A market reversal happens when probabilities rise or fall for a period of time and then turn back in the opposite direction. In prediction markets, this usually means the crowd has changed its mind. The reversal can be slow and gradual, or sudden and dramatic.
Reversals often follow overreactions, rumors, or early speculation. As better information arrives, informed traders step in and correct the price. On platforms like Polymarket, Kalshi, Myriad, and Manifold, reversals are visible in prediction markets data as sharp turns in probability curves after periods of momentum.
Not all reversals mean the market was wrong. Some reflect genuine uncertainty resolving, while others show noise being filtered out. Understanding the context behind a reversal is key to interpreting what the market is really saying.
Market reversals help reveal when prices were driven by noise rather than information. They are critical for understanding the reliability and dynamics of prediction markets data.
They happen when early sentiment or speculation is replaced by stronger evidence. Traders may overreact to headlines, comments, or partial information, pushing probabilities too far. When clearer data appears, prices reverse toward a more realistic level. This process is common in fast-moving prediction markets data.
Reversals often indicate that the market temporarily drifted away from fair value. When informed traders act, they pull the price back. Analysts use reversals to identify periods of overconfidence, noise trading, or base rate neglect within prediction markets data.
Analysts can learn how quickly markets correct mistakes, which events trigger overreaction, and how information is absorbed over time. Frequent reversals may point to low liquidity or emotional trading. Clean reversals followed by stability often signal healthy market behavior in prediction markets data.
A political market on Polymarket climbs rapidly after a viral rumor spreads online. Hours later, official clarification contradicts the claim, and the probability drops sharply. The reversal shows how the market corrected once reliable information replaced speculation.
Studying reversals requires high-resolution probability histories and timing data. FinFeed's Prediction Markets API provides structured prediction markets data that help analysts detect reversals, understand their causes, and evaluate market efficiency.
