A Market for Trading Forecasts: A Wagering Mechanism

Aitazaz Ali Raja*, Pierre Pinson, Jalal Kazempour, Sergio Grammatico

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

In many areas of industry and society, e.g., energy, healthcare, logistics, agents collect vast amounts of data that they deem 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, we envision a platform for improving predictions via implicit pooling of private information in return for possible remuneration. Specifically, we design a wagering-based forecast elicitation market platform, where 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. We propose a payoff mechanism and prove that it satisfies several desirable economic properties, including those specific to electronic platforms. Furthermore, we discuss the properties of the forecast aggregation operator and scoring rules to emphasise their effect on the sellers’ payoff. Finally, we provide numerical examples to illustrate the structure and properties of the proposed market platform.
Original languageEnglish
JournalInternational Journal of Forecasting
Volume40
Issue number1
Pages (from-to)142-159
ISSN0169-2070
DOIs
Publication statusPublished - 2024

Keywords

  • Mechanism design
  • Wagering mechanism
  • Predictive distribution
  • Elicitation of probabilities
  • Value of forecast
  • Scoring rules

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