Automatic Support and Resistance Lines for Continuation Breakouts

Summary

This research note describes a method for detecting support and resistance lines in Chinese A-share price series. It adapts a local high and low point approach with quantile regression, defining line slopes for continuation patterns such as triangles, rectangles, flags, and broadening formations. The method treats chart patterns as geometric relationships between price movements and their future returns. The analysis reports that upside breaks above resistance after bullish continuation patterns had stronger subsequent returns than the full sample, especially among smaller companies. Downside breaks below support showed weaker subsequent returns, also most notably among smaller firms. A further finding links favorable upside breakouts to prior gains above 20% followed by a sideways or broadening consolidation with a particular combination of support and resistance slopes. A strategy based on this setup had lower returns than its benchmark but reduced maximum drawdown and improved its Sharpe ratio during the sample period. These results are historical and the authors warn that the model may stop working.

Key ideas

• Local price highs and lows combined with quantile regression can automate support and resistance detection.
• Continuation patterns can be characterized by the slopes of their upper and lower boundaries.
• Upside resistance breaks and downside support breaks showed different return behavior in the A-share sample.
• The reported strategy traded after prior gains and a specific consolidation pattern, with improved risk measures versus its benchmark.
• Historical pattern relationships may not persist in future markets.

Tags

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