A Stock Screen Combining Trading Activity, Price, and Valuation Factors
Summary
This Chinese-language post sketches a stock selection approach that ranks shares by trading activity, using volume and turnover as proxies for capital strength, and also considers share price. It proposes selecting highly ranked stocks on these measures, with a stated 2021 data window, then combining the screen with valuation measures such as price-to-earnings and price-to-book ratios. A short Python example shows how percentile ranks for volume and turnover can be added to form a strength score.
The post itself cautions that relying heavily on trading activity and price can omit other important drivers, and that the chosen time window may not suit current conditions. It gives no backtest methodology, performance evidence, universe definition, or clear account of how the factor rankings are combined; the text also mixes a particular price criterion with broader ranking language. The screen is therefore a rough factor idea requiring precise rules and out-of-sample evaluation, rather than a validated strategy.
Key ideas
- The proposed screen ranks stocks using trading volume and turnover as indicators of trading activity.
- It also considers share price and suggests adding valuation measures such as price-to-earnings and price-to-book ratios.
- A sample strength score adds percentile ranks for volume and turnover.
- The post warns that these inputs alone may overlook other relevant factors and that the selected period may not fit other market conditions.
- No backtest results or fully specified combination rules are provided.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.