Quality of Stock Price Predictions in Online Communities: Groups or Individuals?

Endress, Tobias (2017) Quality of Stock Price Predictions in Online Communities: Groups or Individuals? DBA thesis, University of Gloucestershire.

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Abstract

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.

Item Type: Thesis (DBA)
Thesis Advisors:
Thesis AdvisorEmailURL
Gear, Tonyagear@glos.ac.ukhttp://www.glos.ac.uk/faculties-and-schools/business/staff-profiles/pages/s2108363-anthony-gear.aspx
Ryan, Bobbryan@glos.ac.ukUNSPECIFIED
Uncontrolled Keywords: Group decision-making; Equity predictions; Stock prices; Financial analysis; Internet comunities
Subjects: H Social Sciences > HG Finance > HG4501 Investment, capital formation, speculation
Divisions: Schools and Research Institutes > Business School > Accounting and Finance
Depositing User: Susan Turner
Date Deposited: 05 Jun 2017 15:45
Last Modified: 05 Jun 2017 15:55
URI: http://eprints.glos.ac.uk/id/eprint/4674

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