Linear and nonlinear Granger causality tests are used to examine the dynamic relation between daily Dow Jones stock returns and percentage changes in New York Stock Exchange trading volume. We find evidence of significant bidirectional nonlinear causality between returns and volume. We also examine whether the nonlinear causality from volume to returns can be explained by volume serving as a proxy for information flow in the stochastic process generating stock return variance as suggested by Clark's (1973) latent common-factor model. After controlling for volatility persistence in returns, we continue to find evidence of nonlinear causality from volume to returns. THIS ARTICLE USES LINEAR and nonlinear Granger causality tests to examine the dynamic relation between daily aggregate stock prices and trading volume. Causality tests can provide useful information on whether knowledge.of past stock price movements improves short-run forecasts of current and future movements in trading volume, and vice versa. We provide empirical support for the argument made by Gallant, Rossi, and Tauchen (1992) that more can be learned about the stock market through studying the joint dynamics of stock prices and trading volume than by focusing only on the univariate dynamics of stock prices. In addition, our analysis produces stylized facts about how daily aggregate stock prices and trading volume are intertemporally related, which may prove useful to future theoretical and empirical work on the stock market.

Linear and nonlinear Granger causality tests are used to examine the dynamic relation between daily Dow Jones stock returns and percentage changes in New York Stock Exchange trading volume. We find evidence of significant bidirectional nonlinear causality between returns and volume. We also examine whether the nonlinear causality from volume to returns can be explained by volume serving as a proxy for information flow in the stochastic process generating stock return variance as suggested by Clark's (1973) latent common‐factor model. After controlling for volatility persistence in returns, we continue to find evidence of nonlinear causality from volume to returns.

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Abstract. Linear asset-pricing relationsAcknowledgments. We wish to thank the participants at earlier presentations of this paper for their helpful comments. We also wish to thank Pedro de Lima, Robert Flood, Ted Jaditz, Jonathan Jones, Francis Longstaff, Bruce Mizrach, and anonymous referees for comments. We also thank Janet Shelley for her assistance with the manuscript.