Prediction Markets? The Accuracy and Efficiency of $2.4 Billion in the 2024 Presidential Election

Political prediction markets have exploded in size and influence, moving billions of dollars and shaping how journalists, donors, and voters interpret electoral odds. If these prices truly capture rational expectations, they should efficiently aggregate information about political outcomes. But do they? We analyze more than 2,500 political prediction markets traded across the Iowa Electronic Markets, Kalshi, PredictIt, and Polymarket during the final five weeks of the 2024 U.S. presidential campaign involving more than than two billion dollars in transactions to assess whether prices accurately and efficiently aggregate political information. While 93\% of PredictIt markets correctly predicted outcomes better than chance on the Election Night eve, the average accuracy was 78\% on Kalshi and 67\% on Polymarket among all active political markets. Even the most accurate markets showed little evidence of efficiency: prices for identical contracts diverged across exchanges, daily price changes were weakly correlated or negatively autocorrelated, and arbitrage opportunities peaked in the final two weeks before Election Day. Together, these findings challenge the view that prediction markets necessarily efficiently and accurately aggregate information about political outcomes and suggest that traders often react not only to political developments but also to the dynamics of the markets themselves.