Trade signing in fast markets
使用纳斯达克和纽交所的真实交易数据，评估了快速交易环境下交易方向判定算法的准确性，发现Lee和Ready算法仍优于其他规则，且引用报价数据能提高分类精度。
Abstract This study assesses the accuracy of trade signing algorithms in fast trading environments using NASDAQ and NYSE trade and quote data. Using data that contain true trade signs, we show that the Lee and Ready algorithm outperforms the tick rule and classifies trades at least as well as in earlier studies from slower trading environments, even in subsamples where the market is particularly fast. We conclude that trade signing remains viable in fast markets, and that the use of quote data continues to increase trade classification accuracy.