🤖 AI Summary
This study addresses the empirical gap in understanding the microstructure of decentralized prediction markets by systematically characterizing eight stylized facts across 600 markets on Polymarket, leveraging 30 billion order book events and on-chain trade records. Through precise alignment of high-frequency order book data with Ethereum’s OrderFilled events, a pre-registered cross-sectional panel design, and a reproducible analytical framework, the authors find that inferring trade direction from public order book data alone achieves only about 59% accuracy—significantly lower than in traditional markets—highlighting the critical necessity of on-chain execution data. Key findings include a long-tailed spread premium, liquidity depth approximately following a uniform geometric distribution, a median wash trading rate of just 1%, and a decay rate of 0.55 in market depth as settlement approaches. The complete replication toolkit is openly released.
📝 Abstract
We study the microstructure of Polymarket, the largest on-chain prediction market, using a continuous tick-level archive of the public WebSocket order-book feed (30 billion events over 52 days) joined to the authoritative on-chain trade record. On a pre-registered stratified panel of 600 markets we report eight stylized facts: a longshot spread premium; a depth-concentration profile closer to a uniform geometric grid than to the top-of-book pattern often assumed for prediction markets; a null block-clock alignment effect; broad maker-wallet diversity with a concentrated tail; category-conditional differences in effective spread; a sub-50 ms median archive-ingestion delay with a multi-second tail; a self-counterparty wash share with median 1% and a 22% upper tail, well below the network-classifier benchmarks of Cong et al. (2023) for unregulated cryptocurrency token exchanges (a sanity bound, not an apples-to-apples reference, since the venues face different wash incentives); and a depth decay near resolution with a within-category slope of 0.55 on log seconds-to-close (t=3.85). The paper also contributes a measurement result: trade direction inferred from Polymarket's public order-book feed agrees with on-chain ground truth only ~59% of the time (panel mean 0.615, 95% CI [0.58, 0.65]), barely above the 50% chance baseline. On the comparable subset of the top-100 panel, the effective half-spread changes sign between feed- and on-chain directions on 67% of markets in a first 7-day window and 50% in a second non-overlapping window, with Kyle's lambda flipping on 60% and 43% respectively; neither window recovers the on-chain sign at anything close to the ~80% rate that Lee-Ready achieves on equity venues. Microstructure work on Polymarket therefore needs to source trade direction from on-chain OrderFilled events; we release a replication package that performs the join.