Screening Stocks by Turnover and Moving-Average Alignment

Summary

This post describes an A-share screening rule combining daily turnover between 3% and 12%, an opening price within 5% of the 10-day moving average, and a moving-average relationship intended to indicate alignment. It includes a formula-style example and a Python example using daily stock data. The accompanying discussion frames the screen as a way to focus on liquid stocks near a short-term reference price, while treating moving-average alignment as a technical setup.

The evidence is limited to the rule and code examples; no performance results, backtest design, or execution assumptions are supplied. The implementations also appear inconsistent: the formula compares the 5-day average with the 10-day average on several prior bars, whereas the prose says at least five averages overlap, and the Python example applies turnover quantiles and median prices across the retrieved history. These differences matter when reproducing the screen. The post itself notes that technical filters omit company fundamentals and may exclude some stocks, and suggests adding fundamental measures and tuning parameters.

Key ideas

• The screen combines a turnover band, proximity of the open to the 10-day average, and moving-average conditions.
• The stated turnover interval is 3% to 12%, and the opening-price tolerance is 5% around the 10-day average.
• The formula and Python examples encode conditions differently, so results may not match without clarifying the intended timing and aggregation.
• The post provides no evidence of historical or live performance.
• Technical screening alone does not assess company fundamentals or long-term value.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.