A-Share Screen for Volatility, Recent Limit-Ups, and Institutional Buying

Summary

This A-share stock screen combines three conditions: daily price amplitude above 1%, at least one limit-up event in the prior 25 days, and reported institutional buying within the past three months. The article frames the conditions as a mix of volatility, recent price strength, and perceived institutional support, then gives example implementations for a Chinese stock screening platform and Python data sources.

The post offers no backtest, performance data, or evidence that the conditions predict returns. It warns that institutional buying data may be incomplete or misclassified, and that market sentiment can shift. Its sample code also appears to implement some conditions differently from the stated rule: the Python limit-up condition checks the current bar and requires the high to equal the low, while the prose specifies an event in the prior 25 days. Treat the examples as screening sketches that need validation, and consider the suggested additions of risk limits, diversification, and further indicators or fundamentals.

Key ideas

• The proposed screen requires amplitude above 1%, a limit-up event in the previous 25 days, and institutional buying within three months.
• The article presents volatility, recent price strength, and institutional activity as complementary selection signals.
• It provides platform-specific and Python examples, but does not report any backtest or measured results.
• The sample Python condition does not clearly match the stated 25-day limit-up rule and should be checked before use.
• The post identifies data quality and changing market sentiment as risks and suggests portfolio limits and broader filters.

Tags

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