Forecast Sensitivity
Forecast sensitivity measures how easily a market’s probability moves. Some markets react sharply to small signals, while others barely move unless strong evidence appears. This difference reflects confidence, liquidity, and uncertainty.
In prediction markets, sensitivity depends on how settled beliefs are. Early-stage or low-liquidity markets tend to be more sensitive, reacting quickly to rumors or partial news. More mature markets usually require stronger confirmation to move. On platforms like Polymarket, Kalshi, Myriad, and Manifold, this behavior is visible in prediction markets data as either sharp jumps or muted responses.
Sensitivity is not good or bad by itself. High sensitivity can mean fast learning, while low sensitivity can mean stability or resistance to noise.
Why It Matters
Forecast sensitivity helps explain why some probabilities move quickly and others stay stable. It adds important context when interpreting prediction markets data.
What determines forecast sensitivity in prediction markets?
Sensitivity is shaped by liquidity, uncertainty, and how concentrated beliefs are. When traders disagree or information is incomplete, small updates can move prices more. As confidence grows, the same updates have less effect. These patterns are visible in prediction markets data.
How does forecast sensitivity differ from volatility?
Volatility describes how much prices move overall. Sensitivity describes how strongly prices react to new information. A market can be volatile due to noise but still show low sensitivity to real updates. Prediction markets data helps distinguish these effects.
When is high forecast sensitivity a warning sign?
High sensitivity can signal fragile beliefs, low liquidity, or overreaction risk. Analysts often treat highly sensitive markets with caution, especially when moves are driven by weak signals. Tracking sensitivity helps avoid misreading prediction markets data.
Real-World Example
A new policy market on Polymarket jumps sharply after a minor statement, showing high forecast sensitivity. Later, as official guidance emerges and liquidity improves, similar statements barely move the probability, indicating reduced sensitivity.
Forecast Sensitivity and FinFeedAPI
Measuring forecast sensitivity requires comparing probability changes to information timing. FinFeed's Prediction Markets API provides structured prediction markets data so developers and analysts can evaluate how responsive forecasts are and when markets become more stable.