Event Outcome Correlation
Event outcome correlation appears when two events share causes, dependencies, or common risk factors. If one event becomes more likely, the other often does too. This relationship can be strong, weak, or conditional.
In prediction markets, correlations emerge through trading behavior. When traders believe events are linked, they adjust positions across multiple markets at the same time. On platforms like Polymarket, Kalshi, Myriad, and Manifold, this shows up in prediction markets data as synchronized probability movements, parallel trends, or joint reversals.
Correlations can be direct or indirect. Some events depend logically on others, while some are connected through shared external forces like policy, timing, or macro conditions.
Why It Matters
Event outcome correlation helps explain why markets move together. Recognizing it prevents misreading prediction markets data as independent signals when they are not.
How do event outcome correlations form in prediction markets?
They form when traders recognize shared drivers or dependencies between events. As beliefs update in one market, traders adjust related markets accordingly. This behavior creates correlated probability paths in prediction markets data.
Why is correlation important for analysis and forecasting?
Ignoring correlation can lead to double-counting confidence or risk. Analysts who assume independence may overestimate certainty. Accounting for correlation makes prediction markets data more accurate for scenario analysis and aggregation.
How can analysts detect correlated outcomes?
Analysts look for markets that move together consistently, especially around the same information events. Comparing probability changes, timing, and volatility across markets helps identify correlation patterns within prediction markets data.
Real-World Example
A Polymarket market tracks whether a bill passes committee, while another tracks whether it becomes law. When the committee approval probability rises, the final-passage market often moves in the same direction, reflecting correlated outcomes.
Event Outcome Correlation and FinFeedAPI
Studying event outcome correlation requires tracking related markets together. FinFeed's Prediction Markets API provides structured prediction markets data that developers and analysts can use to measure correlation, model dependencies, and avoid double-counting signals.