Does the empirical accuracy of prediction markets derive from crowd wisdom or an informed few? In their April 2026 paper entitled "Prediction Market Accuracy: Crowd Wisdom or Informed Minority?", Roberto Cram, Yunhan Guo, Theis Jensen and Howard Kung investigate why prediction markets exhibit accuracy. Specifically, they compare the distribution of actual trade directions with a hypothetical distribution of random trades, and thereby classify traders as:
- Market makers, who provide liquidity by posting limit orders.
- Skilled traders, winners whose gains cannot be attributed to chance.
- Other winners and other losers, who respectively earn positive and negative returns but whose performance is not statistically significant.
- Persistent losers, who consistently and significantly lose.
Using the Polymarket universe of transactions and accounts with at least 10 trades across propositions created after the beginning of January 2023 and resolved by the end of December 2025, they find that:
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