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Chronicles

The story behind the story

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Researchers find Kalshi and Polymarket bettors can more accurately predict economic data, earnings, and political events than analysts, likely due to incentives

Economists at top banks and investment firms who command high salaries to divine the direction of the economy expect …

New York Times Lydia DePillis

Context & Ripple Effects

Kalshi and Polymarket have been building the liquidity and distribution needed for prices to function as widely watched signals: Kalshi had been pursuing brokerage access for its contracts, while later coverage described sharply rising platform activity. The research supplies a performance-based argument for treating those prices as more than gambling outputs.

The result matters because both platforms are competing to make their contract prices useful beyond the trade itself. Their recent attraction of professional gamblers using market-style strategies underscores how participation quality can become part of that product proposition.

First-order effects

  • The findings strengthen Kalshi’s and Polymarket’s case to users, media and institutional audiences that their prices can be a timely benchmark for economic releases, earnings and political outcomes.
  • Professional analysts face a clearer comparative challenge: market-implied probabilities may become a more prominent reference point alongside published forecasts, especially where incentives reward calibrated accuracy.

Second-order effects

  • Financial-data, brokerage and research providers have reason to test prediction-market probabilities as an input to dashboards and event-risk workflows, increasing the value of reliable market access and price feeds.
  • Competition between Kalshi and Polymarket shifts further toward attracting informed traders and sustaining liquid contracts; deeper participation can improve price discovery, while thin or concentrated trading would limit that advantage.

Third-order effects

  • If the accuracy result persists across events and market conditions, prediction markets could evolve from niche wagering venues into an additional layer of public forecasting infrastructure—an instance of prediction-market platformization.
  • That transition would put more emphasis on market integrity, participant concentration and the distinction between informative prices and attention-driven trading, particularly as platforms extend into consequential real-world events.

The trend: Prediction markets are competing to turn financially incentivized collective judgment into a reusable information product, not merely a betting product.