Execution Quality
Execution quality focuses on what happens after a trader decides to act. It compares the price a trader expects to get with the price they actually receive. Good execution means trades fill quickly, at fair prices, and with minimal slippage.
In prediction markets, execution quality depends on liquidity, spreads, and market structure. When markets are active and balanced, trades execute smoothly and prices update cleanly. On platforms like Polymarket, Kalshi, Myriad, and Manifold, execution quality is visible in prediction markets data through tight spreads, high fill rates, and limited price impact during normal conditions.
Poor execution quality shows up when prices jump unexpectedly, orders fail to fill, or traders consistently receive worse prices than expected. These issues are usually tied to low liquidity or fast-moving conditions rather than bad forecasts.
Why It Matters
Execution quality affects how usable market prices really are. High-quality execution makes prediction markets data more reliable for both traders and analysts.
What determines execution quality in prediction markets?
Execution quality is shaped by liquidity depth, bid–ask spreads, order matching rules, and market activity. Markets with many participants and steady order flow tend to offer better execution. These factors are all observable in prediction markets data.
How does execution quality influence probability interpretation?
If execution quality is poor, displayed prices may not be achievable in practice. Analysts must be cautious when using such probabilities as signals. High execution quality means prices closely reflect actionable belief, improving the usefulness of prediction markets data.
How can analysts evaluate execution quality?
Analysts look at slippage, fill probability, spread behavior, and price impact. Comparing expected prices with actual trade outcomes over time reveals whether a market consistently delivers fair execution. This analysis depends on detailed prediction markets data.
Real-World Example
During a calm period, a Polymarket market allows traders to enter and exit positions near the displayed probability with minimal slippage. During a breaking news event, execution quality briefly worsens as prices move quickly and spreads widen.
Execution Quality and FinFeedAPI
Evaluating execution quality requires precise trade and pricing data. FinFeed's Prediction Markets API provides structured prediction markets data: order books, trades, and OHLCV—that developers and analysts can use to measure execution quality and assess how closely prices reflect real trading conditions.