What does a prediction market actually measure: belief, probability, or truth?

Prediction markets measure tradeable belief, not objective truth. Prices reflect what participants are willing to risk capital on under current information and constraints.

Detailed Explanation

Tradeable belief:

• Prices represent the intersection of buyers and sellers willing to put capital at risk
• This is "skin-in-the-game" probability, not polled opinion

Not objective truth:

• Markets can be wrong—they aggregate available information, not perfect foresight
• Prices update as new information arrives, not as "truth" is revealed

Constraint effects:

• Liquidity constraints: Large traders can't fully express views without moving price
• Capital constraints: Some participants are sidelined, reducing information aggregation
• Regulatory constraints: Limits on who can trade or how much

Probability interpretation:

• Prices approximate probability under efficient market assumptions
• In practice, biases, fees, and structural factors distort this mapping

Common Scenarios

• Using prediction market prices as a "consensus forecast" for planning
• Comparing your private estimate to market-implied probability
• Observing how prices move after major news events
• Questioning whether low liquidity makes the price unreliable

Exceptions & Edge Cases

• If a market is dominated by a few large participants, then price reflects their beliefs, not broad consensus.
• If there are capital or participation limits, then informed traders may be unable to move price to "correct" level.
• If the event definition is ambiguous, then prices measure beliefs about resolution, not the underlying event.

Practical Examples

Market: "Will inflation exceed 4% in Q4?"

• Price at 55¢ reflects traders' willingness to bet at those odds
• Does not mean inflation will "probably" exceed 4%—it means that's the traded equilibrium
• If institutional traders are blocked from participating, price may not reflect best available estimates

Market: "Will CEO resign by year-end?"

• Price at 20¢ may reflect low probability or low interest/liquidity
• Thin order book means price could jump dramatically on small trades

Actionable Takeaways

• ✅ Ask what constraints might distort belief
• ✅ Focus on changes in probability over time
• ✅ Examine liquidity and depth alongside price
• ✅ Treat prices as probabilistic signals, not facts