MQL4 and MQL5 Programming Articles

In this article, we'll look at a few ideas, including how mathematical formulas are more complex in appearance than when implemented in code. In addition, we will consider how to set up a chart quadrant, as well as one interesting problem that may arise in your MQL5 code. Although, to be honest, I still don't quite understand how to explain it. Anyway, I'll show you how to fix it in code.

This article, the final in our series to tackle functors as a subject, revisits monoids as a category. Monoids which we have already introduced in these series are used here to aid in position sizing, together with multi-layer perceptrons.

Integer differentiation forces a binary choice between stationarity and memory: returns (d=1) are stationary but discard all price-level information; raw prices (d=0) preserve memory but violate ML stationarity assumptions. We implement the fixed-width fractional differentiation (FFD) method from AFML Chapter 5, covering get_weights_ffd (iterative recurrence with threshold cutoff), frac_diff_ffd (bounded dot product per bar), and fracdiff_optimal (binary search for minimum stationary d*).

This article demonstrates how to automatically identify potentially profitable trading strategies using MetaTrader 5. White-box solutions, powered by unsupervised matrix factorization, are faster to configure, more interpretable, and provide clear guidance on which strategies to retain. Black-box solutions, while more time-consuming, are better suited for complex market conditions that white-box approaches may not capture. Join us as we discuss how our trading strategies can help us carefully identify profitable strategies under any circumstance.

Find out how to build a practical CPU-to-GPU migration path in MQL5 using OpenCL. We will focus on context initialization, buffer organization, large batches, kernel startup, and minimizing data exchanges. Typical errors and ways to eliminate them will be considered as well. An example with candlestick patterns illustrates the practical benefit of the approach.

Today, we take an important step toward helping every developer understand how to read class structures and quickly build Expert Advisors using the MQL5 Standard Library. The library is rich and expandable, yet it can feel like being handed a complex toolkit without a manual. Here we share and discuss an alternative integration routine—a concise, repeatable workflow that shows how to connect classes reliably in real projects.

This article is part of a series describing our development steps of a native MQL5 client for the MQTT protocol. In this part we describe our code organization, the first header files and classes, and how we are writing our tests. This article also includes brief notes about the Test-Driven-Development practice and how we are applying it to this project.

The article describes the practical application of DirectX 11 and built-in MQL5 tools for creating 3D visualizations and interactive interfaces in MetaTrader 5. The focus is on cognitive efficiency - the ability of 3D charts and guided scenes to help in understanding optimization data, liquidity clusters, and multi-dimensional trading scenarios. The basics of the DX pipeline, working with shaders, binding mouse and keyboard events, and objective technological limitations are discussed in detail. The article is intended for MQL5 developers and algorithmic traders who are ready to transform strategy metrics into understandable 3D analytical landscapes, where the visual layer accelerates decision-making.

In this article, we'll look at what you need to do to start using Excel to manage MetaTrader 5, but in a very interesting way. To do this, we will use an Excel add-in to avoid using built-in VBA. If you don't know what add-in is meant, read this article and learn how to program in Python directly in Excel.

The article explores the Battle Royale Optimizer algorithm — a metaheuristic in which solutions compete with their nearest neighbors, accumulate “damage,” are replaced when a threshold is exceeded, and periodically shrink the search space around the current best solution. It presents both pseudocode and an MQL5 implementation of the CAOBRO class, including neighbor search, movement toward the best solution, and an adaptive delta interval. Test results on the Hilly, Forest, and Megacity functions highlight the strengths and limitations of the approach. The reader is provided with a ready-to-use foundation for experimentation and tuning key parameters such as popSize and maxDamage.

This article which is part of a series that follows Category Theory implementation of Graphs in MQL5, delves in Orders. We examine how concepts of Order-Theory can support monoid sets in informing trade decisions by considering two major ordering types.

In this article, we will look at an innovative optimization method called BSO (Brain Storm Optimization) inspired by a natural phenomenon called "brainstorming". We will also discuss a new approach to solving multimodal optimization problems the BSO method applies. It allows finding multiple optimal solutions without the need to pre-determine the number of subpopulations. We will also consider the K-Means and K-Means++ clustering methods.

In this article, we present an MQL5 implementation of Stepwise Feature Selection based on the mutual information between an optimal predictor set and a target variable.

As we explained in the first article about SQL, there is no point in spending time programming procedures to do what is already built into SQL. However, without knowing the basics, you won’t be able to do anything with SQL or take full advantage of everything this tool offers. Therefore, in this article, we will look at how to perform basic tasks in databases.