Analysts' Earnings Forecast Inefficiency Around the Merger Announcement Date

Abstract

We find strong evidence that the impact of biased near term analysts’ forecast on target stocks trading volume becomes larger when the change of information uncertainty increases around the merger announcement date. We also find that analysts systematically mis-react to target stock misvaluation and this empirical finding gives rise to the near term analysts’ forecast inefficiency around the merger announcement date. Moreover, we observe that analysts issue more optimistic earnings forecast toward target stocks when the change of information uncertainty increases around the merger announcement date. This can be explained by the analysts’ incentive to generate trading commissions around the merger announcement date. Our research further extends Chen and Jiang (2006)’s Bayesian approach in modeling the analysts’ weighting behavior and analyzing its subsequent cause of the near term forecast inefficiency. The paper uses portfolio analysis to point out the significant impact of near term analysts’ forecast inefficiency on the target stock cumulative abnormal return. The degree of impact of this forecast inefficiency becomes larger with the increase of the change of information uncertainty. Our research adds to the analysts’ conflict of interest literature in a context of mergers and acquisitions.