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Digital Society Initiative


«PREMIA – A Prediction Market with Integrated Algorithms» is an open environment for the research community in Zurich to forecast socially relevant phenomena.

Prediction markets are virtual stock markets, which use the information contained in market values to make forecasts. By today, these market platforms exclusively rely on the implicit knowledge of groups of humans either in the form of large crowds or expert panels. Hence, this project aims to develop and implement a prediction market with integrated trading algorithms that combines human expertise with artificial intelligence and apply it to a broad range of research questions.

Here you can find a short interview about the project.

Project duration: 01.09.2022 - 31.12.2023

Website: Premia

Contact: Prof. Dr. Carolin Strobl

Project Team

Oliver Strijbis

Prof. Dr. Oliver Strijbis

Oliver Strijbis is SNF Assistant Professor for Political Science at the University of Zurich and an affiliated Professor of Politics at the Franklin University Switzerland. He is head of the research project «The Effect of Campaign Events on Direct Democratic Decisions: Evidence from Prediction Markets». His research focuses on prediction markets, political behavior, migration, and nationalism.

Carolin Strobl

Prof. Dr. Carolin Strobl

Carolin Strobl is Professor for Psychological Methods, head of the statistical consulting unit of the Department of Psychology and steering committee member of the Center for Reproducible Science. Her research focuses on Item Response Theory and Machine Learning.

Marc Wildi

Prof. Dr. Marc Wildi

Marc Wildi is Professor of Econometrics at the Zurich University of Applied Sciences. His research interests are about forecasting, real-time signal extraction, business-cycle analysis, algorithmic trading and risk management. His recent work emphasizes hybrid approaches (mixing real-time filter designs and generic trading concepts) as well as explainability (XAI) of computationally intensive approaches (NN) in the context of longitudinal data (time series).