Effects of task format on probabilistic forecasting of stock prices

Abstract

This study aims to explore the differences in various dimensions of forecasting accuracy that may result from the task format used to elicit the probabilistic forecasts. In particular, we examine the effects of using multiple-interval and dichotomous formats on the performance of portfolio managers' probabilistic forecasts of stock prices. Probabilistic forecasts of these experts are compared with those provided by semi-experts comprised of other banking professionals trained in portfolio management, as well as with forecasts provided by a novice group. The results suggest that the task format used to elicit the probabilistic forecasts has a differential impact on the performance of experts, semi-experts, and novices. The implications of these findings for financial forecasting are discussed and directions for future research are given.