“the public forecast drifts toward the market four times further than the market drifts toward it”
Five years of Kalshi temperature markets across seven U.S. cities, read hour by hour as a probability distribution over tomorrow's daily high. At the end of the market's first hour of trading its root-mean-square error sits about 10 percent below the National Blend of Models, the most accurate single public product, and it still leads by 11 percent at the NBM's final bulletin on the target morning. The advantage is largest where forecasting is hardest, in Philadelphia, Chicago, and New York in winter when cold-front timing matters, and nearly vanishes in Miami where tropical air keeps highs predictable. An event study settles the direction of information flow: public forecast revisions travel toward the market roughly four times further than the market travels toward them, so prices do not jump when the National Weather Service publishes.
Extensive technical background assumed
Platforms mentioned: Kalshi