Prediction market platform Polymarket announced the formation of a dedicated research organization aimed at advancing scholarly understanding of how these markets operate and what they reveal about future events. The newly established Polymarket Institute represents an effort to build formal academic infrastructure around a field that has grown increasingly influential across multiple sectors.
Prediction markets have emerged as dynamic tools for measuring public sentiment and assessing probabilities in real time. Their applications now extend across electoral politics, international affairs, economic trends, technological developments, athletic competitions, and cultural phenomena. Journalists monitor these platforms to gauge shifting expectations, scholars analyze them as experimental forecasting mechanisms, and government institutions reference them as one component in broader risk assessment frameworks. As adoption continues to expand, the sector faces growing demand for rigorous, independent evaluation of how these markets perform at scale, how information propagates through them, and how their structural design influences outcomes.
The Institute intends to address these questions by creating programs that support independent scholarship and by developing open data resources. Its research priorities encompass the evaluation of forecast accuracy, the mechanics of information dissemination, market microstructure, the integrity of market resolution processes, cryptographic safeguards, the intersection of artificial intelligence with market dynamics, and the application of prediction markets to electoral and macroeconomic forecasting.
Leadership of the initiative has been assigned to two individuals with distinct areas of expertise. Brian Jabarian, who holds a faculty position at Carnegie Mellon University’s Heinz College of Information Systems and Public Policy, will direct the scientific program and shape its investigative priorities. Kai Brusch, who leads data operations at Polymarket, will manage the Institute’s day-to-day operations.
The organization has committed to operating within established academic standards, emphasizing transparency in data availability, methodological replicability, and unrestricted publication of findings. The platform has stated that it will not seek to influence research conclusions or require scholars to endorse particular perspectives on prediction markets. Participants in the fellowship program will retain full autonomy over their research questions, study design, analytical approaches, and publication decisions. However, to prevent conflicts of interest, fellows will be prohibited from conducting trades on Polymarket or comparable platforms for the duration of their affiliation with the program.
The Institute’s inaugural initiative is a global fellowship program targeting doctoral candidates whose work touches on prediction markets, forecasting methodologies, information economics, or market design. Recipients will receive financial support and access to proprietary market data to conduct independent studies within the Institute’s priority research domains. In addition to data access, the program will convene regular workshops where participants can develop research suitable for peer-reviewed publication.
Beyond the fellowship, the organization plans to broaden public access to market information through application programming interfaces that will cover market discovery tools, order book data, historical price series, on-chain aggregate statistics, and trading activity records. Where applicable, the Institute will publish datasets, analytical code, and replication materials in open repositories to enable external verification and further inquiry.
The creation of the Polymarket Institute reflects a broader effort to position prediction markets as legitimate instruments for gathering and distributing information about significant global developments. By funding independent scholarship and building transparent data infrastructure, the organization seeks to reinforce the scientific credibility of prediction markets as a category of information infrastructure.
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