A-Share Screening with Moving Average Clusters and Opening Gains

Summary

This post describes an A-share stock screen built around clustered moving averages, market attention, and the pre-open price change. Its initial rule selects stocks with at least five overlapping moving averages, ranks them by popularity, and requires the 9:25 gain to be below 6%. The author interprets the moving-average cluster as nearby support and resistance, popularity as a proxy for investor attention, and a limited opening gain as a sign of a less extreme start.

The post then proposes a revised screen: at least ten overlapping averages, ranking by market capitalization, a 9:25 gain below 5%, and average daily volume above one million shares over the prior month. It offers qualitative rationale and suggested adjustments, but provides no backtest or performance evidence. The claimed support, attention, and stability interpretations are hypotheses, and the post itself notes that the filters may narrow the candidate pool or select weak stocks. Its sample code is incomplete, so implementation details are not fully specified.

Key ideas

• The initial screen looks for at least five clustered moving averages and ranks candidates by popularity.
• It limits the 9:25 pre-open gain to below 6% in the initial version.
• The revised screen raises the moving-average threshold, ranks by market capitalization, and adds a monthly volume filter.
• The rationale treats clustered averages as nearby support and resistance, but the post supplies no empirical validation.
• A narrow candidate pool and weak underlying stocks are identified as potential drawbacks.

Tags

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