Abstract

We posit that the market views bad-news management earnings forecasts as more credible and value-relevant than good-news forecasts not because good-news forecasts tend to be biased, but rather because they are far noisier than bad-news forecasts. After controlling for noise, the difference in market response to good and bad news disappears. We demonstrate that bad-news forecasts show much lower dispersion around final earnings and, unlike good-news forecasts, they become considerably more accurate over time. These results provide direct support for the hypothesis that management perceives incentives to verify information when the news is bad as well as to delay bad-news announcements to allow time to gather additional information. These findings provide a rational explanation, not based on bias, for why on average the market’s reaction to good-news management earnings forecasts is weaker than to bad-news forecasts.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.