This study develops a framework to compare the ability of alternative earnings forecast approaches to capture the market expectation of future earnings. Given prior evidence of analysts' systematic optimistic bias, we decompose earnings surprises into analysts' earnings surprises and adjustments...

An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the...

The business press generally reports news in quarterly earnings announcements based on the difference between actual earnings and two salient benchmarks: earnings of the same quarter in the previous year, and a consensus drawn from a distribution of forecasts by financial analysts. We evaluate...

This paper investigates whether sell-side equity analysts fully incorporate the future earnings implications of really dirty surplus (RDS) into their earnings forecasts. RDS refers to gains or losses from contingent equity transactions settled at prices other than the fair value. We find that...

We investigate how the arrival of Estimize, a provider of crowdsourced earnings forecasts, impacts IBES analysts' forecast timeliness and facilitates market efficiency. We find that IBES analysts become more responsive to earnings announcements and start issuing their quarterly forecasts earlier...

Prior research on financial analyst' quarterly earnings forecasts has documented serial correlation in forecast errors. This paper examines the way serial correlation in quarterly earnings forecast errors varies with firm and analyst attributes such as the firm's industry and the analyst's...