Stock Screening with Price Spikes and Moving Average Conditions

Summary

This proposed stock screen combines three conditions: at least five observations described as overlapping moving averages, a recent price surge, and at least two large gains within a longer lookback. The accompanying Python snippets calculate a rolling five-day close average and count daily percentage changes above 20%. The author frames the conditions as a way to narrow a stock universe and suggests adding company size, profitability, and financial health as further filters.

The code does not clearly implement the stated rules. Its moving-average calculation checks consecutive increases in one rolling average rather than overlap among several moving-average periods. The recent-surge function requires at least 25 qualifying observations, which does not match the description of a limit-up in the preceding 25 days. A fixed gain threshold also does not establish an exchange-defined limit-up. No performance or backtest evidence is presented, and the post itself warns that market declines may reduce qualifying candidates.

Key ideas

• The proposed screen combines moving-average behavior with large daily price gains over short and long lookbacks.
• The snippets use close-to-close percentage changes above 20% as a proxy for sharp gains.
• The moving-average code checks a single rolling average rather than overlap across several averages.
• The stated recent-event condition and the code’s requirement for many qualifying gains do not align.
• The document offers no backtest results and suggests adding fundamental filters.

Tags

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