Trade co-occurrence, trade flow decomposition and conditional order imbalance in equity markets
提出一种基于交易时间邻近性将每笔交易分为五类的方法，通过条件订单不平衡（COI）研究交易流的价格影响，发现COI与同期收益强正相关，且基于COI的交易策略在457只股票4年数据中取得显著收益和夏普比率。
The time proximity of high-frequency trades can contain a salient signal. In this paper, we propose a method to classify every trade, based on its proximity with other trades in the market within a short period of time, into five types. By means of a suitably defined normalized order imbalance associated to each type of trade, which we denote as conditional order imbalance (COI), we investigate the price impact of the decomposed trade flows. Our empirical findings indicate strong positive correlations between contemporaneous returns and COIs. In terms of predictability, we document that associations with future returns are positive for COIs of trades which are isolated from trades of stocks other than themselves, and negative otherwise. Furthermore, trading strategies which we develop using COIs achieve conspicuous returns and Sharpe ratios, in an extensive experimental setup on a universe of 457 stocks using daily data for a period of 4 years.