Implementing a button for managing advisor functions can streamline workflow. This example demonstrates how a button is used to close all active positions across various instruments. The example also includes functionality for handling button events. Methods are provided for closing positions based on the symbol name and for counting positions related to each symbol. This allows for efficient control and management of trading positions. By integrating these methods, advisors can enhance their trading logic and improve execution efficiency. Such implementations aid in maintaining structured and responsive trading systems. This systematic approach benefits both new and experienced developers in optimizing code performance.

👉 Read | Forum | @mql5dev

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The "Quarters Theory" indicator segments price movements around a central reference level, enhancing analysis for multiple assets including Forex, stocks, and commodities. This tool provides visual representation of quarter divisions on the chart, aiding in technical analysis by highlighting potential support and resistance levels.

The indicator calculates a flexible base level, with options including current daily close, previous day, week, and month closes, as well as user-defined levels. It supports various units for quarter size, appropriate for different instruments: pips for Forex, points for other assets, percentages of the base level, or fixed price values.

It adapts automatically to distinguish between Forex and non-Forex assets, adjusts pip calculations accordingly, and manages situations with unavailable timeframes. This makes it a versat...

👉 Read | Signals | @mql5dev

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Explore the advanced framework for enhancing algorithmic trading with MetaTrader 5. The article introduces a disciplined pipeline that filters noise in indicator selection, highlighting its transformation into a predictive engine using a compact neural network. This network is trained on multi-quarter data, outputting an ONNX model for seamless integration with MQL5. Practical advancements include adaptive indicators like FrAMA and TRIX, alongside a robust feature and label engineering process ensuring reliable predictions. Emphasizing a straightforward multi-layer perceptron (MLP) structure, the approach focuses on efficient, transparent model deployment, minimizing overfitting risks and enhancing real-time trading strategy execution.

👉 Read | AppStore | @mql5dev

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In this update of our AI-powered trading system in MQL5, we've focused on further modularization and the automation of trading functionalities. The UI components have been separated into a dedicated include file, enhancing code cleanliness and maintainability. This also streamlines development, testing, and integration of new features like dynamic UIs and automatic signal execution.

Automatic signal checks have been implemented for new bars, enabling trade execution based on AI-generated signals parsed from JSON input. These signals outline entry points and Stop-Loss/Take-Profit levels, offering a clear trading strategy devoid of emotional biases, and improving efficiency.

Our visualization system now signals patterns like engulfing or divergences on charts using arrows, lines, and labels, facilitating clear pattern recognition. We've also implemen...

👉 Read | NeuroBook | @mql5dev

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