This study estimates analyst-level stickiness in forecast updating and investigates its underlying determinants. Consistent with recent experimental findings on belief updating under cognitive noise, analysts often compress their forecasts toward an intermediate default, such as prior forecasts, when uncertain about forecast precision, leading to forecast stickiness. This tendency is more evident among analysts with characteristics associated with higher cognitive noise, including lower forecast accuracy, limited experience, and complex portfolio coverage, and during periods of heightened macroeconomic uncertainty. A model incorporating sticky updating behavior shows that the consensus revision by sticky analysts exhibits stronger return predictability than the traditional consensus revision by all analysts, with this predictability increasing with the proportion of sticky analysts covering a stock. Empirical evidence supports these predictions. Additionally, the return predictability of sticky revisions is especially pronounced when forecast difficulty is elevated. Analyst-level stickiness provides more information about the cross-section of stock returns than firm-level stickiness.

We report experiments on sender-receiver games with an incentive for senders to exaggerate. Subjects “overcommunicate”—messages are more informative of the true state than they should be, in equilibrium. Eyetracking shows that senders look at payoffs in a way that is consistent with a level-k model. A combination of sender messages and lookup patterns predicts the true state about twice as often as predicted by equilibrium. Using these measures to infer the state would enable receiver subjects to hypothetically earn 16–21 percent more than they actually do, an economic value of 60 percent of the maximum increment.