Rule-Based Head and Shoulders Detection with ATR and Breakout Confirmation

Summary

The article presents a structured method for detecting standard and inverse Head and Shoulders formations in an MQL5 chart indicator. It identifies swing highs and lows, then checks candidate formations using the relative positions of the shoulders and head, shoulder symmetry, minimum pattern size normalized by ATR, and limits on neckline slope. A quality score helps screen candidates. The indicator draws the pattern and neckline, and treats a neckline break as confirmation before displaying a directional marker or alert.

The method addresses the subjectivity of visual pattern recognition by turning its criteria into adjustable rules. Parameters control swing sensitivity, tolerances, spacing, pattern size, and scoring thresholds. The document describes the result as an indicator for visualization and signal generation, rather than a complete automated trading strategy. Although it says examples were detected, it supplies no quantitative evidence of predictive performance, false-signal rates, or profitability. Thresholds may therefore need testing and adaptation across instruments and timeframes.

Key ideas

• The scanner builds candidate patterns from detected swing highs and lows.
• It validates geometry with symmetry rules, neckline slope limits, and ATR-normalized size requirements.
• A neckline break confirms a candidate and can trigger a visual signal or alert.
• The indicator supports inverse formations and provides adjustable detection and display settings.
• The article gives no quantitative evidence that the detected patterns are profitable.

Tags

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