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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Deconstructing examples of trading strategies in the client terminal

Deconstructing examples of trading strategies in the client terminal

The article uses block diagrams to examine the logic of the candlestick-based training EAs located in the Experts\Free Robots folder of the terminal.
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Benefiting from Forex market seasonality

Benefiting from Forex market seasonality

We are all familiar with the concept of seasonality, for example, we are all accustomed to rising prices for fresh vegetables in winter or rising fuel prices during severe frosts, but few people know that similar patterns exist in the Forex market.
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Developing a multi-currency Expert Advisor (Part 19): Creating stages implemented in Python

Developing a multi-currency Expert Advisor (Part 19): Creating stages implemented in Python

So far we have considered the automation of launching sequential procedures for optimizing EAs exclusively in the standard strategy tester. But what if we would like to perform some handling of the obtained data using other means between such launches? We will attempt to add the ability to create new optimization stages performed by programs written in Python.
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Mastering File Operations in MQL5: From Basic I/O to Building a Custom CSV Reader

Mastering File Operations in MQL5: From Basic I/O to Building a Custom CSV Reader

This article focuses on essential MQL5 file-handling techniques, spanning trade logs, CSV processing, and external data integration. It offers both conceptual understanding and hands-on coding guidance. Readers will learn to build a custom CSV importer class step-by-step, gaining practical skills for real-world applications.
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Mastering Quick Trades: Overcoming Execution Paralysis

Mastering Quick Trades: Overcoming Execution Paralysis

The UT BOT ATR Trailing Indicator is a personal and customizable indicator that is very effective for traders who like to make quick decisions and make money from differences in price referred to as short-term trading (scalpers) and also proves to be vital and very effective for long-term traders (positional traders).
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Finding custom currency pair patterns in Python using MetaTrader 5

Finding custom currency pair patterns in Python using MetaTrader 5

Are there any repeating patterns and regularities in the Forex market? I decided to create my own pattern analysis system using Python and MetaTrader 5. A kind of symbiosis of math and programming for conquering Forex.
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DoEasy. Controls (Part 5): Base WinForms object, Panel control, AutoSize parameter

DoEasy. Controls (Part 5): Base WinForms object, Panel control, AutoSize parameter

In the article, I will create the base object of all library WinForms objects and start implementing the AutoSize property of the Panel WinForms object — auto sizing for fitting the object internal content.
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Overcoming The Limitation of Machine Learning (Part 5): A Quick Recap of Time Series Cross Validation

Overcoming The Limitation of Machine Learning (Part 5): A Quick Recap of Time Series Cross Validation

In this series of articles, we look at the challenges faced by algorithmic traders when deploying machine-learning-powered trading strategies. Some challenges within our community remain unseen because they demand deeper technical understanding. Today’s discussion acts as a springboard toward examining the blind spots of cross-validation in machine learning. Although often treated as routine, this step can easily produce misleading or suboptimal results if handled carelessly. This article briefly revisits the essentials of time series cross-validation to prepare us for more in-depth insight into its hidden blind spots.
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Experiments with neural networks (Part 4): Templates

Experiments with neural networks (Part 4): Templates

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. Simple explanation.
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Engineering Trading Discipline into Code (Part 3): Enforcing Symbol-Level Trading Boundaries with a Whitelist System in MQL5

Engineering Trading Discipline into Code (Part 3): Enforcing Symbol-Level Trading Boundaries with a Whitelist System in MQL5

This article details an MQL5 framework that restricts trading to an approved set of symbols. The solution combines a shared library, a configuration dashboard, and an enforcement Expert Advisor that validates each trade against a whitelist and logs blocked attempts. It includes fully functional code examples, a clear explanation of the structural design decisions, and validation tests that confirm reliable symbol filtering, controlled market exposure, and transparent monitoring of rule enforcement.
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Understand and efficiently use OpenCL API by recreating built-in support as DLL on Linux (Part 1): Motivation and validation

Understand and efficiently use OpenCL API by recreating built-in support as DLL on Linux (Part 1): Motivation and validation

