Turnover, Reversal Patterns, and Long-Term Trend in Stock Screening

Summary

This Chinese equities screen combines a turnover rate between 3% and 12%, a reversal pattern, and a prior-day closing price above the 250-day moving average. The article presents turnover as a way to select actively traded shares, the reversal condition as a short-term price signal, and the long moving average as a filter for longer-term trend. It provides a platform query and a Python example intended to calculate these conditions.

The post supplies no backtest results or evidence that the combination produces better returns. It warns that the screen uses technical factors alone and may select companies with weak fundamentals; it suggests adding other technical and financial measures. The sample Python implementation has notable inconsistencies, including data handling that does not clearly calculate turnover and combines futures-related data with an equities screen. Its moving-average calculation also depends on suitable historical price series, which the example does not establish. The code should therefore be treated as illustrative rather than a reliable implementation of the written rules.

Key ideas

• The screen requires turnover between 3% and 12%, a reversal pattern, and yesterday's close above the 250-day moving average.
• The long moving average is intended to filter for a positive longer-term trend.
• The article reports no backtest evidence for the combined conditions.
• The sample Python code contains data and calculation inconsistencies that need checking.
• Technical filters alone can overlook company fundamentals and financial quality.

Tags

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