Individual Financial Analysts Contribution In Earnings Per Share Forecasting

Abstract

Financial analysts are among the most influential group of users of financial accounting information. The majority of existing accounting research concerning financial analysts focuses on aggregated analysts' earnings forecasts rather than individual analysts' forecasts. Studies in accounting have documented the superiority of aggregated analysts' earnings forecasts relative to computer models. This is in contrast to the robust result from years of psychology/judgment & decision making (JDM) research that human predictions are inferior to computer model predictions. Humans can make a significant contribution to accurate forecasting in spite of cognitive limitations. Some skills people bring to bear are cue identification, rapid adaptability to environmental changes and the evaluation of qualitative factors. Computer models offer consistency and significant computational power. This research documents the incremental predictive ability of both individual financial analysts and computer models in forecasting earnings per share. It also provides evidence that both individual financial analysts' and computer models' incremental predictive ability varies between industries.