Posterior Belief Shift
In prediction markets, prices represent collective beliefs about future outcomes. When new data, news, or trading behavior appears, those beliefs often change.
A posterior belief shift captures this update by comparing probabilities before and after the new information is absorbed. The size and direction of the shift help explain how strongly the market reacted.
These shifts are visible in prediction markets data as price movements, probability changes, or volatility adjustments. Tracking them helps analysts understand when markets truly learn something new.
Why It Matters
Posterior belief shifts reveal how prediction markets respond to information. They help users separate meaningful updates from routine noise and better interpret probability changes.
What causes a posterior belief shift in prediction markets?
In prediction markets, a posterior belief shift is usually caused by new information entering the market. This can include news events, data releases, or large changes in trading activity. When participants update their expectations, prices adjust to reflect the new consensus. The shift shows how beliefs evolved after the update.
How can posterior belief shifts be identified using prediction markets data?
Posterior belief shifts can be identified by analyzing probability changes over time in prediction markets data. Analysts often compare pre-event and post-event prices, volume patterns, and volatility. Larger or sustained movements suggest stronger belief updates. Smaller shifts may indicate weak or uncertain information.
Why are posterior belief shifts useful in prediction markets APIs?
Prediction markets APIs allow analysts to track belief shifts programmatically across many markets. By monitoring probability updates in real time, models can detect when meaningful information has been absorbed. This is useful for alerts, trend detection, and model recalibration. APIs make belief shift analysis scalable and consistent.
Real-World Example
On Kalshi, a market predicting an economic release may show a noticeable probability jump after official data is published. That change represents a posterior belief shift driven by confirmed information.
Posterior Belief Shift and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides time-series prediction markets data needed to analyze posterior belief shifts. Analysts can track probability updates, volume changes, and volatility before and after events. This supports information impact analysis, signal validation, and model updates. The API enables systematic monitoring of belief changes across prediction markets.