A Small-Cap Screen Using Price Range, Profitability, and Recent Returns

Summary

This document outlines an equity screen beginning with stocks whose daily price range exceeds 1%, market capitalization is at most 10 billion yuan, and average net profit is positive, while excluding stocks that hit the daily limit on the prior session. Its expanded selection logic adds a relative-strength condition, proximity to a moving average, and profitability-based scoring. The Python example also applies growth, valuation, and cash-flow filters, then sorts candidates by a score.

The document gives no backtest or evidence of realized returns. Its stated refinements and sample implementation do not align cleanly: for example, the narrative mentions a five-day and thirty-day moving-average comparison, while the code uses a thirty-day price average and adds several financial filters. The strategy also depends on data fields and definitions that are not explained. The author notes that technical conditions alone can miss business and growth risks and suggests broader fundamental assessment and position-level risk controls.

Key ideas

• The initial screen uses daily price range, a market-cap ceiling, positive average net profit, and prior-session limit-up exclusion.
• The proposed refinements add relative strength, moving-average proximity, and earnings-based ranking.
• The sample code includes additional growth, valuation, and cash-flow filters whose definitions are not explained.
• The prose and implementation differ on parts of the moving-average logic.
• No backtest or performance evidence is provided, so the screen remains an unvalidated selection framework.

Tags

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