MQL4 and MQL5 Programming Articles

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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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Decoding Opening Range Breakout Intraday Trading Strategies

Decoding Opening Range Breakout Intraday Trading Strategies

Opening Range Breakout (ORB) strategies are built on the idea that the initial trading range established shortly after the market opens reflects significant price levels where buyers and sellers agree on value. By identifying breakouts above or below a certain range, traders can capitalize on the momentum that often follows as the market direction becomes clearer. In this article, we will explore three ORB strategies adapted from the Concretum Group.
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Advanced resampling and selection of CatBoost models by brute-force method

Advanced resampling and selection of CatBoost models by brute-force method

This article describes one of the possible approaches to data transformation aimed at improving the generalizability of the model, and also discusses sampling and selection of CatBoost models.
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ALGLIB numerical analysis library in MQL5

ALGLIB numerical analysis library in MQL5

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.
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Backpropagation Neural Networks using MQL5 Matrices

Backpropagation Neural Networks using MQL5 Matrices

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.
Technical Analysis: What Do We Analyze?
Technical Analysis: What Do We Analyze?

Technical Analysis: What Do We Analyze?

This article tries to analyze several peculiarities of representation of quotes available in the MetaTrader client terminal. The article is general, it doesn't concern programming.
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Category Theory in MQL5 (Part 14): Functors with Linear-Orders

Category Theory in MQL5 (Part 14): Functors with Linear-Orders

This article which is part of a broader series on Category Theory implementation in MQL5, delves into Functors. We examine how a Linear Order can be mapped to a set, thanks to Functors; by considering two sets of data that one would typically dismiss as having any connection.
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Data Science and Machine Learning (Part 07): Polynomial Regression

Data Science and Machine Learning (Part 07): Polynomial Regression

Unlike linear regression, polynomial regression is a flexible model aimed to perform better at tasks the linear regression model could not handle, Let's find out how to make polynomial models in MQL5 and make something positive out of it.
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Timeseries in DoEasy library (part 54): Descendant classes of abstract base indicator

Timeseries in DoEasy library (part 54): Descendant classes of abstract base indicator

The article considers creation of classes of descendant objects of base abstract indicator. Such objects will provide access to features of creating indicator EAs, collecting and getting data value statistics of various indicators and prices. Also, create indicator object collection from which getting access to properties and data of each indicator created in the program will be possible.
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Automating Trading Strategies in MQL5 (Part 17): Mastering the Grid-Mart Scalping Strategy with a Dynamic Dashboard

Automating Trading Strategies in MQL5 (Part 17): Mastering the Grid-Mart Scalping Strategy with a Dynamic Dashboard

In this article, we explore the Grid-Mart Scalping Strategy, automating it in MQL5 with a dynamic dashboard for real-time trading insights. We detail its grid-based Martingale logic and risk management features. We also guide backtesting and deployment for robust performance.
Graphics in DoEasy library (Part 90): Standard graphical object events. Basic functionality
Graphics in DoEasy library (Part 90): Standard graphical object events. Basic functionality

Graphics in DoEasy library (Part 90): Standard graphical object events. Basic functionality

In this article, I will implement the basic functionality for tracking standard graphical object events. I will start from a double click event on a graphical object.
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Experiments with neural networks (Part 2): Smart neural network optimization

Experiments with neural networks (Part 2): Smart neural network optimization

In this article, I will use experimentation and non-standard approaches to develop a profitable trading system and check whether neural networks can be of any help for traders. MetaTrader 5 as a self-sufficient tool for using neural networks in trading.
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Population optimization algorithms: Harmony Search (HS)

Population optimization algorithms: Harmony Search (HS)

In the current article, I will study and test the most powerful optimization algorithm - harmonic search (HS) inspired by the process of finding the perfect sound harmony. So what algorithm is now the leader in our rating?
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Canvas based indicators: Filling channels with transparency

Canvas based indicators: Filling channels with transparency

In this article I'll introduce a method for creating custom indicators whose drawings are made using the class CCanvas from standard library and see charts properties for coordinates conversion. I'll approach specially indicators which need to fill the area between two lines using transparency.
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Data Science and Machine Learning (Part 06): Gradient Descent

Data Science and Machine Learning (Part 06): Gradient Descent

The gradient descent plays a significant role in training neural networks and many machine learning algorithms. It is a quick and intelligent algorithm despite its impressive work it is still misunderstood by a lot of data scientists let's see what it is all about.
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Neural networks made easy (Part 15): Data clustering using MQL5

Neural networks made easy (Part 15): Data clustering using MQL5

We continue to consider the clustering method. In this article, we will create a new CKmeans class to implement one of the most common k-means clustering methods. During tests, the model managed to identify about 500 patterns.
MQL4  as a Trader's Tool, or The Advanced Technical Analysis
MQL4  as a Trader's Tool, or The Advanced Technical Analysis

