Probabilistic forecasts of stock prices and earnings: The hazards of nascent expertise

Abstract

Undergraduate and graduate students in finance courses made probabilistic forecasts of the quarterly changes in the stock prices and earnings of publicly traded companies. Consistent with previous findings (Staël von Holstein, 1972), the overall accuracy of both price and earnings forecasts was very modest; subjects would have been more accurate had they predicted that price changes were equally likely to fall into any of the specified ranges. Also consistent with earlier suggestions of “inverted” expertise effects, undergraduate subjects were more accurate than graduate subjects. Decompositional analyses of subjects' judgments were consistent with the hypothesis that graduate students' relatively poor accuracy was affected by their greater tendency to report forecasts that varied from one stock to the next instead of the same forecast for every one. It is argued that the most plausible explanation is that the graduate subjects responded to cues they thought were predictive, but which actually were not. However, it cannot be ruled out completely that the graduate subjects attended to truly predictive cues, but were simply unable to use them appropriately.