Equity Screen Using Price Range, Turnover, and Recent Return

Summary

This post presents a simple stock-selection filter based on three recent market characteristics: daily price amplitude above 1%, prior-day trading volume above 60 million, and a return between -5% and 2.6%. It explains that the conditions combine price movement, trading activity, and recent performance, and includes a Python example that calculates each filter and intersects them.

The author cautions that price change alone does not capture broader market conditions or company quality, so the screen can select stocks that look active while having weak underlying prospects. The post recommends considering company-level information, moving averages, volume measures, or indicators such as MACD. It provides no backtest, return analysis, market universe definition, or evidence that the thresholds have predictive value. The thresholds and example are presented as a screening recipe rather than a validated trading strategy.

Key ideas

• The screen requires daily price amplitude above 1% and prior-day volume above 60 million.
• It also restricts the recent return to between -5% and 2.6%.
• The accompanying example calculates the three filters and combines them.
• The post gives no performance test and warns that market and company fundamentals are omitted.

Tags

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