Are prediction markets accurate compared to polls or expert forecasts?

Detailed Explanation

Prediction markets differ from polls and expert forecasts in how information is collected and weighted.

• Polls sample opinions, often with methodological lag, response bias, and fixed assumptions.
• Expert forecasts rely on limited viewpoints and may overweight narratives or reputational risk.
• Prediction markets force participants to put capital at risk, which penalizes overconfidence and rewards accuracy.

Prices continuously update as:

1. New information arrives
2. Traders reassess probabilities
3. Capital flows toward better estimates

This creates a self-correcting mechanism: incorrect beliefs are costly, while correct beliefs are profitable. Over time, this tends to push prices toward better-calibrated probabilities—particularly for:

• Binary outcomes
• Clearly defined events
• Markets with reasonable liquidity

Markets tend to outperform polls near the end of an event timeline, when information is richest and incentives are strongest.

Common Scenarios

• National elections vs polling averages
• Central bank decisions vs economist surveys
• Geopolitical escalation risk vs media narratives
• Corporate approvals vs analyst commentary

Exceptions & Edge Cases

• If liquidity is low, then accuracy can degrade due to noise or manipulation.
• If the contract resolution is ambiguous, then price reflects rules risk, not reality.
• If participation is ideologically skewed, then bias may persist longer.

Practical Examples

• Two weeks before an election, polls show a tied race.
• Prediction markets imply a 65% chance for Candidate A.
• On election night, Candidate A wins—markets incorporated turnout, fundraising, and regional signals faster than polls.

Actionable Takeaways

• ✅ Use markets as a probability layer, not a crystal ball
• ✅ Compare market probabilities vs poll averages for divergence
• ✅ Trust markets more as resolution approaches
• ✅ Discount thin or poorly specified markets

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