A recent scandal involving a Green Beret accused of 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 but influential group of traders who drive price movements on platforms like Polymarket, while the broader crowd incurs 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 between 2023 and 2025. The findings indicate that a mere 3% of traders are responsible for the majority of price discovery, consistently making accurate predictions 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, using the same markets, moments, and dollar amounts, but with the direction of the bet determined by a coin flip. The results showed that only 12% of the biggest winners by raw profit consistently outperformed the benchmark, while many apparent winners were found to be merely lucky. The study also found that when skilled traders account for a larger share of trading, prices tend to move closer to the correct outcome, particularly in the final stages before resolution. Moreover, these traders are often the first to react to new information, such as Federal Reserve announcements or corporate earnings, whereas other traders exhibit little consistent reaction.
The research raises important questions about the role of non-public information in trading and the potential risks associated with insider trades. While both Polymarket and Kalshi have stated that trading on non-public information is strictly against their rules, the study highlights the challenges of detecting and preventing such activities. The findings have significant implications for our understanding of how prediction markets work, suggesting that their accuracy is driven by the actions of a small group of informed traders rather than the collective wisdom of the crowd.