Purpose: This study aims to investigate the behavior of sell-side analysts covering firms that are about to experience breaks in strings of consecutive quarterly earnings increases. Design/methodology/approach: The authors estimate the likelihood of analysts predicting a break by using logit regressions for nearly half a million earnings per share forecasts issued by individual analysts from 1992 to 2017. Findings: The authors find that analysts can predict breaks in earnings strings by issuing less favorable earnings estimates ahead of a break announcement. The probability of detecting a break is higher for longer and more severe breaks, for more skillful analysts and for firms with richer information environments. The authors find that analysts’ warnings are heeded by investors and result in less severe reactions to break announcements. Originality/value: Breaks in strings of earnings increases are situations in which information asymmetry exists and could be mitigated by information intermediaries such as sell-side analysts. Therefore, it is important to examine whether analysts have any informational advantages or disadvantages over insiders and institutional investors in the quarters prior to breaks in strings and whether they communicate such information to the market in a timely and accurate manner, thus reducing information asymmetry by “leveling the field” across the investment community.
All Science Journal Classification (ASJC) codes
- Economics, Econometrics and Finance(all)