Expert Prediction Markets for Climate Risks

Abstract

The market for climate forecasts suffers from three major challenges: the fragmentation of relevant expertise, the information asymmetry inherent in long-range prediction when forecaster track records are not available, and the ‘circularity’ of the interdependence between physical climate predictions and future greenhouse gas concentrations.

These three issues can be simultaneously and elegantly addressed using prediction markets. Prediction markets are similar to financial futures markets, or even sport betting, but instead of being designed to transfer risks, or for entertainment, they are specifically intended to elicit and aggregate disparate information. Prediction markets have been used to predict things such as the outcomes of elections and the reliability of psychological research but attempts to use them for predicting climate have met with mixed results due to the low liquidity typically encountered by markets for specialized topics.

The liquidity problem can be tackled using automated market making algorithms and this approach will be illustrated with examples of successful climate-related prediction markets. How such markets can be used for long-range climate prediction, addressing the problem of circularity, will also be explained.

Date
Sep 18, 2024 2:00 PM — 3:00 PM
Location
University of Reading
Room 113, Mathematics Building, Pepper Lane, Reading, RG6 6AX, UK

*Image: Climate Stripes, created by Professor Ed Hawkins at the University of Reading in 2018, projected onto the White Cliffs of Dover.

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