A Model of Price, Volume, and Sequential Information

Gaiyan Zhang

College of Business Administration, University of Missouri—St. Louis, U.S.A.

This paper models the relationship between price and volume by tracking their adjustment path and speed in a world with heterogeneous investors. Motivated by widely observed information leakage in the stock market and fast-growing electronic communication networks, the model features sequential information and direct order matching. I show that both the content and the dissemination speed of information are incorporated in price changes and volume accumulations simultaneously. A convergence trading strategy is proposed based on a joint statistic of price and volume, which should help to improve the timing of market entry and exit. The model offers an explanation for the mixed evidence on the relationship between price change and volume and provides several testable hypotheses.

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