Metatrader 5 / Metatrader 4 for MQL5 / MQL4 articles preview

In the previous article "Developing a Replay System (Part 77): New Chart Trade (IV), I explained the subject as thoroughly as possible, while trying not to overcomplicate matters, even though this is often a rather complex topic. The question at hand is: how do you develop a communication protocol? This is essential if you want to transfer information between different applications or programs, whether they are running in the same environment or not. In our specific case, we want the Chart Trade indicator to be able to instruct the Expert Advisor on what actions to take. In other words, when the user tells Chart Trade they want to sell, the Expert Advisor will execute a sell order. When the user indicates they want to buy, the Expert Advisor will place a market buy order.

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At the time this article is being written, the new repository is already available for use, but MetaEditor integration has not yet been completed. Thus, while MetaEditor remains the main development environment, developers are still limited to MQL Storage based on SVN.

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Does anyone have an updated link to this article? I’d like to drop the code into HFM's MT5 Strategy Tester and benchmark execution vs the MQL4 version across a few symbols

In the first article, we began transitioning from the built-in SVN-based MQL5 Storage in MetaEditor to a more flexible and modern solution based on the Git version control system: MQL5 Algo Forge. The main reason for this step was the need to fully leverage repository branches while working on multiple projects or on different functionalities within a single project.

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In our previous article (Part 35), we developed a Breaker Block Trading System in MetaQuotes Language 5 (MQL5) that identified consolidation ranges, validated breaker blocks with swing points, and traded retests with customizable risk parameters and visual feedback. In Part 36, we develop a Supply and Demand Trading System utilizing a retest and impulse model. This model detects supply and demand zones through consolidation, validates them with impulsive moves, and executes trades on retests with trend confirmation and dynamic chart visualizations.

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In today's article, we will take a closer look at the stage of publishing the edits made in the repository, a certain set of changes that form a complete solution, whether it's adding new functionality to a project or fixing a discovered issue. This is the process of committing or releasing a new product version. We will see how to organize this process and what capabilities MQL5 Algo Forge provides for it.

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We looked at how to manually set up support and resistance zones using the rectangle chart object in Part 24 of this series. This allowed you to create a semi-automated trading system that reacts to the zones you draw. However, what if you want the EA to automatically, without human assistance, identify every support and resistance zone on the chart? This article will specifically address that. As usual, we will cover MQL5 principles in a hands-on, beginner-friendly manner using a project-based approach. You'll discover how to identify these zones programmatically, track price movements surrounding them, and create an EA that responds sensibly to possible reversals.

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Explore practical Metatrader 5 and 4 articles focused on MQL5 and MQL4 programming. Learn strategy coding, indicator creation, backtesting, and optimization with clear examples and step-by-step tutorials. Suitable for beginners and experienced developers seeking efficient EA development, debugging tips, and performance improvements to build robust automated trading systems today confidently.

By leveraging the capabilities of MQL5, we can precisely define the times we want to trade and receive alerts accordingly. In our previous discussion, we established the foundation for session visualization, where we uncovered the structure of each trading session—its body, upper wick, and lower wick. That project enabled us to visualize the broader market structure across higher-timeframe sessions, synchronized with lower-timeframe data to reveal the magnified internal price movements and patterns forming within.

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I research on HFM MT5 for the multi-threaded tester and better Python bridges, but I still execute on MT4 where my broker’s plugins and trade copier live. That split workflow has been the most stable combo for me