Discussing the article: "Automating Trading Strategies in MQL5 (Part 34): Trendline Breakout System with R-Squared Goodness of Fit"
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Check out the new article: Automating Trading Strategies in MQL5 (Part 34): Trendline Breakout System with R-Squared Goodness of Fit.
In this article, we develop a Trendline Breakout System in MQL5 that identifies support and resistance trendlines using swing points, validated by R-squared goodness of fit and angle constraints, to automate breakout trades.Our plan is to detect swing highs and lows within a specified lookback period, construct trendlines with a minimum number of touch points, and validate them using R-squared metrics and angle constraints to ensure reliability.
The trendline breakout strategy involves drawing diagonal lines on price charts to connect swing highs (resistance) or swing lows (support), identifying key price levels where the market is likely to reverse or continue. When the price breaks through these trendlines—either closing above a resistance line or below a support line—it signals a potential shift in market momentum, prompting traders to enter trades in the direction of the breakout with defined risk and reward parameters. This approach capitalizes on strong price movements following the break, aiming to capture significant trends while managing risk through stop-loss and take-profit levels. Here is an illustration of a downward trendline breakout.
Our plan is to detect swing highs and lows within a specified lookback period, construct trendlines with a minimum number of touch points, and validate them using R-squared metrics and angle constraints to ensure reliability. In case you need to know, R-squared, also called the coefficient of determination, is a statistical measure that indicates how well a regression model explains the variability of the dependent variable using the independent variables. It represents the proportion of the total variation in the outcome that is accounted for by the model, with values ranging from 0 to 1. Here is a quick visualization of the model.
Author: Allan Munene Mutiiria