Informed Minority Shapes Prediction Markets

A new study from London Business School and Yale University challenges the notion that prediction markets reflect crowd wisdom. Focusing on Polymarket, the researchers argue that a small cadre of well-informed traders drives most price discovery on these platforms.

According to the paper, roughly 3.5% of accounts generate the bulk of price discovery on Polymarket. The remaining majority trades actively but contributes little information; their losses tend to accrue to the informed minority. The study, authored by Roberto Gomez-Cram, Yunhan Guo, Theis Ingerslev Jensen, and Howard Kung and revised on April 25, relies on a sign-randomization approach that re-samples each account’s past trades 10,000 times to simulate profit and loss.

“Prediction market accuracy thus reflects the wisdom of an informed minority, not the wisdom of the crowd.”

Polymarket and other prediction markets have surged in crypto circles, with industry data suggesting monthly trading volumes commonly around $15 billion across markets spanning sports, elections, corporate results, and cultural events.

However, the rise of these platforms has drawn regulatory scrutiny amid concerns that insider trading could exploit confidential information. The authors note that prediction markets operate with less oversight than traditional securities markets, in part because many users are pseudonymous and contracts are narrowly defined around specific events.

“These features make prediction markets an attractive venue for trading on private information,” the authors write, highlighting a salient tension between market efficiency and potential misuse.

The “informed minority” and outsized profits

The study identifies the informed minority as comprising market makers and “skilled takers,” together capturing over 30% of total gains on prediction markets. On average, market-maker accounts earned about $11,830 per account in the period studied.

By contrast, roughly 69% of profit-takers fall into a category the authors call the “lucky winners,” who account for about 29% of all accounts. The remaining participants are the “unlucky losers,” who absorb the aggregate losses.

These dynamics echo earlier research suggesting that a small subset of traders can dominate profitability on Polymarket. A separate analysis published earlier this month by crypto analyst Andrey Sergeenkov estimated that just 0.015% of Polymarket traders achieve profits large and consistent enough to contemplate leaving their day jobs.

The broader takeaway is clear: while prediction markets can show high activity and liquidity, the actual informational value often hinges on a narrow group of participants rather than a democratic crowd signal.

Regulatory spotlight and market design implications

The authors’ findings arrive at a moment of intensified regulatory attention toward crypto prediction markets. Insiders trading on platforms like Polymarket and Kalshi has become a focal point for policymakers, who are weighing how to balance innovation with safeguards against confidential-information trading. The study notes that pseudonymity and narrowly defined contracts create structural vulnerabilities that could complicate enforcement and oversight.

For platform operators, the results raise practical questions about design choices, such as how to encourage broader participation without diluting the precision of price signals, and what kinds of disclosure or verification might enhance market integrity without eroding user trust.

Investors and users, meanwhile, should consider that a large portion of trading volume may reflect participation by less information-rich actors. As price discovery appears concentrated within a minority, capital decisions tied to these markets could be influenced more by information asymmetries than by the crowd-sourced wisdom some proponents hoped to see.

What to watch next

As regulators scrutinize insider-trading risk and as exchanges iterate on their market designs, readers should monitor how policy, enforcement, and platform innovations shape the accessibility and integrity of prediction markets. The core question remains whether safeguards can widen the circle of informed participation without dampening the very signals that keep these markets functional.

Source data and the study’s methodology are documented in the authors’ paper, which is available for reference as a revision published on April 25. For broader context on market volumes, industry data place monthly prediction-market activity around the $15 billion mark across the sector.

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