We show current market practices relating to odd-lot quotes create a large “inside” market where better prices routinely exist relative to the National Best Bid or Offer. We show that odd-lot quotes play a price discovery role, and these quotes provide valuable information to traders with access to proprietary data feeds. Using a XGBoost machine learning algorithm that uses odd-lot data to predict future prices, we demonstrate a simple and profitable trading strategy. We argue the SEC’s proposed round-lot redefinition reduces—but does not eliminate—the high incidence of superior odd-lot quotes within the NBBO.

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市场内部的市场：碎股报价

我们展示了当前与碎股报价相关的市场实践创建了一个大型“内部”市场，其中通常存在相对于全国最佳买价或卖价更好的价格。我们表明，碎股报价发挥着价格发现作用，这些报价为能够访问专有数据源的交易者提供了有价值的信息。我们使用 XGBoost 机器学习算法（使用零股数据来预测未来价格）展示了一种简单且有利可图的交易策略。我们认为，SEC 提议的整批重新定义减少了——但并没有消除——NBBO 内优质零股报价的高发生率。