Using monthly data for earnings forecasts by market analysts, this paper shows that the dispersion in forecasts has particularly strong predictive power for future aggregate stock returns at intermediate horizons. The results are robust (1) regardless of whether Newey-West or Hodrick corrected t-statistics are used, (2) when other forecasting or macroeconomic variables are included, (3) when different scaling variables are used for the dispersion measure, and (4) after correcting for finite sample biases. Furthermore, additional results suggest that the dispersion in analysts' forecasts can be interpreted as a measure of the differences in investors' expectations rather than the risk.
ASJC Scopus subject areas
- Business and International Management
- Economics and Econometrics
- Statistics, Probability and Uncertainty