Market Microstructure Dataset
In prediction markets, prices are shaped by many small interactions. A market microstructure dataset captures these interactions at a granular level, such as individual trades, order timing, and liquidity changes. Instead of summarizing outcomes, this dataset shows how probabilities are formed step by step. It reveals how orders arrive, how quickly they are filled, and how prices respond to pressure.
Microstructure data is especially useful for understanding short-term behavior. It helps explain sudden jumps, slow adjustments, and periods of instability that are not obvious in aggregated data. These datasets also highlight differences between markets. Two markets with similar probabilities may behave very differently at the trade level.
For analysts, market microstructure datasets provide the foundation for deep analysis. They allow investigation of efficiency, liquidity quality, and behavioral effects within prediction markets data. Over time, microstructure analysis helps improve market design. It shows which mechanisms support smooth price discovery and which introduce friction or noise.
Why It Matters
Understanding how trades form prices improves trust in forecasts. Market microstructure datasets explain why probabilities move, not just where they end up.
What is a market microstructure dataset in prediction markets?
In prediction markets, a market microstructure dataset records detailed trading activity. It includes information like order flow, execution timing, and liquidity changes. This data shows how prices are actually formed. It is essential for low-level market analysis.
How does a market microstructure dataset improve prediction markets data analysis?
Microstructure datasets allow analysts to study trading behavior directly. They help identify informed trading, noise, and liquidity gaps. This improves interpretation of volatility and belief shifts. It adds depth beyond aggregated probability data.
Why are market microstructure datasets important for prediction markets APIs?
Prediction markets APIs provide the granular data needed to build microstructure datasets. APIs expose trade-level events, timestamps, and liquidity signals. This enables systematic and scalable microstructure analysis. Without APIs, this level of insight is difficult to achieve.
Real-World Example
On Polymarket, a sharp probability jump may be driven by a sequence of small trades rather than a single large one. A market microstructure dataset reveals this pattern by showing the underlying order flow.
Market Microstructure Dataset and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides detailed prediction markets data suitable for market microstructure datasets. Analysts can access trade-level activity, timing data, and liquidity signals. This supports execution analysis, efficiency measurement, and behavioral research. The API enables consistent microstructure analysis across prediction markets.