Stock Screening with Moving Average Crossovers and a Morning Star Pattern

Summary

The document outlines a short-term stock screen that combines a price-range condition, three moving-average crossover signals, and a candlestick reversal pattern. It also suggests considering financial measures and industry prospects when assessing candidates. The examples describe the pattern using recent and current open and close prices, and provide sample screening logic and a Python implementation. The samples do not fully agree: the written rule calls for amplitude above a threshold, while the Python selection does not apply that condition; the code also uses different crossover and moving-average conditions from the prose.

The post cautions that short-term technical signals omit longer-term prospects and fundamentals, and says the pattern’s independent effectiveness has not been established. It presents no performance results or validation study. The screen is therefore an illustrative rule set, not evidence of a profitable strategy; parameter choices, data handling, and out-of-sample testing would need to be addressed before practical use.

Key ideas

• The proposed screen combines price amplitude, three moving-average crossovers, and a bullish candlestick reversal pattern.
• The post recommends reviewing company financials and industry outlook alongside technical signals.
• The written criteria and sample Python implementation differ, including whether amplitude is applied.
• The document provides no backtest or evidence that the pattern adds predictive value.

Tags

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