Print Email Facebook Twitter A market for trading forecasts Title A market for trading forecasts: A wagering mechanism Author Raja, A.A. (TU Delft Team Sergio Grammatico) Pinson, Pierre (Imperial College London; Technical University of Denmark) Kazempour, Jalal (Technical University of Denmark) Grammatico, S. (TU Delft Team Sergio Grammatico; TU Delft Team Bart De Schutter) Date 2024 Abstract In many areas of industry and society, including energy, healthcare, and logistics, agents collect vast amounts of data that are deemed proprietary. These data owners extract predictive information of varying quality and relevance from data depending on quantity, inherent information content, and their own technical expertise. Aggregating these data and heterogeneous predictive skills, which are distributed in terms of ownership, can result in a higher collective value for a prediction task. In this paper, a platform for improving predictions via the implicit pooling of private information in return for possible remuneration is envisioned. Specifically, a wagering-based forecast elicitation market platform has been designed, in which a buyer intending to improve their forecasts posts a prediction task, and sellers respond to it with their forecast reports and wagers. This market delivers an aggregated forecast to the buyer (pre-event) and allocates a payoff to the sellers (post-event) for their contribution. A payoff mechanism is proposed and it is proven that it satisfies several desirable economic properties, including those specific to electronic platforms. Furthermore, the properties of the forecast aggregation operator and scoring rules are discussed in order to emphasize their effect on the sellers’ payoff. Finally, numerical examples are provided in order to illustrate the structure and properties of the proposed market platform. Subject Elicitation of probabilitiesMechanism designPredictive distributionScoring rulesValue of forecastWagering mechanism To reference this document use: http://resolver.tudelft.nl/uuid:213602b7-9f32-496b-b262-586560ff46a6 DOI https://doi.org/10.1016/j.ijforecast.2023.01.007 ISSN 0169-2070 Source International Journal of Forecasting, 40 (1), 142-159 Part of collection Institutional Repository Document type journal article Rights © 2024 A.A. Raja, Pierre Pinson, Jalal Kazempour, S. Grammatico Files PDF 1_s2.0_S0169207023000079_main.pdf 2.56 MB Close viewer /islandora/object/uuid:213602b7-9f32-496b-b262-586560ff46a6/datastream/OBJ/view