AI 中文总结
该研究基于去中心化交易所的公开钱包交易数据，发现钱包身份具有信息性，其排名可预测短期收益，身份信息能提升收益预测模型的样本外R²，且增益显著。
AI 中文摘要
知情交易者被认为需要匿名性：他们通过隐藏在非知情交易者中获利。现在，一个去中心化交易所会公布交易对手信息：每一笔已提交的订单、撤单、拒单和成交都带有一个持久的假名钱包地址。我们从147113个钱包的171亿条消息和1430万条激进订单记录中重建了完整深度的限价订单簿，覆盖了843亿美元的吃单名义价值。我们报告三项发现：第一，信息性是钱包的持久属性。我们根据钱包的激进订单在未来十天内跟随的价格变动对钱包进行排名，该排名在接下来的十天内大体保持稳定，秩相关系数为0.52。第二，该排名可预测收益：使用身份信息的线性模型对一秒钟收益的样本外R²达到12.31%，比基于价格、报价和订单流的标准匿名基准提高了13.2%（t值为9.2），该增益是20个与活动匹配的安慰剂队列中最大增益的1.6倍。第三，我们在实际交易时而非每个采样时刻测试该增益，身份带来的R²增量从1.43个百分点增长至2.47个百分点。因此，公开钱包历史包含匿名订单簿数据未测量的短期价格信息。
英文摘要
Informed traders are supposed to need anonymity: they profit by hiding among the uninformed. A decentralized exchange now publishes the counterparty. Every committed order, cancellation, rejection, and fill carries a persistent pseudonymous wallet address. We reconstruct the full-depth limit order book from a record of 17.1 billion messages and 14.3 million aggressive orders by 147,113 wallets, covering $84.3 billion in taker notional. We report three findings. First, informativeness is a persistent wallet attribute. Wallets ranked by the price movement following their aggressive orders retain that ordering across adjacent ten-day windows, with a rank correlation of 0.52. Second, the ranking predicts returns. Adding the live activity of the highest-ranked wallets to a standard anonymous benchmark of prices, quotes, and order flow raises the out-of-sample R2 for one-second returns to 12.31%, a 13.2% gain (t = 9.2) that is 1.6 times the largest of 200 activity-matched placebo cohorts. Third, measured at realized trades rather than at every sampled moment, the increment grows from 1.43 to 2.47 percentage points of R2. Public wallet histories therefore carry short-horizon price information that anonymous order-book data leave unmeasured.
Comments40 pages, 8 figures, 15 tables
