Screening Stocks by Turnover, Three Down Days, and Long-Term Trend

Summary

This post describes a Chinese stock screen using turnover between stated bounds, three consecutive declining closes, and a prior closing price above its 250-day moving average. It includes a technical-indicator formula and a Python example that queries daily price history and filters stocks based on recent closes and a long-term average. The accompanying discussion notes that the rule relies on technical conditions and suggests incorporating company fundamentals for a broader assessment.

The document offers screening logic and implementation examples, but it reports no backtest, return statistics, or portfolio construction and execution rules. The Python example uses an average of earlier closes as its trend comparison rather than explicitly calculating a 250-day moving average, and it does not implement the stated turnover range. Those differences mean the sample code may not reproduce the described screen. The rule is a candidate filter, not evidence of predictive value, and would need consistent definitions and testing with realistic costs and point-in-time data.

Key ideas

• The described screen combines bounded turnover with three declining sessions and a close above the 250-day average.
• The post provides formula and historical-price query examples for screening Chinese equities.
• The Python example does not fully implement the stated turnover filter or explicit 250-day average.
• The document provides no performance evidence and identifies fundamentals as a possible additional input.

Tags

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