Bulit-in OpenCL support in MetaTrader 5 still has a major problem especially the one about device selection error 5114 resulting from unable to create an OpenCL context using CL_USE_GPU_ONLY, or CL_USE_GPU_DOUBLE_ONLY although it properly detects GPU. It works fine with directly using of ordinal number of GPU device we found in Journal tab, but that's still considered a bug, and users should not hard-code a device. We will solve it by recreating an OpenCL support as DLL with C++ on Linux. Along the journey, we will get to know OpenCL from concept to best practices in its API usage just enough for us to put into great use later when we deal with DLL implementation in C++ and consume it with MQL5.
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Neural Networks in Trading: Hybrid Graph Sequence Models (GSM++)

Neural Networks in Trading: Hybrid Graph Sequence Models (GSM++)

Hybrid graph sequence models (GSM++) combine the advantages of different architectures to provide high-fidelity data analysis and optimized computational costs. These models adapt effectively to dynamic market data, improving the presentation and processing of financial information.
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Creating a market making algorithm in MQL5

Creating a market making algorithm in MQL5

How do market makers work? Let's consider this issue and create a primitive market-making algorithm.
Andrey Voitenko: Programming errors cost me $15,000 (ATC 2010)
Andrey Voitenko: Programming errors cost me $15,000 (ATC 2010)

Andrey Voitenko: Programming errors cost me $15,000 (ATC 2010)

Andrey Voitenko is participating in the Automated Trading Championship for the first time, but his Expert Advisor is showing mature trading. For already several weeks Andrey's Expert Advisors has been listed in the top ten and seems to be continuing his positive performance. In this interview Andrey is telling about his EA's features, errors and the price they cost him.
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MetaTrader Meets Google Sheets with Pythonanywhere: A Guide to Secure Data Flow

MetaTrader Meets Google Sheets with Pythonanywhere: A Guide to Secure Data Flow

This article demonstrates a secure way to export MetaTrader data to Google Sheets. Google Sheet is the most valuable solution as it is cloud based and the data saved in there can be accessed anytime and from anywhere. So traders can access trading and related data exported to google sheet and do further analysis for future trading anytime and wherever they are at the moment.
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Data Science and Machine Learning(Part 14): Finding Your Way in the Markets with Kohonen Maps

Data Science and Machine Learning(Part 14): Finding Your Way in the Markets with Kohonen Maps

Are you looking for a cutting-edge approach to trading that can help you navigate complex and ever-changing markets? Look no further than Kohonen maps, an innovative form of artificial neural networks that can help you uncover hidden patterns and trends in market data. In this article, we'll explore how Kohonen maps work, and how they can be used to develop smarter, more effective trading strategies. Whether you're a seasoned trader or just starting out, you won't want to miss this exciting new approach to trading.
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News Trading Made Easy (Part 3): Performing Trades

News Trading Made Easy (Part 3): Performing Trades

In this article, our news trading expert will begin opening trades based on the economic calendar stored in our database. In addition, we will improve the expert's graphics to display more relevant information about upcoming economic calendar events.
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Neural Networks in Trading: A Multimodal, Tool-Augmented Agent for Financial Markets (Final Part)

Neural Networks in Trading: A Multimodal, Tool-Augmented Agent for Financial Markets (Final Part)

We continue to develop the algorithms for FinAgent, a multimodal financial trading agent designed to analyze multimodal market dynamics data and historical trading patterns.
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William Gann methods (Part III): Does Astrology Work?

William Gann methods (Part III): Does Astrology Work?

