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. The authors find evidence of significant bidirectional nonlinear causality between returns and volume. They 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 P. Clark's (1973) latent common-factor model. After controlling for volatility persistence in returns, the authors continue to find evidence of nonlinear causality from volume to returns.

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.