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Trading volume and firm size: A test of the information spillover hypothesis

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  • Robert A. Weigand

Abstract

This study investigates information transfer across firms by using the trading volume of large‐and small‐stock portfolios as a proxy for the flow of information in financial markets. I find bi‐directional Granger‐causality between the trading volume of large and small firms. The results do not support previous studies that report evidence of one‐way information transfer using the returns and variances of different‐sized firms. My findings suggest several explanations. Either information arrival in financial markets has a different impact on trading volume than it does on returns and variances, or certain information shocks may affect different firms more rapidly, with these shocks eventually influencing the volume of trade of all firms.

Suggested Citation

  • Robert A. Weigand, 1996. "Trading volume and firm size: A test of the information spillover hypothesis," Review of Financial Economics, John Wiley & Sons, vol. 5(1), pages 47-58, December.
    • Handle: RePEc:wly:revfec:v:5:y:1996:i:1:p:47-58
    DOI: 10.1016/S1058-3300(96)90005-1
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    1. Scholes, Myron & Williams, Joseph, 1977. "Estimating betas from nonsynchronous data," Journal of Financial Economics, Elsevier, vol. 5(3), pages 309-327, December.
    2. Beaver, Wh, 1968. "Information Content Of Annual Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 6, pages 67-92.
    3. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    4. Thornton, Daniel L & Batten, Dallas S, 1985. "Lag-Length Selection and Tests of Granger Causality between Money and Income," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 17(2), pages 164-178, May.
    5. Grammatikos, Theoharry & Saunders, Anthony, 1986. "Futures Price Variability: A Test of Maturity and Volume Effects," The Journal of Business, University of Chicago Press, vol. 59(2), pages 319-330, April.
    6. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    7. Stock, James H., 1987. "Measuring Business Cycle Time," Scholarly Articles 3425950, Harvard University Department of Economics.
    8. Huffman, Gregory W, 1992. "Information, Asset Prices, and the Volume of Trade," Journal of Finance, American Finance Association, vol. 47(4), pages 1575-1590, September.
    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. 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.
    11. Morgan, I G, 1976. "Stock Prices and Heteroscedasticity," The Journal of Business, University of Chicago Press, vol. 49(4), pages 496-508, October.
    12. Boudoukh, Jacob & Richardson, Matthew P & Whitelaw, Robert F, 1994. "A Tale of Three Schools: Insights on Autocorrelations of Short-Horizon Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 7(3), pages 539-573.
    13. Stock, James H, 1987. "Measuring Business Cycle Time," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1240-1261, December.
    14. 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.
    15. Crouch, R L, 1970. "A Nonlinear Test of the Random-Walk Hypothesis," American Economic Review, American Economic Association, vol. 60(1), pages 199-202, March.
    16. Granger, C. W. J., 1980. "Testing for causality : A personal viewpoint," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 329-352, May.
    17. Conrad, Jennifer & Gultekin, Mustafa N & Kaul, Gautam, 1991. "Asymmetric Predictability of Conditional Variances," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 597-622.
    18. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    19. Lev, B & Ohlson, Ja, 1982. "Market-Based Empirical-Research In Accounting - A Review, Interpretation, And Extension," Journal of Accounting Research, Wiley Blackwell, vol. 20, pages 249-322.
    20. repec:bla:jfinan:v:44:y:1989:i:1:p:1-17 is not listed on IDEAS
    21. Westerfield, Randolph, 1977. "The Distribution of Common Stock Price Changes: An Application of Transactions Time and Subordinated Stochastic Models," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(5), pages 743-765, December.
    22. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," The Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
    23. Brennan, Michael J & Jegadeesh, Narasimhan & Swaminathan, Bhaskaran, 1993. "Investment Analysis and the Adjustment of Stock Prices to Common Information," The Review of Financial Studies, Society for Financial Studies, vol. 6(4), pages 799-824.
    24. Jain, Prem C. & Joh, Gun-Ho, 1988. "The Dependence between Hourly Prices and Trading Volume," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(3), pages 269-283, September.
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