Do the positions of planets and stars affect financial markets? Let's arm ourselves with statistics and big data, and embark on an exciting journey into the world where stars and stock charts intersect.
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Data Science and ML (Part 42): Forex Time series Forecasting using ARIMA in Python, Everything you need to Know

Data Science and ML (Part 42): Forex Time series Forecasting using ARIMA in Python, Everything you need to Know

ARIMA, short for Auto Regressive Integrated Moving Average, is a powerful traditional time series forecasting model. With the ability to detect spikes and fluctuations in a time series data, this model can make accurate predictions on the next values. In this article, we are going to understand what is it, how it operates, what you can do with it when it comes to predicting the next prices in the market with high accuracy and much more.
Market Diagnostics by Pulse
Market Diagnostics by Pulse

Market Diagnostics by Pulse

In the article, an attempt is made to visualize the intensity of specific markets and of their time segments, to detect their regularities and behavior patterns.
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Population optimization algorithms: Artificial Bee Colony (ABC)

Population optimization algorithms: Artificial Bee Colony (ABC)

In this article, we will study the algorithm of an artificial bee colony and supplement our knowledge with new principles of studying functional spaces. In this article, I will showcase my interpretation of the classic version of the algorithm.
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DoEasy. Controls (Part 29): ScrollBar auxiliary control

DoEasy. Controls (Part 29): ScrollBar auxiliary control

In this article, I will start developing the ScrollBar auxiliary control element and its derivative objects — vertical and horizontal scrollbars. A scrollbar is used to scroll the content of the form if it goes beyond the container. Scrollbars are usually located at the bottom and to the right of the form. The horizontal one at the bottom scrolls content left and right, while the vertical one scrolls up and down.
Testing Visualization: Account State Charts
Testing Visualization: Account State Charts

Testing Visualization: Account State Charts

Enjoy the process of testing with charts, displaying the balance - now all the necessary information is always in view!
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Implementing the SHA-256 Cryptographic Algorithm from Scratch in MQL5

Implementing the SHA-256 Cryptographic Algorithm from Scratch in MQL5

Building DLL-free cryptocurrency exchange integrations has long been a challenge, but this solution provides a complete framework for direct market connectivity.
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Mastering PD Arrays: Optimizing Trading from Imbalances in PD Arrays

Mastering PD Arrays: Optimizing Trading from Imbalances in PD Arrays

This is an article about a specialized trend-following EA that aims to clearly elaborate how to frame and utilize trading setups that occur from imbalances found in PD arrays. This article will explore in detail an EA that is specifically designed for traders who are keen on optimizing and utilizing PD arrays and imbalances as entry criteria for their trades and trading decisions. It will also explore how to correctly determine and profile premium and discount arrays and how to validate and utilize each of them when they occur in their respective market conditions, thus trying to maximize opportunities that occur from such scenarios.
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Developing a trading Expert Advisor from scratch (Part 23): New order system (VI)

Developing a trading Expert Advisor from scratch (Part 23): New order system (VI)

We will make the order system more flexible. Here we will consider changes to the code that will make it more flexible, which will allow us to change position stop levels much faster.
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MQL5 Wizard Techniques you should know (Part 71): Using Patterns of MACD and the OBV

MQL5 Wizard Techniques you should know (Part 71): Using Patterns of MACD and the OBV

The Moving-Average-Convergence-Divergence (MACD) oscillator and the On-Balance-Volume (OBV) oscillator are another pair of indicators that could be used in conjunction within an MQL5 Expert Advisor. This pairing, as is practice in these article series, is complementary with the MACD affirming trends while OBV checks volume. As usual, we use the MQL5 wizard to build and test any potential these two may possess.
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Population optimization algorithms: Stochastic Diffusion Search (SDS)

Population optimization algorithms: Stochastic Diffusion Search (SDS)

The article discusses Stochastic Diffusion Search (SDS), which is a very powerful and efficient optimization algorithm based on the principles of random walk. The algorithm allows finding optimal solutions in complex multidimensional spaces, while featuring a high speed of convergence and the ability to avoid local extrema.
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Self Optimizing Expert Advisors in MQL5 (Part 17): Ensemble Intelligence

Self Optimizing Expert Advisors in MQL5 (Part 17): Ensemble Intelligence

All algorithmic trading strategies are difficult to set up and maintain, regardless of complexity—a challenge shared by beginners and experts alike. This article introduces an ensemble framework where supervised models and human intuition work together to overcome their shared limitations. By aligning a moving average channel strategy with a Ridge Regression model on the same indicators, we achieve centralized control, faster self-correction, and profitability from otherwise unprofitable systems.
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Neural Networks in Trading: Scene-Aware Object Detection (HyperDet3D)

