MQL4 and MQL5 Programming Articles

This part explores how to design a Dynamic Multi-Pair Expert Advisor capable of adapting between Scalping and Swing Trading modes. It covers the structural and algorithmic differences in signal generation, trade execution, and risk management, allowing the EA to intelligently switch strategies based on market behavior and user input.

In this article we will look at the MqlDateTime, MqlTick, MqlRates and MqlBookInfo strutures, as well as methods for printing data from them. In order to print all the fields of a structure, there is a standard ArrayPrint() function, which displays the data contained in the array with the type of the handled structure in a convenient tabular format.

Accurate calculation of key trading values is an indispensable part of every trader’s workflow. In this article, we will discuss, the integration of a powerful utility—the Forex Calculator—into the Trade Management Panel, further extending the functionality of our multi-panel Trading Administrator system. Efficiently determining risk, position size, and potential profit is essential when placing trades, and this new feature is designed to make that process faster and more intuitive within the panel. Join us as we explore the practical application of MQL5 in building advanced, trading panels.

In this article, I will make an attempt to consider some ways of building non-linear indicators and their use in trading. There are quite a few indicators in the MetaTrader trading platform that use non-linear approaches.

In this article, we develop a Pin Bar Averaging system in MQL5 that detects pin bar patterns to initiate trades and employs an averaging strategy for multi-position management, enhanced by trailing stops and breakeven adjustments. We incorporate customizable parameters with a dashboard for real-time monitoring of positions and profits.

The metabar-based indicator detected more candles than the conventional one. Let's check if this provides real benefit in the automated trading.

In this second installment of the MetaTrader 5 Machine Learning Blueprint series, you’ll discover why simple labels can lead your models astray—and how to apply advanced techniques like the Triple-Barrier and Trend-Scanning methods to define robust, risk-aware targets. Packed with practical Python examples that optimize these computationally intensive techniques, this hands-on guide shows you how to transform noisy market data into reliable labels that mirror real-world trading conditions.

The article describes the theory and practice of applying the backpropagation algorithm in MQL5 using matrices. It provides ready-made classes along with script, indicator and Expert Advisor examples.

The article takes a quick look at the ALGLIB 3.19 numerical analysis library, its applications and new algorithms that can improve the efficiency of financial data analysis.

In this article, we apply a relatively complex neural network algorithm released in 2023 called PatchTST for predicting the price action for the next 24 hours. We will use the official repository, make slight modifications, train a model for EURUSD, and apply it to making future predictions both in Python and MQL5.

How to access custom indicators directly in an Expert Advisor? A trading EA can be truly useful only if it can use custom indicators; otherwise, it is just a set of codes and instructions.

Global market sessions shape the rhythm of the trading day, and understanding their overlap is vital to timing entries and exits. In this article, we’ll build an interactive trading sessions  EA that brings those global hours to life directly on your chart. The EA automatically plots color‑coded rectangles for the Asia, Tokyo, London, and New York sessions, updating in real time as each market opens or closes. It features on‑chart toggle buttons, a dynamic information panel, and a scrolling ticker headline that streams live status and breakout messages. Tested on different brokers, this EA combines precision with style—helping traders see volatility transitions, identify cross‑session breakouts, and stay visually connected to the global market’s pulse.

This is a continuation of the series for beginners. In this article, we'll look at how to create constants and variables, write dates, colors, and other useful data. We will learn how to create enumerations like days of the week or line styles (solid, dotted, etc.). Variables and expressions are the basis of programming. They are definitely present in 99% of programs, so understanding them is critical. Therefore, if you are new to programming, this article can be very useful for you. Required programming knowledge level: very basic, within the limits of my previous article (see the link at the beginning).

In this article, we will learn how to make the MetaTrader 5 platform talk. What if we make the EA more fun? Financial market trading is often too boring and monotonous, but we can make this job less tiring. Please note that this project can be dangerous for those who experience problems such as addiction. However, in a general case, it just makes things less boring.

There are several types of algorithms for self-optimization of trading strategies and parameters. These algorithms are used to automatically improve trading strategies based on historical and current market data. In this article we will look at one of them with python and MQL5 examples.

The article will be useful for both beginners and experienced developers. We will look at the PrintFormat() function, analyze examples of string formatting and write templates for displaying various information in the terminal log.

This topic focuses on incorporating a trained AI model (such as a reinforcement learning model like LSTM or a machine learning-based predictive model) into an existing MQL5 trading strategy.