MQL4 and MQL5 Programming Articles
Study the MQL5 language for programming trading strategies in numerous published articles mostly written by you - the community members. The articles are grouped into categories to help you quicker find answers to any questions related to programming: Integration, Tester, Trading Strategies, etc.
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On the Long Way to Be a Successful Trader - The Two Very First Steps
The main point of this article is to show a practical way to implement an effective MM. This can be achieved only by using a certain kind of strategies that we need to identify and describe first. In the following we’ll cover the basic concepts of how to build such a strategy and we’ll point out the common mistakes which always end up in draining a trader’s account.
Larry Williams Market Secrets (Part 4): Automating Short-Term Swing Highs and Lows in MQL5
Master the automation of Larry Williams’ short-term swing patterns using MQL5. In this guide, we develop a fully configurable Expert Advisor (EA) that leverages non-random market structures. We’ll cover how to integrate robust risk management and flexible exit logic, providing a solid foundation for systematic strategy development and backtesting.
A scientific approach to the development of trading algorithms
The article considers the methodology for developing trading algorithms, in which a consistent scientific approach is used to analyze possible price patterns and to build trading algorithms based on these patterns. Development ideals are demonstrated using examples.
Custom Graphical Controls. Part 3. Forms
This is the last of the three articles devoted to graphical controls. It covers the creation of the main graphical interface component - the form - and its use in combination with other controls. In addition to the form classes, CFrame, CButton, CLabel classes have been added to the control library.
Better programmer (Part 05): How to become a faster developer
Every developer wants to be able to write code faster, and being able to code faster and effective is not some kind of special ability that only a few people are born with. It's a skill that can be learned, that is what I'm trying to teach in this article.
How to Implement Auto Optimization in MQL5 Expert Advisors
Step by step guide for auto optimization in MQL5 for Expert Advisors. We will cover robust optimization logic, best practices for parameter selection, and how to reconstruct strategies with back-testing. Additionally, higher-level methods like walk-forward optimization will be discussed to enhance your trading approach.
Everything you need to learn about the MQL5 program structure
Any Program in any programming language has a specific structure. In this article, you will learn essential parts of the MQL5 program structure by understanding the programming basics of every part of the MQL5 program structure that can be very helpful when creating our MQL5 trading system or trading tool that can be executable in the MetaTrader 5.
Trading with the MQL5 Economic Calendar (Part 1): Mastering the Functions of the MQL5 Economic Calendar
In this article, we explore how to use the MQL5 Economic Calendar for trading by first understanding its core functionalities. We then implement key functions of the Economic Calendar in MQL5 to extract relevant news data for trading decisions. Finally, we conclude by showcasing how to utilize this information to enhance trading strategies effectively.
Prices in DoEasy library (Part 64): Depth of Market, classes of DOM snapshot and snapshot series objects
In this article, I will create two classes (the class of DOM snapshot object and the class of DOM snapshot series object) and test creation of the DOM data series.
MQL5 Cookbook: Analyzing Position Properties in the MetaTrader 5 Strategy Tester
We will present a modified version of the Expert Advisor from the previous article "MQL5 Cookbook: Position Properties on the Custom Info Panel". Some of the issues we will address include getting data from bars, checking for new bar events on the current symbol, including a trade class of the Standard Library to a file, creating a function to search for trading signals and a function for executing trading operations, as well as determining trade events in the OnTrade() function.
Price Action Analysis Toolkit Development (Part 52): Master Market Structure with Multi-Timeframe Visual Analysis
This article presents the Multi‑Timeframe Visual Analyzer, an MQL5 Expert Advisor that reconstructs and overlays higher‑timeframe candles directly onto your active chart. It explains the implementation, key inputs, and practical outcomes, supported by an animated demo and chart examples showing instant toggling, multi‑timeframe confirmation, and configurable alerts. Read on to see how this tool can make chart analysis faster, clearer, and more efficient.
Graphical Interfaces X: Sorting, rebuilding the table and controls in the cells (build 11)
We continue to add new features to the rendered table: data sorting, managing the number of columns and rows, setting the table cell types to place controls into them.
