Spread Compression
Spread compression happens when buyers and sellers move closer on price. Instead of wide gaps between bids and asks, orders cluster tightly, making trades easier to execute. This usually reflects higher confidence, better liquidity, or increased participation.
In prediction markets, spread compression often appears as an event becomes clearer or attracts more attention. Traders are more willing to quote tighter prices because uncertainty is lower or competition is higher. On platforms like Polymarket, Kalshi, Myriad, and Manifold, this shows up in prediction markets data as tighter execution ranges and smoother probability updates.
Compressed spreads reduce friction. Prices move with smaller steps, and probabilities become easier to interpret as true belief rather than liquidity noise.
Why It Matters
Spread compression improves price quality and execution. It makes prediction markets data more reliable by reducing distortion from trading friction.
Why does spread compression occur in prediction markets?
It occurs when more traders are willing to provide liquidity and uncertainty declines. As confidence grows, participants compete by offering better prices. This competitive pressure tightens spreads and improves the quality of prediction markets data.
How does spread compression affect forecast accuracy?
Narrow spreads mean prices better reflect consensus belief. Trades cause smaller distortions, and probabilities adjust more smoothly to new information. This leads to cleaner, more interpretable prediction markets data, especially near resolution.
What insights can analysts gain from observing spread compression?
Analysts can identify moments of rising confidence, improved liquidity, or approaching resolution. Sudden compression may signal that uncertainty has dropped or that new information has been widely accepted. Tracking spread changes adds valuable context to prediction markets data.
Real-World Example
As a key policy decision approaches, a Polymarket market shows its bid–ask spread shrinking steadily. Traders agree more closely on the likely outcome, and execution becomes easier, reflecting spread compression.
Spread Compression and FinFeedAPI
Studying spread compression requires detailed bid and ask data over time. FinFeed's Prediction Markets API provides structured prediction markets data—bid–ask prices, volume, and OHLCV—that developers can use to monitor spread behavior and assess market quality.