MQL4 as a Trader's Tool, or The Advanced Technical Analysis

Trading is, first of all, a calculus of probabilities. The proverb about idleness being an engine for progress reveals us the reason why all those indicators and trading systems have been developed. It comes that the major of newcomers in trading study "ready-made" trading theories. But, as luck would have it, there are some more undiscovered market secrets, and tools used in analyzing of price movements exist, basically, as those unrealized technical indicators or math and stat packages. Thanks awfully to Bill Williams for his contribution to the market movements theory. Though, perhaps, it's too early to rest on oars.
Nikolay Ivanov (Techno): "What is important for programs is the accuracy of their algorithms"
Nikolay Ivanov (Techno): "What is important for programs is the accuracy of their algorithms"

Nikolay Ivanov (Techno): "What is important for programs is the accuracy of their algorithms"

A programmer from Krasnoyarsk Nikolay Ivanov (Techno) is a leader among the developers in terms of the number of completed orders - he has implemented already more than 200 applications in the Jobs service. In this interview, he is talking about the Jobs service, its specific features and challengers faced by programmers.
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Build Self Optimizing Expert Advisors in MQL5 (Part 6): Self Adapting Trading Rules (II)

Build Self Optimizing Expert Advisors in MQL5 (Part 6): Self Adapting Trading Rules (II)

This article explores optimizing RSI levels and periods for better trading signals. We introduce methods to estimate optimal RSI values and automate period selection using grid search and statistical models. Finally, we implement the solution in MQL5 while leveraging Python for analysis. Our approach aims to be pragmatic and straightforward to help you solve potentially complicated problems, with simplicity.
Beginners' Mistakes when Working with MetaTrader 4 Client Terminal
Beginners' Mistakes when Working with MetaTrader 4 Client Terminal

Beginners' Mistakes when Working with MetaTrader 4 Client Terminal

Err is human. Everybody makes mistakes: more or less frequently, through ignorance or inadvertently. You ask and we answer your questions about: terminal time, test results, Print in journal, symbols, history for Tester, history import, leverage, traffic, hints, scaling, wrong calculations, Invalid account, Empty News, Price changed, Not Enough Money, Market Is Closed.
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Tips from a professional programmer (Part III): Logging. Connecting to the Seq log collection and analysis system

Tips from a professional programmer (Part III): Logging. Connecting to the Seq log collection and analysis system

Implementation of the Logger class for unifying and structuring messages which are printed to the Experts log. Connection to the Seq log collection and analysis system. Monitoring log messages online.
MT4TerminalSync - System for the Synchronization of MetaTrader 4 Terminals
MT4TerminalSync - System for the Synchronization of MetaTrader 4 Terminals

MT4TerminalSync - System for the Synchronization of MetaTrader 4 Terminals

This article is devoted to the topic "Widening possibilities of MQL4 programs by using functions of operating systems and other means of program development". The article describes an example of a program system that implements the task of the synchronization of several terminal copies based on a single source template.
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Developing a trading Expert Advisor from scratch (Part 9): A conceptual leap (II)

Developing a trading Expert Advisor from scratch (Part 9): A conceptual leap (II)

In this article, we will place Chart Trade in a floating window. In the previous part, we created a basic system which enables the use of templates within a floating window.
Timeseries in DoEasy library (part 48): Multi-period multi-symbol indicators on one buffer in a subwindow
Timeseries in DoEasy library (part 48): Multi-period multi-symbol indicators on one buffer in a subwindow

Timeseries in DoEasy library (part 48): Multi-period multi-symbol indicators on one buffer in a subwindow

The article considers an example of creating multi-symbol multi-period standard indicators using a single indicator buffer for construction and working in the indicator subwindow. I am going to prepare the library classes for working with standard indicators working in the program main window and having more than one buffer for displaying their data.
How we developed the MetaTrader Signals service and Social Trading
How we developed the MetaTrader Signals service and Social Trading

How we developed the MetaTrader Signals service and Social Trading

We continue to enhance the Signals service, improve the mechanisms, add new functions and fix flaws. The MetaTrader Signals Service of 2012 and the current MetaTrader Signals Service are like two completely different services. Currently, we are implementing A Virtual Hosting Cloud service which consists of a network of servers to support specific versions of the MetaTrader client terminal.
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Developing a trading Expert Advisor from scratch (Part 13): Time and Trade (II)

Developing a trading Expert Advisor from scratch (Part 13): Time and Trade (II)

Today we will construct the second part of the Times & Trade system for market analysis. In the previous article "Times & Trade (I)" we discussed an alternative chart organization system, which would allow having an indicator for the quickest possible interpretation of deals executed in the market.
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Algorithmic trading based on 3D reversal patterns

Algorithmic trading based on 3D reversal patterns

Discovering a new world of automated trading on 3D bars. What does a trading robot look like on multidimensional price bars? Are "yellow" clusters of 3D bars able to predict trend reversals? What does multidimensional trading look like?
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Introduction to MQL5 (Part 12): A Beginner's Guide to Building Custom Indicators

Introduction to MQL5 (Part 12): A Beginner's Guide to Building Custom Indicators

Learn how to build a custom indicator in MQL5. With a project-based approach. This beginner-friendly guide covers indicator buffers, properties, and trend visualization, allowing you to learn step-by-step.
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Neural networks made easy (Part 32): Distributed Q-Learning

