Study Reveals Only a Fraction of Traders Contribute to Prediction Market Accuracy

A recent scandal involving a Green Beret arrested for betting on a classified US raid may be more than an isolated incident, according to a new study. The research suggests that this individual may represent an extreme example of a small group of informed traders who significantly influence prices on platforms like Polymarket, while the majority of users incur losses. The study, conducted by researchers from the London Business School and Yale, analyzed 1.72 million accounts and $13.76 billion in trading volume on Polymarket between 2023 and 2025. The findings indicate that just 3% of traders are responsible for the majority of price discovery, consistently predicting outcomes and moving prices in the correct direction. In contrast, the remaining 97% of traders primarily provide liquidity and generate volume, but ultimately end up on the losing side of trades against the informed minority. To distinguish between skill and luck, the researchers simulated each trader's bets 10,000 times, keeping all parameters constant except the direction of the trade. The results showed that among the biggest winners, only 12% consistently outperformed the simulated benchmark, while many apparent winners did not sustain their performance over time. The study also found that when skilled traders account for a larger share of trading activity, market accuracy improves, particularly in the period leading up to the resolution of an event. However, the same edge that makes skilled traders valuable to price discovery raises concerns when they may be acting on non-public information. Both Polymarket and Kalshi have stated that trading on non-public information is strictly prohibited. The researchers cite the example of the US removal of Nicolás Maduro from power in Venezuela, where three newly created accounts placed unusually large bets on a contract related to the event before the price moved. While there is no evidence of wrongdoing, the incident highlights the risk of insider trading in prediction markets. Overall, the study challenges the notion that prediction markets work due to the collective knowledge of their participants, instead suggesting that they are driven by the actions of a small group of informed traders.