Quantifying Support, Resistance, Touches, and Breakouts from Price History
Summary
The document presents an MQL5 tool for testing a chosen price level against historical bars. It classifies touches using a configurable pip tolerance and assigns direction by the bar close. A breakout requires a close beyond the level by a separate margin, with the preceding close on the other side. Counts of bullish and bearish touches and breakouts are converted into sample frequencies, then used to label the level as support, resistance, or neutral.
A GBP/USD example describes repeated rejection, later support, and a subsequent break that turned the level into resistance. This illustrates how level behavior can change over time, while the tool’s proposed output makes interactions easier to count consistently than visual recall alone. The article argues that these measurements can inform backtesting or further research, but they describe only the selected historical window. They are not forecasts, and the stated rules depend on user choices such as tolerance, breakout margin, and lookback length; no evidence here establishes future profitability.
Key ideas
- A pip-based tolerance makes touch classification explicit and repeatable.
- A confirmed breakout requires a close beyond a threshold and a prior close on the opposite side.
- Directional touch and breakout counts can be summarized as empirical frequencies for a chosen sample.
- Support and resistance classifications can reverse as price behavior changes.
- Historical event frequencies describe the sample and should not be treated as guaranteed forecasts.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.