Price Action Analysis Toolkit Development (Part 51): Revolutionary Chart Search Technology for Candlestick Pattern Discovery
This article is intended for algorithmic traders, quantitative analysts, and MQL5 developers interested in enhancing their understanding of candlestick pattern recognition through practical implementation. It provides an in‑depth exploration of the CandlePatternSearch.mq5 Expert Advisor—a complete framework for detecting, visualizing, and monitoring classical candlestick formations in MetaTrader 5. Beyond a line‑by‑line review of the code, the article discusses architectural design, pattern detection logic, GUI integration, and alert mechanisms, illustrating how traditional price‑action analysis can be automated efficiently.
Timeseries in DoEasy library (part 36): Object of timeseries for all used symbol periods
In this article, we will consider combining the lists of bar objects for each used symbol period into a single symbol timeseries object. Thus, each symbol will have an object storing the lists of all used symbol timeseries periods.
Graphical Interfaces V: The List View Element (Chapter 2)
In the previous chapter, we wrote classes for creating vertical and horizontal scrollbars. In this chapter, we will implement them. We will write a class for creating the list view element, a compound part of which will be a vertical scrollbar.
Reimagining Classic Strategies (Part 20): Modern Stochastic Oscillators
This article demonstrates how the stochastic oscillator, a classical technical indicator, can be repurposed beyond its conventional use as a mean-reversion tool. By viewing the indicator through a different analytical lens, we show how familiar strategies can yield new value and support alternative trading rules, including trend-following interpretations. Ultimately, the article highlights how every technical indicator in the MetaTrader 5 terminal holds untapped potential, and how thoughtful trial and error can uncover meaningful interpretations hidden from view.
Graphical Interfaces XI: Integrating the Standard Graphics Library (build 16)
A new version of the graphics library for creating scientific charts (the CGraphic class) has been presented recently. This update of the developed library for creating graphical interfaces will introduce a version with a new control for creating charts. Now it is even easier to visualize data of different types.
Formulating Dynamic Multi-Pair EA (Part 5): Scalping vs Swing Trading Approaches
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.
Implementing an ARIMA training algorithm in MQL5
In this article we will implement an algorithm that applies the Box and Jenkins Autoregressive Integrated Moving Average model by using Powells method of function minimization. Box and Jenkins stated that most time series could be modeled by one or both of two frameworks.
Automating Trading Strategies in MQL5 (Part 14): Trade Layering Strategy with MACD-RSI Statistical Methods
In this article, we introduce a trade layering strategy that combines MACD and RSI indicators with statistical methods to automate dynamic trading in MQL5. We explore the architecture of this cascading approach, detail its implementation through key code segments, and guide readers on backtesting to optimize performance. Finally, we conclude by highlighting the strategy’s potential and setting the stage for further enhancements in automated trading.
Contest of Expert Advisors inside an Expert Advisor
Using virtual trading, you can create an adaptive Expert Advisor, which will turn on and off trades at the real market. Combine several strategies in a single Expert Advisor! Your multisystem Expert Advisor will automatically choose a trade strategy, which is the best to trade with at the real market, on the basis of profitability of virtual trades. This kind of approach allows decreasing drawdown and increasing profitability of your work at the market. Experiment and share your results with others! I think many people will be interested to know about your portfolio of strategies.
Designing and implementing new GUI widgets based on CChartObject class
After I wrote a previous article on semi-automatic Expert Advisor with GUI interface it turned out that it would be desirable to enhance interface with some new functionalities for more complex indicators and Expert Advisors. After getting acquainted with MQL5 standard library classes I implemented new widgets. This article describes a process of designing and implementing new MQL5 GUI widgets that can be used in indicators and Expert Advisors. The widgets presented in the article are CChartObjectSpinner, CChartObjectProgressBar and CChartObjectEditTable.
MetaTrader 5 Machine Learning Blueprint (Part 2): Labeling Financial Data for Machine Learning
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.
Trailing stop in trading
In this article, we will look at the use of a trailing stop in trading. We will assess how useful and effective it is, and how it can be used. The efficiency of a trailing stop largely depends on price volatility and the selection of the stop loss level. A variety of approaches can be used to set a stop loss.
