What is a prediction market, and how is it different from betting?

Detailed Explanation

1. Core idea: A contract pays $1 if an event happens and $0 if it doesn’t (or a similar payout structure).
2. Price as probability: If a “Yes” share trades at $0.62, the market is implying roughly a 62% chance of “Yes.”
3. Market-driven odds: Participants trade with each other (often via an order book), so the “odds” update continuously as new information arrives.
4. Why this exists: Markets aggregate dispersed information—many small signals combine into a single, tradable probability estimate.

Common Scenarios

• You want a simple “odds” read on an election, policy decision, or economic release
• You believe news is underpriced or overpriced by the crowd
• You want to hedge business exposure to a specific outcome
• You’re comparing “market probability” vs your internal forecast

Exceptions & Edge Cases

• If a contract’s payout isn’t binary (e.g., range/ladder or scalar), then price ≠ probability in a simple way.
• If there’s low liquidity, then price can be a noisy estimate of probability.
• If rules allow “void” or special resolution, then you must map those conditions to your thesis.

Practical Examples

• A “Yes” contract pays $1 if a central bank cuts rates by March 31.
  • “Yes” trades at $0.40 → market implies ~40%
  • You estimate 55% → you see positive expected value (EV) in buying “Yes.”

Actionable Takeaways

• ✅ Confirm payout rules (binary vs non-binary)
• ✅ Interpret price as implied probability (only when truly binary)
• ✅ Check liquidity (spread + depth) before trusting the price
• ✅ Write down your forecast and what would change it

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