How do I read a prediction market price as a probability?

Detailed Explanation

1. Binary contract mapping:
   • “Yes” share pays $1 if Yes, $0 if No
   • Fair price ≈ probability of Yes
2. Implied probability:
   • Probability ≈ Price / $1 payout
3. Why it’s approximate:
   • Fees, spreads, and risk preferences can push price away from “true” probability.
4. Why it matters:
   • It’s a fast way to compare crowd belief vs your model.

Common Scenarios

• Comparing market odds to your internal estimate
• Tracking how probability moves after new information
• Monitoring “surprise” vs consensus into an event
• Building a dashboard of implied probabilities across topics

Exceptions & Edge Cases

• If fees are large or asymmetric, then implied probability from raw price can be biased.
• If the contract can resolve “ambiguous,” “void,” or “other,” then simple mapping breaks.
• If market is extremely illiquid, then last trade price can be meaningless.

Practical Examples

• Market: “Company X launches product by June 30”
  • “Yes” price $0.25
  • Implied probability ~25%
  • Your estimate 10% → you might sell/short “Yes” (if possible) or buy “No” (if offered)

Actionable Takeaways

• ✅ Verify it’s a true binary $1/$0 payoff
• ✅ Use mid-price (between bid/ask) when possible
• ✅ Adjust expectations for fees/spread
• ✅ Treat low-volume “last price” with skepticism