Order Flow Imbalance
Order flow imbalance appears when trades are skewed in one direction. If many traders are buying an outcome while few are selling, the market experiences buy-side pressure. The opposite happens when sell orders dominate. This imbalance pushes prices until the market finds a new balance.
In prediction markets, order flow imbalance reflects short-term belief shifts. Traders may react to news, sentiment, or visible price moves, creating bursts of one-sided activity. On platforms like Polymarket, Kalshi, Myriad, and Manifold, this shows up in prediction markets data as rapid probability changes, temporary volatility, or momentum-driven moves.
Not every imbalance means new information has arrived. Some are driven by herd behavior, liquidity gaps, or timing effects. Understanding the cause behind the imbalance is key to interpreting what the market is really signaling.
Why It Matters
Order flow imbalance explains why prices move, not just that they move. It helps analysts understand short-term dynamics inside prediction markets data.
Why does order flow imbalance occur in prediction markets?
It occurs when many traders act on similar signals at the same time. This can be due to breaking news, social sentiment, or visible price momentum. In low-liquidity markets, even modest coordination can create strong imbalance, which becomes visible in prediction markets data.
How does order flow imbalance affect probabilities?
Imbalance pushes prices quickly as the market adjusts to absorb demand. Probabilities may overshoot if the imbalance is emotional or speculative, then correct once countertrades appear. Analysts often see this pattern in prediction markets data as sharp moves followed by stabilization.
What insights can analysts gain from tracking order flow imbalance?
Analysts can distinguish information-driven moves from noise-driven ones. Persistent imbalance may signal strong conviction, while short-lived imbalance often points to herd behavior or sentiment spikes. Tracking these patterns improves interpretation of prediction markets data and market behavior.
Real-World Example
After a breaking headline, a Polymarket market sees a surge of buy orders for one outcome. The probability jumps quickly, then slows as sellers enter and balance returns, showing a clear order flow imbalance followed by correction.
Order Flow Imbalance and FinFeedAPI
Studying order flow imbalance requires granular trade and probability data. FinFeed's Prediction Markets API provides structured prediction markets data—time-stamped price changes and volume signals that developers can use to detect imbalances, analyze short-term pressure, and understand how order flow shapes forecasts.