Group decision-making and equity predictions are topics that are interesting for
academic research as well as for business purposes. Numerous studies have been conducted
to assess the quality of forecasts by financial analysts, but in general these studies still show
little evidence that it is possible to generate accurate predictions that in the long run create,
after transaction costs, profits higher than the market average. This thesis investigates an
alternative approach to traditional financial analysis. This approach is based on Internet
group decision-making and follows the suggestion that a group decision is better than the
decision of an individual. The research project follows a mixed-methods approach in the
form of a sequential study with a field experiment. Different groups—consisting of lay
people, but also financial professionals—were formed purposefully in different group
designs to generate equity forecasts. The field experiment was conducted following an e-
Delphi approach with online questionnaires, but also in-depth interviews with all
participants. Data from financial analysts was used to compare the predictions from the
groups with actual results of share prices.
The data from the experiment suggests that there are different variables, in terms of
the individual characteristics of the participants, which indicated significant impact on the
quality of equity predictions. The predictions of some participants (e.g. “PID-S-plus” rated
participants) are apparently of significantly higher accuracy. The findings from the study
indicate that intuition plays a significant role in the decision-making process not only for lay
people, but also for financial analysts and other financial professionals. However, there are
observable differences in the intuitive decision-making of lay people and experts. While it
was possible to observe that intuition is interpreted as “random guess” by poor predictors, it
was found that good predictors base their intuition on several factors—even including
fundamental and macroeconomic considerations. The findings of the experiments led to an
explanatory model that is introduced as the ‘Deliberated Intuition’ Model. The model of deliberated intuition which is proposed here views prediction as a process of practice which
will be different for each individual. The model proposes that a predictor will decide,
consciously or semi-consciously, when they feel ready to rely on gut-feeling, or to
undertake more analysis. Generally, it appears to contribute to a good prediction to think
about the problem in different ways and with various techniques. The experiment indicated
that (online-) groups are not per se better than individuals. The Deliberated Intuition Model
might help to prepare better group settings and improve prediction quality. Apparently a
combination of rational and intuitive techniques leads to the best prediction quality.