Modeling financial analysts’ decision making via the pragmatics andsemantics of earnings calls
Abstract
Every fiscal quarter, companies hold earnings
calls in which company executives respond
to questions from analysts. After these calls,
analysts often change their price target recommendations, which are used in equity research reports to help investors make decisions. In this paper, we examine analysts’ decision making behavior as it pertains to the
language content of earnings calls. We identify a set of 20 pragmatic features of analysts’ questions which we correlate with analysts’ pre-call investor recommendations. We
also analyze the degree to which semantic and
pragmatic features from an earnings call complement market data in predicting analysts’
post-call changes in price targets. Our results show that earnings calls are moderately
predictive of analysts’ decisions even though
these decisions are influenced by a number of
other factors including private communication
with company executives and market conditions. A breakdown of model errors indicates
disparate performance on calls from different
market sectors.