Next we consider the impact of such misreaction to information by focusing on the implication for earnings momentum strategies. From a quantitative perspective, investors have traditionally relied upon earnings momentum factors to incorporate corporate news flow. A consistent strategy based on buying companies each month that have seen the most broker upgrades, and selling those with the most downgrades would have generated an annualized return of 9.1% pa since 1990. Earnings revisions strategies, however, typically do not identify the piece of information that has triggered the change in forecasts. We only observe the actions of analysts, rather than the motive behind analysts' actions.
Here we consider whether earnings expectations change following certain news flows and, if news does lead revisions, how can investors exploit this effect?
To proxy for changes in the market's expectation of earnings around news, we focus on revisions “clusters” (detailed below) using detailed analyst EPS revisions. Using individual analyst EPS forecasts we calculate the dates when revision clusters are formed. Our aim is to match revisions clusters to news items to understand what triggers changes in analyst forecasts.
Following Bagnoli, Levine, and Watts (2005a, b), we define a revisions cluster as occurring when at least three different analysts have revised their EPS forecasts within three trading days for a given company. Once a cluster begins, the end date ...