Information Aggregation in Decision Markets under a Modified Hanson Market Maker

<p>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. </p>

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Behavioral and Computational Economics

Year

2026

Author dc:creator

• Vershel, Leo

Contributors dc:contributor

• David Porter
• Stephen Rassenti
• Ryan French

• Decision Markets
• Hanson Market Maker
• Conditional Markets
• Market-based Governance
• Information Aggregation
• Not-states
• Behavioral Economics

Repository record dc:identifier

https://digitalcommons.chapman.edu/behavioral_and_computational_economics_theses/8

OAI identifier oai:identifier

oai:digitalcommons.chapman.edu:behavioral_and_computational_economics_theses-1007