Price Discovery and Trading in Modern Prediction Markets

This study provides the first evidence on price discovery dynamics across modern prediction markets. We study a unique dataset of common contracts traded on leading prediction markets, Polymarket, Kalshi, PredictIt, and Robinhood, during the period leading up to the 2024 U.S. presidential election. We find that more liquid prediction markets substantially outperform polls in predicting subsequent election results, yet there are significant price disparities across platforms. Polymarket leads Kalshi in price discovery, particularly when liquidity and trading activity are high, implying economically meaningful arbitrage opportunities. Moreover, net order imbalance from large trades strongly predicts subsequent returns, and the market experiencing greater directional order flow from large trades tends to lead price discovery. These results underscore how platform structure, liquidity, and informed trading interact to shape trading and prices.