Information Signal
In prediction markets, not all price changes are meaningful. An information signal occurs when probabilities adjust in response to credible, outcome-relevant information.
These signals tend to be directional and persistent. Prices move and stay moved because participants update beliefs based on shared evidence. Information signals are often supported by volume and broader participation. Multiple traders act independently on the same information, reinforcing the change. They differ from behavioral or liquidity-driven moves. Unlike hype or panic, information signals do not immediately reverse once trading stabilizes.
For analysts, identifying information signals is central to interpreting prediction markets data. They indicate when markets are genuinely learning rather than reacting emotionally.
Why It Matters
Information signals reveal when prediction markets are functioning as intended. They help users trust probability updates and filter out noise.
How can information signals be distinguished from noise in prediction markets?
Information signals tend to persist over time and are supported by trading volume and participation. Noise-driven moves often reverse quickly or lack volume support. Analysts look for consistency across multiple updates. Prediction markets data makes these distinctions observable.
What types of events generate strong information signals in prediction markets?
Strong information signals usually follow official announcements, verified data releases, or clear real-world developments. These events reduce uncertainty in a concrete way. Rumors and speculation produce weaker signals. Markets respond most clearly to authoritative information.
How are information signals used in prediction markets data analysis?
Analysts use information signals to weight forecasts and detect meaningful belief updates. Signals that persist are treated as informative inputs for models. Weak or short-lived signals are often downweighted. This improves accuracy and reliability in analysis.
Real-World Example
On Polymarket, a probability shift following an official election result update is an information signal. The move persists as participants independently react to the same verified data.
Information Signal and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides prediction markets data needed to identify information signals. Analysts can combine probability changes with volume, timing, and persistence metrics to separate information-driven moves from noise. This supports signal classification, efficiency analysis, and forecast weighting. The API enables consistent detection of information signals across prediction markets.