Graphics in DoEasy library (Part 83): Class of the abstract standard graphical object
In this article, I will create the class of the abstract graphical object. This object is to serve as a basis for creating the class of standard graphical objects. Graphical objects feature multiple properties. Therefore, I will need to do a lot of preparatory work before actually creating the abstract graphical object class. This work includes setting the properties in the library enumerations.
Movement continuation model - searching on the chart and execution statistics
This article provides programmatic definition of one of the movement continuation models. The main idea is defining two waves — the main and the correction one. For extreme points, I apply fractals as well as "potential" fractals - extreme points that have not yet formed as fractals.
Advantages of MQL5 Signals
Trading Signals service recently introduced in MetaTrader 5 allows traders to copy trading operations of any signals provider. Users can select any signal, subscribe to it and all deals will be copied at their accounts. Signals providers can set their subscription prices and receive a fixed monthly fee from their subscribers.
Graphics in DoEasy library (Part 86): Graphical object collection - managing property modification
In this article, I will consider tracking property value modification, as well as removing and renaming graphical objects in the library.
Neural networks made easy (Part 5): Multithreaded calculations in OpenCL
We have earlier discussed some types of neural network implementations. In the considered networks, the same operations are repeated for each neuron. A logical further step is to utilize multithreaded computing capabilities provided by modern technology in an effort to speed up the neural network learning process. One of the possible implementations is described in this article.
Neural networks made easy (Part 29): Advantage Actor-Critic algorithm
In the previous articles of this series, we have seen two reinforced learning algorithms. Each of them has its own advantages and disadvantages. As often happens in such cases, next comes the idea to combine both methods into an algorithm, using the best of the two. This would compensate for the shortcomings of each of them. One of such methods will be discussed in this article.
DoEasy. Controls (Part 1): First steps
This article starts an extensive topic of creating controls in Windows Forms style using MQL5. My first object of interest is creating the panel class. It is already becoming difficult to manage things without controls. Therefore, I will create all possible controls in Windows Forms style.
Graphical Interfaces XI: Text edit boxes and Combo boxes in table cells (build 15)
In this update of the library, the Table control (the CTable class) will be supplemented with new options. The lineup of controls in the table cells is expanded, this time adding text edit boxes and combo boxes. As an addition, this update also introduces the ability to resize the window of an MQL application during its runtime.
The Principles of Economic Calculation of Indicators
Calls to user and technical indicators takes up very little space in the program code of automated trading systems. Often it’s simply a few code lines. But it often happens that it is these few lines of code which use up the largest portion of time, which needs to be spent on testing the Expert Advisor. Therefore, everything that is related to data calculations within an indicator, needs to be considered much more thoroughly than would seem at first glance. This article will talk precisely about this.
How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 6): Two RSI indicators cross each other's lines
The multi-currency expert advisor in this article is an expert advisor or trading robot that uses two RSI indicators with crossing lines, the Fast RSI which crosses with the Slow RSI.
Neural networks made easy (Part 27): Deep Q-Learning (DQN)
We continue to study reinforcement learning. In this article, we will get acquainted with the Deep Q-Learning method. The use of this method has enabled the DeepMind team to create a model that can outperform a human when playing Atari computer games. I think it will be useful to evaluate the possibilities of the technology for solving trading problems.
Cascade Order Trading Strategy Based on EMA Crossovers for MetaTrader 5
The article guides in demonstrating an automated algorithm based on EMA Crossovers for MetaTrader 5. Detailed information on all aspects of demonstrating an Expert Advisor in MQL5 and testing it in MetaTrader 5 - from analyzing price range behaviors to risk management.
Understand and Use MQL5 Strategy Tester Effectively
There is an essential need for MQL5 programmers or developers to master important and valuable tools. One of these tools is the Strategy Tester, this article is a practical guide to understanding and using the strategy tester of MQL5.
Optimal approach to the development and analysis of trading systems
In this article, I will show the criteria to be used when selecting a system or a signal for investing your funds, as well as describe the optimal approach to the development of trading systems and highlight the importance of this matter in Forex trading.
Deep Neural Networks (Part III). Sample selection and dimensionality reduction
This article is a continuation of the series of articles about deep neural networks. Here we will consider selecting samples (removing noise), reducing the dimensionality of input data and dividing the data set into the train/val/test sets during data preparation for training the neural network.