Detecting Historical Support and Resistance Levels with Candle Patterns and Clustering

Summary

The document describes an indicator that estimates historical support and resistance levels from repeated prices and candle behavior. It proposes two bullish-candle rules around candidate levels: a minimum difference between close and low, with an additional candle-range ratio condition for one resistance case. The indicator gathers qualifying support and resistance observations into separate datasets, then applies K-means clustering to group them into levels that it draws on a chart.

The author presents the tool as showing strong support and resistance behavior and suggests extending it with more rules, region-specific clustering, and analysis of the maximum move before a level is revisited. The description offers a conceptual method and implementation outline, but the referenced images are unavailable here and no sample statistics, predictive tests, or trading results are provided. The rules’ parameters, level definition, and treatment of repeated observations are not specified in enough detail to assess robustness. The proposed levels should therefore be understood as exploratory chart features, not demonstrated forecasts of price reversals or jumps.

Key ideas

• The method collects candidate levels from historical prices and candle formations.
• It uses close-to-low distance and, in one rule, a candle-range ratio to identify bullish responses.
• Support and resistance observations are stored separately and grouped with K-means clustering.
• The resulting clusters are plotted as levels on the analyzed instrument’s chart.
• No statistical validation or trading performance evidence is presented.

Tags

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