MQL5 Algo Trading
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In Part 10 of our series on MQL5 for Expert Advisors, we introduce a strategy tracker system that enhances real-time performance monitoring. This system is capable of detecting moving average crossover signals filtered by a long-term moving average, and visualizes trade actions on the chart. It provides a comprehensive dashboard with performance metrics, including total signals, wins/losses, profit points, and success rates.

Implementation involves creating enumerations, input parameters, global variables, and helper functions for visualization. We leverage the MQL5 environment to handle moving averages, signal detection, and position tracking. Key features include modular dashboard creation, signal visualization, and both virtual and real trade simulations. This tool supports strategy evaluation, allowing for dynamic adjustments based on detailed f...

πŸ‘‰ Read | AppStore | @mql5dev

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Explore the power of time-filtered trading within the MQL5 framework, where precision meets discipline. Using modular components such as the TimeFilter layer and SessionVisualizer, we can define specific trading windows, ensuring trades execute only during optimal market conditions. This approach minimizes noise and leverages session-based volatility, providing clarity and adaptability in trading strategies. By combining clock, session, and event-driven controls, traders and developers can create sophisticated automated systems that respond not just to price signals, but aligned with the market's temporal rhythm, enhancing decision accuracy and strategic performance in algorithmic trading environments.

πŸ‘‰ Read | Docs | @mql5dev

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The application of one-position-type strategies in live market environments presents an analysis based on Nvidia Corp’s stock (NVDA). Training and testing were conducted over distinct time periods, utilizing signals derived from multiple oscillator integrations, specifically RSI and DeMarker. Each pattern analyzes specific market movements, aiming to optimize entry and exit points across varying market conditions.

Pattern-5 focuses on slope confluence with range expansion, where synchronized momentum and price movements are logged. The buy signals are derived when RSI and DeMarker conditions align, demonstrating increased trader activity and potential market volatility.

Forward testing of Pattern-6 capitalizes on leading price movements with lagging indicators, identifying pullback entries for order continuation. The setup confirms trend strength w...

πŸ‘‰ Read | CodeBase | @mql5dev

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Enhancing black-box models for trading strategy selection presents complex challenges. Traditional metrics like RMSE often mislead due to sensitivity to scale and lack of comparability across regression targets. Mutual Information (MI) offers a more robust alternative. Its nonparametric nature and unitless measurement provide a consistent comparison across targets, helping identify the most informative strategies.

Empirical results demonstrate MI's superiority. Models predicting changes in the Stochastic oscillator show marked improvements, reflecting market width better than others. Visual analysis through scatterplots and bar plots further validate these findings, reinforcing MI's reliability.

In application, a neural network model, backed by ONNX, enables real-time strategy execution in MQL5, leveraging newfound insights for improved decision-ma...

πŸ‘‰ Read | AlgoBook | @mql5dev

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