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Extracting information from trading volume

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  • Dominique Dupont

Abstract

This paper shows how to infer information about any random variable from trading volume, assuming that the random variable and the traders' demands are symmetrically (and then normally) distributed around zero. The volume-based conditional expectation of such a random variable is zero, while the covariance between its absolute value and volume is positive if the variable is jointly normally distributed with the traders' demands. In that case, numerical examples indicate that the volume-based conditional probability of extreme asset value realizations (positive or negative) increases with volume. These results, developed in a market-clearing framework, apply also to market-making frameworks. Finally, the paper develops a simple model where transaction costs can generate a positive covariance between price and trading volume.

Suggested Citation

  • Dominique Dupont, 1997. "Extracting information from trading volume," Finance and Economics Discussion Series 1997-20, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:1997-20
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    References listed on IDEAS

    as
    1. Michael J. Fleming & Eli M. Remolona, 1996. "Price formation and liquidity in the U.S. treasuries market: evidence from intraday patterns around announcements," Research Paper 9633, Federal Reserve Bank of New York.
    2. Assogbavi, T. & Khoury, N. & Yourougou, P., 1995. "Short interest and the asymmetry of the price-volume relationship in the Canadian stock market," Journal of Banking & Finance, Elsevier, vol. 19(8), pages 1341-1358, November.
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    Cited by:

    1. Dominique Dupont, 1997. "Trading volume and information distribution in a market-clearing framework," Finance and Economics Discussion Series 1997-41, Board of Governors of the Federal Reserve System (U.S.).

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    Keywords

    Information theory;

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