Losing Outcome
In prediction markets, multiple outcomes are traded before an event resolves. When resolution occurs, all outcomes except the winning one become losing outcomes. Losing outcomes expire without value once settlement is completed. Any positions held in these outcomes are closed with no payout.
The designation of losing outcomes is rule-based. It follows directly from the market’s resolution criteria and source of truth. Losing outcomes are an expected part of forecasting under uncertainty. Their presence allows probabilities to be tested and evaluated over time.
For analysts, losing outcomes are essential for performance measurement. They provide the contrast needed to assess accuracy, confidence, and forecast error in prediction markets data.
Why It Matters
Losing outcomes make forecast evaluation possible. They define what was incorrect and allow prediction markets to be judged objectively.
How are losing outcomes identified in prediction markets?
Losing outcomes are identified once the market resolves. Any outcome that does not match the verified real-world result is designated as losing. This process follows predefined rules and sources. No discretion is applied after resolution.
What happens to positions in losing outcomes after settlement?
Positions in losing outcomes are closed during settlement. They do not receive any payout. Collateral or stake associated with these positions is forfeited according to market rules. This finality ensures clear economic outcomes.
How are losing outcomes used in prediction markets data analysis?
Losing outcomes are used to calculate forecast error and accuracy. Analysts compare the probabilities assigned to losing outcomes against the winning one. Repeated patterns of high confidence in losing outcomes reveal bias or miscalibration. This analysis improves forecasting models.
Real-World Example
On Polymarket, if a market predicts whether a bill will pass and it fails, the “Yes” outcome becomes the losing outcome and pays nothing.
Losing Outcome and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides prediction markets data that identifies losing outcomes after resolution. Analysts can align losing outcomes with historical probabilities to measure error, calibration, and confidence breakdowns. This supports backtesting, performance analysis, and model improvement. The API enables consistent analysis of losing outcomes across prediction markets.