In prediction markets, a signal provider is anyone whose trade reflects meaningful information about an event. When they buy or sell outcome shares, they embed their insight directly into the price. Other participants then react to these moves, allowing the market to incorporate that information into a shared forecast.
Signal providers can be traders who follow data closely, spot news early, recognize patterns, or have domain expertise. On platforms like Polymarket, Kalshi, Myriad, and Manifold, these providers often shape market behavior by acting quickly when new information appears. Their trades serve as early indicators of belief shifts, making prediction markets data more responsive and useful.
Over time, repeated contributions from signal providers help markets reflect a deeper pool of knowledge. Their influence is visible in sharper probability adjustments, faster reactions to breaking developments, and more accurate consensus forecasts.
Signal providers make prediction markets smarter by injecting new information into the system. Their trades help generate cleaner, more accurate prediction markets data.
They are important because prediction markets depend on informed trading to update probabilities. When a signal provider acts on credible information, the market adjusts quickly, reducing mispricing. This continuous flow of insight helps markets stay accurate and responsive, resulting in prediction markets data that reflects the most current understanding of an event.
Signal providers influence markets by placing trades that shift probabilities in the direction of their belief. Large or timely trades can signal new developments or reinterpreted data. Other participants may follow these signals, accelerating the adjustment. This dynamic makes prediction markets data a real-time record of how new information spreads across the trading community.
Analysts can identify which traders tend to act early, which signals reliably move markets, and how quickly information spreads among participants. Studying these patterns reveals market efficiency, potential biases, and how informed communities behave. This makes prediction markets data more interpretable and improves forecasting models.
On Polymarket, a trader reacts early to a newly released economic report by buying heavily into a relevant market. Their trade shifts the probability sharply, signaling to others that the report contains meaningful information. The rest of the market follows as participants digest the news, reflecting efficient signal propagation.
Understanding signal providers requires tracking how probability reacts to trades over time. FinFeed's Prediction Markets API offers structured prediction markets data—price, timestamps, and OHLCV—that developers can use to identify influential trades, detect information flow, and model how signals shape market outcomes.
