the theoretical prediction.

Suggested Citation

  • Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2001. "Dynamic Volume-Return Relation of Individual Stocks," NBER Working Papers 8312, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:8312
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    References listed on IDEAS

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    1. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, Oxford University Press, vol. 108(4), pages 905-939.
    2. Scholes, Myron & Williams, Joseph, 1977. "Estimating betas from nonsynchronous data," Journal of Financial Economics, Elsevier, vol. 5(3), pages 309-327, December.
    3. Hasbrouck, Joel, 1991. " Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    4. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    5. Lee, Charles M C & Mucklow, Belinda & Ready, Mark J, 1993. "Spreads, Depths, and the Impact of Earnings Information: An Intraday Analysis," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 345-374.
    6. Morse, Dale, 1980. "Asymmetrical Information in Securities Markets and Trading Volume," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(05), pages 1129-1148, December.
    7. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Wiley Blackwell, vol. 17(31), pages 334-355, December.
    8. Blake LeBaron, "undated". "Persistence of the Dow Jones Index on Rising Volume," Working papers _006, University of Wisconsin - Madison.
    9. He, Hua & Wang, Jiang, 1995. "Differential Information and Dynamic Behavior of Stock Trading Volume," Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 919-972.
    10. Lo, Andrew W. & Craig MacKinlay, A., 1990. "An econometric analysis of nonsynchronous trading," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 181-211.
    11. Jiang Wang, 1993. "A Model of Intertemporal Asset Prices Under Asymmetric Information," Review of Economic Studies, Oxford University Press, vol. 60(2), pages 249-282.
    12. Lo, Andrew W & Wang, Jiang, 2000. "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 257-300.
    13. Charles M.C. Lee & Bhaskaran Swaminathan, 2000. "Price Momentum and Trading Volume," Journal of Finance, American Finance Association, vol. 55(5), pages 2017-2069, October.
    14. Lamoureux, Christopher G & Lastrapes, William D, 1990. " Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    15. Hasbrouck, Joel, 1988. "Trades, quotes, inventories, and information," Journal of Financial Economics, Elsevier, vol. 22(2), pages 229-252, December.
    16. Ajinkya, Bipin B. & Jain, Prem C., 1989. "The behavior of daily stock market trading volume," Journal of Accounting and Economics, Elsevier, vol. 11(4), pages 331-359, November.
    17. Conrad, Jennifer & Kaul, Gautam, 1988. "Time-Variation in Expected Returns," The Journal of Business, University of Chicago Press, vol. 61(4), pages 409-425, October.
    18. Jegadeesh N. & Titman S., 1995. "Short-Horizon Return Reversals and the Bid-Ask Spread," Journal of Financial Intermediation, Elsevier, vol. 4(2), pages 116-132, April.
    19. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    20. Easley, David & O'Hara, Maureen, 1987. "Price, trade size, and information in securities markets," Journal of Financial Economics, Elsevier, vol. 19(1), pages 69-90, September.
    21. Cready, William M. & Ramanan, Ramachandran, 1991. "The power of tests employing log-transformed volume in detecting abnormal trading," Journal of Accounting and Economics, Elsevier, vol. 14(2), pages 203-214, June.
    22. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    23. Linda Canina & Roni Michaely & Richard Thaler & Kent Womack, 1998. "Caveat Compounder: A Warning about Using the Daily CRSP Equal-Weighted Index to Compute Long-Run Excess Returns," Journal of Finance, American Finance Association, vol. 53(1), pages 403-416, February.
    24. Brennan, Michael J. & Subrahmanyam, Avanidhar, 1995. "Investment analysis and price formation in securities markets," Journal of Financial Economics, Elsevier, vol. 38(3), pages 361-381, July.
    25. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    26. Roll, Richard, 1984. " A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market," Journal of Finance, American Finance Association, vol. 39(4), pages 1127-1139, September.
    27. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. " Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
    28. Richardson, Gordon & Sefcik, Stephan E. & Thompson, Rex, 1986. "A test of dividend irrelevance using volume reactions to a change in dividend policy," Journal of Financial Economics, Elsevier, vol. 17(2), pages 313-333, December.
    29. Madhavan, Ananth & Sofianos, George, 1998. "An empirical analysis of NYSE specialist trading," Journal of Financial Economics, Elsevier, vol. 48(2), pages 189-210, May.
    30. Harrison Hong & Jiang Wang, 2000. "Trading and Returns under Periodic Market Closures," Journal of Finance, American Finance Association, vol. 55(1), pages 297-354, February.
    31. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
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    JEL classification:

    • G1 - Financial Economics - - General Financial Markets

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