Pedro Bordalo, Nicola Gennaioli, Rafael La Porta, and Andrei Shleifer

Abstract

We revisit La Porta’s (1996) finding that returns on portfolios of stocks with the most optimistic analyst long term earnings growth forecasts are substantially lower than those for stocks with the most pessimistic forecasts. We document that this finding still holds, and present several further facts about the joint dynamics of fundamentals, expectations, and returns for these portfolios. We then propose a new approach to modeling belief formation and over-reaction to news that explains these facts, based on a portable psychological model of judgment by representativeness. This entails a learning model in which analysts forecast future fundamentals based on the history of earnings growth, but update excessively in the direction of states of the world whose objective likelihood rises the most in light of the news. Intuitively, fast earnings growth news predicts future Googles but not as many as analysts believe. The model delivers the empirical findings we initially document, and yields additional empirical predictions that distinguish it from both Bayesian learning and adaptive expectations. We test these predictions and find supportive evidence.

Rafael La Porta. Ph.D. en economía, Harvard University. Actualmente es profesor Noble Foundation en Tuck School of Business, Dartmouth College.  Es Research Associate en el National Bureau of Economic Research.

Su investigación se centra principalmente la protección de los inversores y en el gobierno corporativo, una disciplina conocida como "derecho y finanzas".