Date of Award
Spring 5-2026
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Behavioral and Computational Economics
First Advisor
David Porter
Second Advisor
Stephen Rassenti
Third Advisor
Ryan French
Abstract
In this paper, we report the results of experiments where subjects participate in a prediction market utilizing the Hanson automated market maker. The key distinction of our environment when compared with previous studies in the prediction market space is in the introduction of a conditional market that allows subjects to make conscious decisions to infuence market outcomes, and thus it investigates the quality of the decisions made by the subjects as opposed to the accuracy of the market prices. Utilizing dispersed “not-state” information, we evaluate whether subjects can accurately infer true states and maximize organizational welfare. Our initial baseline results with fully informed subjects demonstrate that while the mechanism can achieve perfect coordination and optimal decision making in certain sessions, the strategic environment is cognitively demanding and remains susceptible to coordination failures. Furthermore, we outline our experimental design for future treatment sessions that will introduce uninformed subjects to test the robustness of these decision markets against noise trader risk.
DOI
10.36837/chapman.000737
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Vershel, Leo (2026). Information Aggregation in Decision Markets under a Modified Hanson Market Maker. [Master's thesis, Chapman University]. Chapman University Digital Commons. https://doi.org/10.36837/chapman.000737