Stock Screening by Price Range, Turnover, Auction Volume, and Market Heat

Summary

This Chinese equity-screening proposal selects stocks with a stated price-amplitude threshold and a ratio combining the previous day's turnover rate with current auction volume relative to prior volume. It keeps values within a specified range, then ranks candidates by a measure described as individual-stock heat and selects the highest-ranked names. The article frames the filters as a way to capture volatility, liquidity, and short-term attention, but does not define a reproducible heat measure in the prose.

The post includes a Python example, though parts of the described logic and code do not align cleanly, and it offers no backtest or return evidence. It acknowledges that the limited filters can miss market, sector, and company fundamentals, and that selection timing may change results. Suggested additions include industry, growth, technical, and sentiment information, as well as attention to market conditions. These are recommendations, not demonstrated improvements.

Key ideas

• The screen combines a price-amplitude condition with turnover and auction-volume information.
• Candidates are ranked by a stock-heat measure, whose definition is not clearly specified.
• The post provides an implementation example but no backtest or performance evidence.
• The author notes that the simple filters omit important market, sector, and company factors.

Tags

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