News, Influence, and the Evolution of Prices in Financial Markets

Abstract

Opinions by experts and media pundits that are widely disseminated in various media forms (both traditional outlets and online venues) constitute a major source of influence on investors. While a published view could be more accurate than the view of a typical investor, its influence displaces many independent views and hence has the potential to introduce a shared error. Our objective is to study the influence of published views on the evolution of prices by constructing a theoretical model and using empirical work to test and calibrate the model. Our probabilistic trading model demonstrates how the influence of published views creates patterns in prices and volume. Still, a wisdom of the crowds effect emerges endogenously in our framework and helps expunge such shared errors from the price. We use the timing of earnings announcements to test our model, and find evidence consistent with the theoretical predictions. The magnitude of the empirical effects is then used to calibrate the model, and our calibration exercise suggests that while the published opinion has only a modest degree of influence, its exact accuracy matters somewhat less than the extent of its influence.