Chinese Stock Screening with Turnover, Reversal Shape, and Popularity

Summary

This stock screen combines a turnover-rate band of 3%–12% with a candlestick range measure intended to identify a reversal pattern, then ranks qualifying stocks by market interest. The example calculates the smaller distance from the previous close to the day’s high or low as a fraction of the day’s range, retaining stocks at or below 0.2. It then sorts candidates using a heat or trading-amount ranking. The Python example also applies a positive price-to-earnings filter and removes stocks that are not currently listed, while the stated core screen does not include those extra filters.

The article gives a rule description and implementation examples, but no backtest results or evidence that the screen predicts returns. Its own discussion warns that popularity can change quickly and that relying on it may omit useful fundamentals such as valuation and earnings growth. The examples also draw on different dates and data sources, so they do not establish a consistent, tested process.

Key ideas

• The core screen requires a turnover rate between 3% and 12%.
• A range-based measure uses the smaller distance from the previous close to the daily high or low, divided by the daily range.
• The example ranks qualifying stocks by a heat or trading-amount measure.
• The Python example adds positive earnings valuation and listing-status filters beyond the stated core rules.
• The document provides no performance test and cautions that popularity can shift while fundamentals are omitted.

Tags

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