Validity Window
In prediction markets, every contract is tied to a specific timeframe. The validity window specifies when trading is allowed and when the forecast is considered applicable.
This window starts when the market opens and ends at a predefined cutoff, often just before resolution. After the window closes, no new information should influence the outcome.
Validity windows help separate relevant signals from late or invalid data. They ensure that prediction markets data reflects expectations formed within a clearly defined period.
They also shape trading behavior over time. Early in the window, uncertainty is higher, while activity near the end often reflects final adjustments as information becomes clearer.
For analysts, the validity window provides essential context. It explains why probability dynamics, volume, and confidence signals change as a contract approaches expiration.
Why It Matters
Without a clear validity window, prediction markets can produce misleading signals. Defined windows help users interpret probabilities correctly and avoid mixing outdated or irrelevant data.
What does validity window mean in prediction markets?
In prediction markets, a validity window refers to the time span during which a contract’s predictions apply. It defines when trades influence the outcome and when they no longer count. This prevents late or post-event information from affecting probabilities. It helps preserve forecast integrity.
How does a validity window affect prediction markets data?
The validity window shapes how prediction markets data evolves over time. Activity often increases as the window narrows and uncertainty declines. After the window closes, probabilities stop updating even if external information continues to emerge. Analysts use this boundary to segment and analyze market behavior accurately.
Why is validity window important for prediction markets APIs?
Prediction markets APIs deliver time-series data tied to specific contract windows. Knowing the validity window helps analysts filter, align, and model data correctly. It is critical for backtesting, lifecycle analysis, and performance evaluation. APIs make it possible to track validity windows consistently across markets.
Real-World Example
On Kalshi, a contract predicting an economic release stops accepting new trades once the data is published. The validity window ensures that only pre-release expectations shape the final probability.
Validity Window and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides metadata and time-based prediction markets data needed to analyze validity windows. Analysts can identify when markets open, close, and resolve. This supports lifecycle modeling, probability alignment, and accurate historical analysis. The API enables consistent handling of validity windows across prediction markets.