Prediction markets as a bridge between probabilistic hydrological forecasting and user beliefs

Probabilistic forecasts, when optimally calibrated, have the ability to encode both the current state of knowledge and the uncertainty about the future value of a variable. Forecasting systems developed by experts and trained on data, and optimized using proper scoring rules, are therefore well positioned to produce calibrated probabilistic forecasts. Conversely, prediction markets capture the collective state of knowledge of their participants in the form of market-implied probabilities.

If participants in such markets have access to a forecasting system, as well as additional information (e.g. local or contextual knowledge), they can trade against the forecast and thereby recalibrate the implied probabilities. This interaction has the potential either to improve forecast quality or, alternatively, to increase confidence in the forecasting system among the participants it outperforms. An additional benefit is that participation in prediction markets can help users and stakeholders develop better intuition for probabilistic forecasts and uncertainty.

In this presentation, we discuss several potential set-ups for connecting forecasting models, users, local experts, and armchair hydrologists through prediction and betting markets. We highlight theoretical connections to proper scoring rules and information-theoretic forecast evaluation, as well as practical considerations related to implementation using publicly available platforms, including their promises and limitations. Finally, the presentation will include an opportunity for the audience to put their (play-)money where their skill is and take a chance.