Neural Networks in Trading: Scene-Aware Object Detection (HyperDet3D)

We invite you to get acquainted with a new approach to detecting objects using hypernetworks. A hypernetwork generates weights for the main model, which allows taking into account the specifics of the current market situation. This approach allows us to improve forecasting accuracy by adapting the model to different trading conditions.
Interview with Egidijus Bockus (ATC 2012)
Interview with Egidijus Bockus (ATC 2012)

Interview with Egidijus Bockus (ATC 2012)

"I examined many indicators before realizing that they are not necessary for making money on Forex" - our present interviewee Egidijus Bockus (Egidijus) told us boldly. We have all reasons to take his words seriously, as his Expert Advisor occupies the third place with more than $32 000 beginning from the third week of the Automated Trading Championship 2012.
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Population optimization algorithms: Firefly Algorithm (FA)

Population optimization algorithms: Firefly Algorithm (FA)

In this article, I will consider the Firefly Algorithm (FA) optimization method. Thanks to the modification, the algorithm has turned from an outsider into a real rating table leader.
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MetaTrader 5 Machine Learning Blueprint (Part 8): Bayesian Hyperparameter Optimization with Purged Cross-Validation and Trial Pruning

MetaTrader 5 Machine Learning Blueprint (Part 8): Bayesian Hyperparameter Optimization with Purged Cross-Validation and Trial Pruning

GridSearchCV and RandomizedSearchCV share a fundamental limitation in financial ML: each trial is independent, so search quality does not improve with additional compute. This article integrates Optuna — using the Tree-structured Parzen Estimator — with PurgedKFold cross-validation, HyperbandPruner early stopping, and a dual-weight convention that separates training weights from evaluation weights. The result is a five-component system: an objective function with fold-level pruning, a suggestion layer that optimizes the weighting scheme jointly with model hyperparameters, a financially-calibrated pruner, a resumable SQLite-backed orchestrator, and a converter to scikit-learn cv_results_ format. The article also establishes the boundary — drawn from Timothy Masters — between statistical objectives where directed search is beneficial and financial objectives where it is harmful.
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Master MQL5 from beginner to pro (Part V): Fundamental control flow operators

Master MQL5 from beginner to pro (Part V): Fundamental control flow operators

This article explores the key operators used to modify the program's execution flow: conditional statements, loops, and switch statements. Utilizing these operators will allow the functions we create to behave more "intelligently".
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Creating 3D bars based on time, price and volume

Creating 3D bars based on time, price and volume

The article dwells on multivariate 3D price charts and their creation. We will also consider how 3D bars predict price reversals, and how Python and MetaTrader 5 allow us to plot these volume bars in real time.
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Neural Networks Made Easy (Part 87): Time Series Patching

Neural Networks Made Easy (Part 87): Time Series Patching

Forecasting plays an important role in time series analysis. In the new article, we will talk about the benefits of time series patching.
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Matrix Utils, Extending the Matrices and Vector Standard Library Functionality

Matrix Utils, Extending the Matrices and Vector Standard Library Functionality

Matrix serves as the foundation of machine learning algorithms and computers in general because of their ability to effectively handle large mathematical operations, The Standard library has everything one needs but let's see how we can extend it by introducing several functions in the utils file, that are not yet available in the library
Interview with Alexander Prishchenko (ATC 2012)
Interview with Alexander Prishchenko (ATC 2012)

Interview with Alexander Prishchenko (ATC 2012)

What can be more complicated than a multicurrency trading robot? Surely, it is an automated strategy based on Elliott Wave Principle. Can we imagine something more complicated than that? Yes, we can. It is a multicurrency Expert Advisor using Elliott Waves on each currency pair! Alexander Prishchenko (Crucian) believes that even a newcomer can learn the rules.
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MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library

MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library

Learn how to create a developer's toolkit for managing various position operations with MQL5. In this article, I will demonstrate how to create a library of functions (ex5) that will perform simple to advanced position management operations, including automatic handling and reporting of the different errors that arise when dealing with position management tasks with MQL5.