“Show Me!” The Informativeness of Images

Abstract

We introduce the concept of visual informativeness in annual reports and innovate by using machine-learning algorithms to construct visual informativeness measures. We create a novel measure of content reinforcement, representing the information content investors can extract from images, complementing and reinforcing particulars contained in textual narrative. An increase in visual prevalence and in the degree to which images convey reinforcing information is associated with greater (lower) analyst forecast accuracy (dispersion) in subsequent quarters, and lower risk. Firms increase the use of visuals when facing an exogenous drop in analyst coverage. Importantly, visual informativeness facilitates information assimilation.

Keywords: Visual informativeness, annual reports, images, image information content, information dissemination, content reinforcement, analyst forecast accuracy, analyst dispersion

JEL Classification: D83, G12, G14, M41