Individual Differences and Analyst Forecast Accuracy

This study examines the impact of unidentifiable individual differences among financial analysts on the cross section of their earnings forecast accuracy. Various psychological factors, such as decision style and personality traits, are documented to impact individuals' decision making. However, analysts' individual differences in such psychological factors are not captured by identifiable personal attributes employed in finance literature, such as years of experience. In this paper, we employ the concept of analyst fixed effects to control for unidentifiable individual differences. Examining the factors related to forecast accuracy, we document that controlling for these unidentifiable analyst-specific effects improves model fitting, and changes the explanatory power of some of the traditionally used independent variables in the literature. We confirm that the analyst's firm-specific experience, the intensity of following that a firm receives, and the forecast horizon are all significantly and consistently related to forecast accuracy. However, we find that analyst general experience and coverage complexity lose explanatory power when individual differences are controlled for. Furthermore, we document that analyst general experience is not monotonically associated with better accuracy, and that analysts only benefit from increased general experience during the early to middle stages of their career. Finally, we observe that when analysts' individual differences are controlled for, the boldness of a forecast revision is no longer a significant determinant of the improvement of accuracy. This is one of the first studies to highlight the necessity of recognizing individual differences among financial analysts. We argue that this treatment advances the literature of analyst forecast performance, and closely relates financial agents' decision making to psychology theories of decision style and personality