Stock Screening with Price, Range, and Order-Flow Filters

Summary

This Chinese-language post proposes a stock screen using daily price range, closing price, and the ratio of outside to inside trading volume. Its stated core thresholds are amplitude above 1, close below 20, and outside volume divided by inside volume above 1.3. The post also presents platform-specific formula and Python examples; the Python version adds a positive price-change condition, while the formula includes additional volume, volatility, and trend-related filters. These variants are not fully consistent, so an implementation would need to resolve which conditions define the intended screen.

The rationale is that range and price behavior capture technical conditions while the trading-volume ratio may help assess market pressure. No historical sample, benchmark, or performance statistics are supplied. The author notes market risk and suggests adding fundamental data and other indicators, potentially with machine learning. The thresholds and order-flow measures are not justified or validated in the text, and the screen should not be treated as evidence of durable returns.

Key ideas

• The proposed screen selects stocks using an amplitude threshold, a low closing price, and an outside-to-inside volume ratio above a stated cutoff.
• The Python example also requires positive price change, while the platform formula adds other filters.
• The post offers a technical and order-flow rationale but gives no backtest evidence.
• The thresholds and differing implementations require clarification and independent validation.
• The author suggests combining additional fundamental and technical data for possible refinement.

Tags

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