This paper considers the puzzle of increased trading volume around information releases through the lens of canonical models of disagreement. I use a unique data set of clicks on news by key finance professionals to simultaneously measure gradual information diffusion and differences of opinion. I find that neither channel subsumes the other and that the two are complementary in generating trading volume around news events. Their relative strengths depend on the characteristics of the underlying information: gradual information diffusion matters more for straightforward news, while differences of opinion play a larger role around textually ambiguous news. (JEL G12, G14, G41, D84) Received January 12, 2020; editorial decision: November 24, 2020 by Editor: Jeffrey Pontiff.