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Screening Stocks with a Morning-Star Pattern and Moving-Average Trend Filter

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Summary

This stock-selection example combines a daily range filter, a morning-star-style candlestick condition, and a trend filter requiring the 20-day moving average to be above the 120-day moving average. Its accompanying indicator formula also includes a turnover-based condition. The Python example describes checking recent price data, excluding one market segment, requiring turnover above a stated threshold, and calculating the two moving averages. It presents the approach as a short-term technical screen rather than a complete investment system.

The post offers no historical test, trade list, or performance statistics to establish whether the combined conditions have predictive value. It acknowledges that the method omits fundamental analysis and that the absence of robust volume or liquidity screening can leave less-tradable stocks in the results. It also notes that reliance on moving averages may fail to capture some rising stocks. The proposed improvements are to incorporate measures of business quality and growth, use volume to assess liquidity, and adapt moving-average choices to market and industry conditions. The implementation details differ across the formula and Python examples, so they should not be assumed to describe an identical, validated rule set.

Key ideas

  • The screen combines a daily range condition, a morning-star-style pattern, and a 20-day average above the 120-day average.
  • The indicator formula adds a turnover-related condition, while the Python example uses its own turnover threshold.
  • The post frames the screen as a short-term technical method and provides no reported performance evidence.
  • The author identifies missing fundamental analysis and potential liquidity problems as limitations.
  • Suggested refinements include adding business metrics and volume filters and adapting moving-average choices to market conditions.

Tags

China marketsEquitiesTechnical indicatorsTrend followingRisk management

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