Informed Buy and Sell Flow Factors for Chinese Equities
Summary
This research summary describes stock-selection factors built from tick-level aggressive buy and sell amounts. It applies an informed-trading probability model to filter noisy order flow, then forms informed sell share, informed buy share, and net informed buy share measures. The factors are assessed over different parts of the trading day and with different volume denominators.
The summary reports that full-day and post-open informed sell shares, as well as pre-close informed buy share, showed monthly cross-sectional predictive ability. It gives examples of information coefficients, information ratios, long-short returns, and win rates; post-open net informed buy share is also reported as useful. Results vary by universe: some effects persist in broader CSI 800 or CSI 500 groups, while several weaken or disappear in the CSI 300 or as the stock universe narrows. The source text is only an abstract and points to a full paper that is not included, so sample design, implementation details, costs, and robustness beyond the summarized checks cannot be evaluated here.
Key ideas
- A probability model for informed trading can filter aggressive buy and sell flows before factor construction.
- The study examines informed buy, informed sell, and net informed buy shares across intraday periods.
- Post-open informed sell share and pre-close informed buy share are among the stronger reported signals.
- Factor performance varies across index universes and can weaken as the eligible stock set narrows.
- The available summary omits the full methodology, sample design, and trading-cost analysis.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.