A recent scandal involving a Green Beret allegedly 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, informed group of traders who significantly 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 between 2023 and 2025. The findings indicate that a mere 3% of traders are responsible for the majority of price discovery, consistently predicting outcomes and driving prices in the right direction.
In contrast, the remaining 97% of traders largely fail to achieve this, instead providing liquidity and generating volume while collectively losing money to 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 randomizing the direction of the trades.
This allowed them to establish a benchmark for what each trader's profits would look like without any actual edge. The results show that among the biggest winners by raw profit, only 12% outperformed this 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 resolution, and they are also the first to react to new information, such as Federal Reserve announcements or corporate earnings. However, the same edge that makes these traders valuable to price discovery raises concerns when they are acting on non-public information. Both Polymarket and Kalshi have strict rules against trading on non-public information, and the paper highlights the risk of insider trades, which can move prices aggressively but are rare and concentrated in specific events. The study's findings challenge the conventional wisdom that prediction markets work due to the collective knowledge of their participants, instead suggesting that they are driven by the actions of a small, informed group of traders.