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

Detailed Explanation

A prediction market price is best understood as a consensus probability shaped by incentives, information, and market structure. It does not claim to represent objective truth or certainty, but rather the weighted belief of participants who are willing and able to trade. This distinction matters because market prices embed not only expectations about the real world, but also factors such as risk tolerance, liquidity, fees, regulatory constraints, and ambiguity around resolution. As a result, a market can be directionally informative while still being imperfect or temporarily wrong. The value of the signal lies less in whether the market is “right” at every moment and more in how probabilities change as new information arrives.

Common Scenarios

• Interpreting election probabilities as forecasts
• Comparing market odds to internal models
• Explaining market prices to non-technical stakeholders
• Assessing confidence vs uncertainty in outcomes

Exceptions & Edge Cases

• If liquidity is very low, then prices may reflect noise more than belief.
• If traders are hedging rather than speculating, then price embeds risk transfer, not pure expectation.
• If resolution rules are unclear, then prices reflect rules risk as much as outcome likelihood.

Practical Examples

• A market trades at 80%, but only small size is available.
• The price signals directional confidence, but not strong conviction.

Actionable Takeaways

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

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