Stock Momentum Screening with Moving Averages, Turnover, and Limit-Up Days

Summary

This note describes a stock screen using three signals: at least five moving averages converging, turnover within a specified range, and more than two limit-up days over a recent window. Its discussion frames clustered averages as relatively stable price behavior, the turnover filter as moderate activity, and repeated limit-up moves as evidence of strong market interest. It then proposes changing the moving-average horizon and broadening the turnover and observation windows, although those revised conditions differ from the original screen.

The note identifies broad market declines and execution mistakes as risks, but provides no backtest or return evidence. Its final stated criteria also conflict with the original thresholds, and the attached Python example is truncated. The visible code uses cryptocurrency exchange tooling for a stock-selection description and does not clearly calculate moving-average convergence, turnover bands, or official limit-up events. The strategy is therefore best read as a rough screening idea rather than a validated or reproducible trading method.

Key ideas

• The initial screen combines moving-average convergence, a turnover band, and multiple limit-up days.
• The note interprets these conditions as signs of stable price behavior, moderate activity, and strong recent demand.
• Its proposed revised thresholds differ from those in the initial screen.
• It names market declines and trading errors as risks but provides no performance results.
• The sample implementation is incomplete and does not clearly reproduce the stated stock filters.

Tags

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