Stock Screening by Price Range, Daily Amplitude, and Positive P/E

Summary

This stock screen combines a price-movement threshold with a low share-price condition and positive earnings valuation. The stated logic selects stocks whose high–low amplitude exceeds 1%, whose closing price is below 20, and whose price-to-earnings ratio is above zero. The document provides both a formula-style expression and a Python outline for applying those filters; it does not report a tested universe, performance results, or a holding and execution method.

The accompanying discussion says amplitude and price action may reflect short-term activity, while positive P/E excludes companies with negative earnings. It cautions that market sentiment and policy changes can make outcomes unstable, and that P/E alone does not capture company quality. It suggests adding measures such as price-to-book and return on equity, or using machine learning, but supplies no model specification or evidence that these additions improve results. The amplitude calculation differs between the formula example and Python outline in its reference price, so an implementation should define that convention consistently.

Key ideas

• The screen requires amplitude above 1%, closing price below 20, and positive P/E.
• The examples express the same filters in formula-style and Python forms.
• The document warns that market conditions can destabilize results and P/E is an incomplete measure of company quality.
• It suggests adding other fundamental measures, but gives no evidence that these changes improve performance.

Tags

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