Screening 2021 Stocks by Moving-Average Clustering and Turnover

Summary

This note proposes a historical stock screen based on five moving averages (5, 10, 20, 30, and 60 days), average turnover over 20 days between 2% and 9%, and the year 2021. Its stated final selection logic adds market capitalization above 1 billion yuan and a price-to-earnings ratio below 30. The rationale is that clustered averages may help identify price support or resistance, while a middle range of turnover may indicate active trading. The sample code is inconsistent: its operations do not clearly implement the stated average-turnover and moving-average-confluence conditions, and some steps appear to apply thresholds to unrelated fields.

The author says the strict conditions may exclude relevant stocks and may fail when market sentiment shifts. It suggests adding valuation or size criteria and possibly using more complex forecasting methods. The note provides no historical performance statistics or validation, and the code does not establish a reproducible strategy. The criteria should therefore be treated as an informal screening proposal, not evidence of predictive value.

Key ideas

• The proposed screen uses five moving averages, 20-day average turnover between 2% and 9%, and a 2021 period.
• The stated final rules also require market capitalization above 1 billion yuan and price-to-earnings below 30.
• The author associates moving-average clustering with potential support and resistance analysis.
• The sample code does not clearly implement the stated conditions and appears internally inconsistent.
• No backtest evidence is provided, and strict filters may omit stocks or fail as market sentiment changes.

Tags

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