Combining RSI Midpoint and Moving Average Strategies in MQL5

Summary

The article shows how to add an RSI midpoint strategy to an MQL5 framework built around a moving average crossover strategy, then combine the components into an ensemble. The RSI logic buys below the midpoint and sells above it. The strategies are structured as classes sharing a parent interface, and the article discusses comparing a class-based implementation with a hard-coded baseline to check that both behave consistently. It also emphasizes limiting tunable parameters so optimization remains manageable.

The described workflow uses MetaTrader 5’s genetic optimizer and forward testing to select and assess parameter sets. It reports forward-test figures for the moving-average strategy and the RSI strategy, including Sharpe ratios, profits, and trade counts, with the RSI example showing stronger stated results and fewer trades. Those figures are specific to the article’s test setup and do not establish future performance. The text cautions that optimization cannot repair a fundamentally weak strategy and does not guarantee improvement.

Key ideas

• The RSI midpoint strategy buys below 50 and sells above 50.
• The RSI component is added to an MQL5 strategy framework and combined with a moving average crossover.
• A hard-coded baseline helps verify that a class-based strategy implementation matches expected behavior.
• Reducing the number of tunable parameters can make optimization more manageable.
• The reported forward-test comparison is specific to the authors’ setup and cannot guarantee future results.

Tags

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