Neural networks made easy (Part 32): Distributed Q-Learning

We got acquainted with the Q-learning method in one of the earlier articles within this series. This method averages rewards for each action. Two works were presented in 2017, which show greater success when studying the reward distribution function. Let's consider the possibility of using such technology to solve our problems.
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Reimagining Classic Strategies (Part 13): Minimizing The Lag in Moving Average Cross-Overs

Reimagining Classic Strategies (Part 13): Minimizing The Lag in Moving Average Cross-Overs

Moving average cross-overs are widely known by traders in our community, and yet the core of the strategy has changed very little since its inception. In this discussion, we will present you with a slight adjustment to the original strategy, that aims to minimize the lag present in the trading strategy. All fans of the original strategy, could consider revising the strategy in accordance with the insights we will discuss today. By using 2 moving averages with the same period, we reduce the lag in the trading strategy considerably, without violating the foundational principles of the strategy.
The Random Sandbox
The Random Sandbox

The Random Sandbox

The article includes an interactive "sandbox" as an Excel file which simulates randomized Expert Advisor backtest data. Readers can use this to help explore and more deeply understand the EA performance metrics offered by default with MetaTrader. The text of the article is designed to guide the user through this experience.
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Parallel Particle Swarm Optimization

Parallel Particle Swarm Optimization

The article describes a method of fast optimization using the particle swarm algorithm. It also presents the method implementation in MQL, which is ready for use both in single-threaded mode inside an Expert Advisor and in a parallel multi-threaded mode as an add-on that runs on local tester agents.
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How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 4): Triangular moving average — Indicator Signals

How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 4): Triangular moving average — Indicator Signals

The Multi-Currency Expert Advisor in this article is Expert Advisor or trading robot that can trade (open orders, close orders and manage orders for example: Trailing Stop Loss and Trailing Profit) for more than one symbol pair only from one symbol chart. This time we will use only 1 indicator, namely Triangular moving average in multi-timeframes or single timeframe.
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Neural networks made easy (Part 25): Practicing Transfer Learning

Neural networks made easy (Part 25): Practicing Transfer Learning

In the last two articles, we developed a tool for creating and editing neural network models. Now it is time to evaluate the potential use of Transfer Learning technology using practical examples.
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MQL5 Cookbook — Macroeconomic events database

MQL5 Cookbook — Macroeconomic events database

The article discusses the possibilities of handling databases based on the SQLite engine. The CDatabase class has been formed for convenience and efficient use of OOP principles. It is subsequently involved in the creation and management of the database of macroeconomic events. The article provides the examples of using multiple methods of the CDatabase class.
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Category Theory (Part 9): Monoid-Actions

Category Theory (Part 9): Monoid-Actions

This article continues the series on category theory implementation in MQL5. Here we continue monoid-actions as a means of transforming monoids, covered in the previous article, leading to increased applications.
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Population optimization algorithms: Grey Wolf Optimizer (GWO)

Population optimization algorithms: Grey Wolf Optimizer (GWO)

Let's consider one of the newest modern optimization algorithms - Grey Wolf Optimization. The original behavior on test functions makes this algorithm one of the most interesting among the ones considered earlier. This is one of the top algorithms for use in training neural networks, smooth functions with many variables.
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Price Action Analysis Toolkit Development (Part 19): ZigZag Analyzer

Price Action Analysis Toolkit Development (Part 19): ZigZag Analyzer

Every price action trader manually uses trendlines to confirm trends and spot potential turning or continuation levels. In this series on developing a price action analysis toolkit, we introduce a tool focused on drawing slanted trendlines for easy market analysis. This tool simplifies the process for traders by clearly outlining key trends and levels essential for effective price action evaluation.
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DoEasy. Controls (Part 6): Panel control, auto resizing the container to fit inner content

DoEasy. Controls (Part 6): Panel control, auto resizing the container to fit inner content

In the article, I will continue my work on the Panel WinForms object and implement its auto resizing to fit the general size of Dock objects located inside the panel. Besides, I will add the new properties to the Symbol library object.
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Automating Trading Strategies in MQL5 (Part 20): Multi-Symbol Strategy Using CCI and AO

Automating Trading Strategies in MQL5 (Part 20): Multi-Symbol Strategy Using CCI and AO

In this article, we create a multi-symbol trading strategy using CCI and AO indicators to detect trend reversals. We cover its design, MQL5 implementation, and backtesting process. The article concludes with tips for performance improvement.
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Neural networks made easy (Part 76): Exploring diverse interaction patterns with Multi-future Transformer

Neural networks made easy (Part 76): Exploring diverse interaction patterns with Multi-future Transformer

This article continues the topic of predicting the upcoming price movement. I invite you to get acquainted with the Multi-future Transformer architecture. Its main idea is to decompose the multimodal distribution of the future into several unimodal distributions, which allows you to effectively simulate various models of interaction between agents on the scene.