Study Reveals Only a Small Percentage of Traders Drive Prediction Market Accuracy

A recent scandal involving a Green Beret arrested for betting on a classified U.S. raid may be more than an isolated incident, as a new study suggests it could be an extreme example of the small group of informed traders who actually influence prices on Polymarket, while the majority of traders incur losses. The study, conducted by researchers from London Business School and Yale, analyzed 1.72 million accounts and $13.76 billion in trading volume on Polymarket from 2023 to 2025. The findings indicate that a mere 3% of traders are responsible for most price discovery, consistently predicting outcomes and moving prices in the right 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, reversing the direction of the trades. The results showed that among the biggest winners, only 12% outperformed the simulated benchmark, and many apparent winners did not sustain their performance over time. The activity of skilled traders improves market accuracy, particularly in the final stages before an event's resolution. They are also the first to react to new information, adjusting their positions in response to events such as Federal Reserve announcements or corporate earnings. However, the same edge that makes skilled traders valuable to price discovery raises concerns when they possess non-public information. The study highlights the risk of insider trading, citing the example of the U.S. removal of Nicolás Maduro from power in Venezuela. In the days leading up to the operation, three newly created Polymarket accounts placed unusually large bets on the contract, collectively making over $630,000 when the event occurred. While there is no evidence of wrongdoing, the incident underscores the potential for insider trades to manipulate prices. The research challenges the notion that prediction markets work due to the collective knowledge of their participants, instead suggesting that they work because of the presence of informed traders.