A-Share Screen Using Turnover, Convertible Bond Data, and Moving Averages

Summary

This post presents an A-share selection rule that combines daily price movement, convertible-bond information, and a moving-average trend filter. Its stated criteria include an amplitude above 1, a nonempty name for outstanding convertible bonds, and a 20-day moving average above the 120-day average. It describes ordering candidates by the 20-day average, while its Python example instead sorts by average trading value, so the ranking method is inconsistent across the post.

The author frames the filters as a way to find volatile stocks with an upward trend and says the bond field may screen for certain company characteristics. The post warns that the rule omits broader fundamentals and that technical indicators can mislead; it suggests adding valuation measures. The included code and formula are references rather than a validated implementation: fields and filters differ between them, and no backtest, transaction-cost analysis, or return evidence is provided. The criteria therefore need clarification and independent testing before use.

Key ideas

• The stated screen requires amplitude above 1 and a 20-day average above the 120-day average.
• It also filters on a nonempty outstanding convertible-bond name field.
• The post gives conflicting descriptions of how selected stocks should be ranked.
• It warns that the screen omits broader fundamental information and that technical signals can be unreliable.
• The formula and Python example are not accompanied by performance tests.

Tags

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