Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We study a matched sample of individual stock market forecasts consisting of both qualitative and quantitative forecasts. This allows us to test for the quality of forecast quantification methods by comparing quantified qualitative forecasts with actual quantitative forecasts. Focusing mainly on the widely used quantification framework advocated by Carlson and Parkin (1975), the so-called “probability approach”, we find that quantified expectations derived from the probability approach display a surprisingly weak correlation with the reported quantitative stock return forecasts. We trace the reason for this low correlation to the importance of asymmetric and time-varying thresholds, while individual heterogeneity across forecasters seems to play only a minor role. Hence, our results suggest that qualitative survey data may not be a very useful device for obtaining quantitative forecasts, and we suggest ways to remedy this problem when designing qualitative surveys.