We examine whether finance professionals deviate from Bayes’ theorem on the processing of nondiagnostic information when forecasting quarterly earnings. Using field data from sell-side financial analysts and employing a regression discontinuity design, we find that analysts whose forecasts...

Bayesian learning provides a core concept of information processing in financial markets. Typically it is assumed that market participants perfectly know the quality of released news. However, in practice, news' precision is rarely disclosed. Therefore, we extend standard Bayesian learning...

This paper introduces a new information density indicator to provide a more comprehensive understanding of price reactions to news and, more specifically, to the sources of jumps in financial markets. Our information density indicator, which measures the abnormal amount of noisy “ticker”...