Research Reveals Only a Small Group of Informed 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, according to a new study. The research suggests that this individual may be an extreme example of the small group of informed traders who actually influence prices on platforms like Polymarket, while the majority of participants 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 the majority of price discovery, consistently predicting outcomes and moving prices in the right direction. In contrast, the remaining 97% of traders tend to lose money, providing liquidity and generating volume but ultimately being on the wrong side of trades against the informed minority. To distinguish between skill and luck, the researchers simulated each trader's bets 10,000 times, using the same markets, moments, and dollar amounts but with the direction of the trade determined by a coin flip. The results showed that among the biggest winners, only 12% consistently outperformed the benchmark, while many apparent winners were found to be lucky rather than skilled. The study also found that when skilled traders account for a larger share of trading, prices move closer to the correct outcome, especially in the final stages before resolution. However, the same edge that makes skilled traders valuable to price discovery raises concerns when they are trading on non-public information. The researchers cite the example of the U.S. removal of Nicolás Maduro from power in Venezuela, where three newly created Polymarket accounts placed unusually large bets on the contract before the operation, collectively making over $630,000. While there is no evidence of wrongdoing in this case, the study highlights the risk of insider trades and the need for platforms to enforce their rules against trading on non-public information. Ultimately, the findings challenge the idea 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.