去中心化预测市场的解剖：来自Polymarket订单簿的微观结构证据
The Anatomy of a Decentralized Prediction Market: Microstructure Evidence from the Polymarket Order Book
AI总结：
本文通过分析Polymarket订单簿数据，揭示了去中心化预测市场的微观结构特征，包括长shot溢价、深度分布、延迟效应等，并指出需通过链上订单成交事件获取交易方向。
摘要：
我们利用Polymarket订单簿的连续tick级档案（52天内300亿事件）和链上交易记录，研究了该最大链上预测市场微观结构。在600个预注册市场面板上，报告了八个特征：长shot溢价、深度分布更接近均匀而非簿子顶部、无区块时间对齐效应、广义做市者钱包多样性、条件有效溢价差异、亚50毫秒的中位数存档延迟、自我对手清算份额（中位数1%，上尾22%）、以及由市场持续时间、价格水平和成交量解释的横截面深度分布。本文还贡献了测量结果：Polymarket的公开订单簿流推断的交易方向仅在59%的桶中与链上真实值一致（面板均值0.615，95%置信区间[0.58, 0.65]），低于纳斯达克的80% Lee-Ready 准确率。有效半幅价在订单簿和链上交易方向之间改变符号的比例为67%/50%的市场，Kyle的lambda为60%/43%。因此，Polymarket的微观结构研究需通过链上订单成交事件获取交易方向；我们发布了一个可复现的包以执行该连接。
英文摘要：
We study the microstructure of Polymarket, the largest on-chain prediction market, using a continuous tick-level archive of the public 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 profile closer to uniform than to top-of-book; a null block-clock alignment effect; broad maker-wallet diversity with a concentrated tail; category-conditional effective-spread differences; 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 Cong et al. 2023's 25-70% for unregulated crypto venues -- a sanity bound, not an apples-to-apples reference); and a cross-sectional depth profile explained by market duration, price level, and volume, with no residual time-to-close effect. The paper also contributes a measurement result: trade direction inferred from Polymarket's public order-book feed agrees with on-chain ground truth on only ~59% of buckets (panel mean 0.615, 95% CI [0.58, 0.65]), well below the ~80% Lee-Ready accuracy on Nasdaq. The effective half-spread changes sign between feed- and on-chain trade directions on 67%/50% of markets across two 7-day windows; Kyle's lambda on 60%/43%. Microstructure work on Polymarket therefore needs to source trade direction from on-chain OrderFilled events; we release a replication package that performs the join.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
