Price Discovery and Trading in Modern Prediction Markets

Abstract

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.

Keywords: Prediction Markets, Election Betting, Price Discovery, Polymarket, Kalshi, Arbitrage, Law of One Price, Return Prediction

JEL Classification: D47, G14, D83, C58, H11