The Best of Times, the Worst of Times: Testing which Behavioral Biases Affect Analyst Forecasts

Abstract

Mood-induced optimism, cognitive inaccuracy, and distraction can affect analyst forecasts. This study compares and contrasts these influences. The novelty of our approach is that we first show that these behavioral biases have different implications for analysts' forecast errors conditioned on the errors being positive and negative. We then use proxies for positive and negative moods to empirically test the support for each of these biases. Consistent with cognitive precision, we find that analysts make less (more) accurate forecasts when they are in positive (negative) moods. We further show that these results are driven neither by sentiment associated with contemporaneous economic or market conditions nor by under-or overreaction to more bad news released on days immediately before weekends or holidays. there were 77,000 and 59,500 Google Scholar hits for "accuracy of analyst forecasts" and "analyst forecast errors", respectively. 2 This example compares a mood-affected analyst with an unbiased analyst. However, a similar argument applies if we compare an analyst's forecast errors when he is exposed to moodaffecting events with his average positive and negative forecast errors. The latter comparison is more consistent with our empirical methodology, which considers "within variation" and subsumes time-invariant analyst effects with analyst fixed effects.