Forecast History
In prediction markets, forecasts update continuously as participants trade and new information appears. Forecast history captures these updates as a time-ordered sequence of probabilities.
Rather than focusing on the latest price, forecast history shows the full path of belief formation. It includes early uncertainty, mid-course corrections, and late-stage convergence.
This history reveals how markets respond to information. Sudden jumps, gradual trends, and periods of stability all become visible.
Forecast history is essential for understanding context. Two markets with the same final probability may have followed very different paths to get there.
For analysts, forecast history transforms prediction markets data into an analytical timeline. It supports behavioral analysis, performance evaluation, and learning assessment.
Over time, studying forecast histories across events reveals recurring patterns. These patterns help explain market efficiency, bias, and responsiveness.
Why It Matters
Forecast history provides context that single probabilities cannot. It helps users understand how confident, stable, or reactive a market has been.
How is forecast history different from a snapshot price in prediction markets?
A snapshot price shows belief at one moment. Forecast history shows how that belief developed over time. This reveals volatility, persistence, and reaction timing. History adds depth to prediction markets data interpretation.
What can forecast history reveal about market behavior?
Forecast history can reveal overreaction, delayed response, and attention-driven swings. It shows whether markets learn early or adjust late. These patterns help explain forecast reliability. Analysts rely on history to understand behavior, not just outcomes.
How is forecast history used in prediction markets data analysis?
Analysts use forecast history for backtesting, calibration, and behavioral studies. It allows comparison of early versus late forecasts. History is also used to compute metrics like persistence and volatility. This makes prediction markets data suitable for long-term analysis.
Real-World Example
On Polymarket, analysts may review the full forecast history of an election market to see how probabilities changed after debates, polls, and announcements.
Forecast History and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides historical prediction markets data needed to construct forecast histories. Analysts can retrieve time-stamped probability updates for events and outcomes. This supports trend analysis, backtesting, and forecast evaluation. The API enables consistent access to forecast history across prediction markets.