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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Developing an MQTT client for MetaTrader 5: a TDD approach
This article reports the first attempts in the development of a native MQTT client for MQL5. MQTT is a Client Server publish/subscribe messaging transport protocol. It is lightweight, open, simple, and designed to be easy to implement. These characteristics make it ideal for use in many situations.
Category Theory in MQL5 (Part 8): Monoids
This article continues the series on category theory implementation in MQL5. Here we introduce monoids as domain (set) that sets category theory apart from other data classification methods by including rules and an identity element.
Building A Candlestick Trend Constraint Model (Part 1): For EAs And Technical Indicators
This article is aimed at beginners and pro-MQL5 developers. It provides a piece of code to define and constrain signal-generating indicators to trends in higher timeframes. In this way, traders can enhance their strategies by incorporating a broader market perspective, leading to potentially more robust and reliable trading signals.
Tomasz Tauzowski:"All I can do is pray for a loss position" (ATC 2010)
Tomasz Tauzowski (ttauzo) is a long-standing member of the top ten on the Automated Trading Championship 2010. For the seventh week his Expert Advisor is between the fifth and the seventh places. And no wonder: according to the report of the current Championship leader Boris Odinstov, ttauzo is one of the most stable EAs participating in the competition.
Expert Advisor based on the universal MLP approximator
The article presents a simple and accessible way to use a neural network in a trading EA that does not require deep knowledge of machine learning. The method eliminates the target function normalization, as well as overcomes "weight explosion" and "network stall" issues offering intuitive training and visual control of the results.
Overcoming ONNX Integration Challenges
ONNX is a great tool for integrating complex AI code between different platforms, it is a great tool that comes with some challenges that one must address to get the most out of it, In this article we discuss the common issues you might face and how to mitigate them.
Developing a Replay System (Part 53): Things Get Complicated (V)
In this article, we'll cover an important topic that few people understand: Custom Events. Dangers. Advantages and disadvantages of these elements. This topic is key for those who want to become a professional programmer in MQL5 or any other language. Here we will focus on MQL5 and MetaTrader 5.
Integrating ML models with the Strategy Tester (Conclusion): Implementing a regression model for price prediction
This article describes the implementation of a regression model based on a decision tree. The model should predict prices of financial assets. We have already prepared the data, trained and evaluated the model, as well as adjusted and optimized it. However, it is important to note that this model is intended for study purposes only and should not be used in real trading.
Interview with Evgeny Gnidko (ATC 2012)
The Expert Advisor of Evgeny Gnidko (FIFO) currently seems to be the most stable one at the Automated Trading Championship 2012. This trading robot entered TOP-10 at the third week remaining one of the leading Expert Advisors ever since.
Graphics in DoEasy library (Part 98): Moving pivot points of extended standard graphical objects
In the article, I continue the development of extended standard graphical objects and create the functionality for moving pivot points of composite graphical objects using the control points for managing the coordinates of the graphical object pivot points.
Price Action Analysis Toolkit Development Part (4): Analytics Forecaster EA
We are moving beyond simply viewing analyzed metrics on charts to a broader perspective that includes Telegram integration. This enhancement allows important results to be delivered directly to your mobile device via the Telegram app. Join us as we explore this journey together in this article.
Interview with Li Fang (ATC 2011)
On the seventh week of the Championship, Li Fang's Expert Advisor (lf8749) set a new record - it earned over $100,000 in 10 trades. This successful series helped the Expert Advisor to stay at the very top of the Automated Trading Championship 2011 rating for two weeks. In this interview we tried to find out the secret of Li Fang's success.
Neural networks made easy (Part 58): Decision Transformer (DT)
We continue to explore reinforcement learning methods. In this article, I will focus on a slightly different algorithm that considers the Agent’s policy in the paradigm of constructing a sequence of actions.
Monitoring trading with push notifications — example of a MetaTrader 5 service
In this article, we will look at creating a service app for sending notifications to a smartphone about trading results. We will learn how to handle lists of Standard Library objects to organize a selection of objects by required properties.
Non-linear regression models on the stock exchange
Non-linear regression models on the stock exchange: Is it possible to predict financial markets? Let's consider creating a model for forecasting prices for EURUSD, and make two robots based on it - in Python and MQL5.
Developing a Replay System — Market simulation (Part 05): Adding Previews
We have managed to develop a way to implement the market replay system in a realistic and accessible way. Now let's continue our project and add data to improve the replay behavior.
MQL5 Trading Tools (Part 21): Adding Cyberpunk Theme to Regression Graphs
In this article, we enhance the regression graphing tool in MQL5 by adding a cyberpunk theme mode with neon glows, animations, and holographic effects for immersive visualization. We integrate theme toggling, dynamic backgrounds with stars, glowing borders, and neon points/lines, while maintaining standard mode compatibility. This dual-theme system elevates pair analysis with futuristic aesthetics, supporting real-time updates and interactions for engaging trading insights.
Non-linear regression models on the stock exchange
Non-linear regression models on the stock exchange: Is it possible to predict financial markets? Let's consider creating a model for forecasting prices for EURUSD, and make two robots based on it - in Python and MQL5.
Neural networks made easy (Part 23): Building a tool for Transfer Learning
In this series of articles, we have already mentioned Transfer Learning more than once. However, this was only mentioning. in this article, I suggest filling this gap and taking a closer look at Transfer Learning.
Outline of MetaTrader Market (Infographics)
A few weeks ago we published the infographic on Freelance service. We also promised to reveal some statistics of the MetaTrader Market. Now, we invite you to examine the data we have gathered.
MQL5 Trading Tools (Part 6): Dynamic Holographic Dashboard with Pulse Animations and Controls
In this article, we create a dynamic holographic dashboard in MQL5 for monitoring symbols and timeframes with RSI, volatility alerts, and sorting options. We add pulse animations, interactive buttons, and holographic effects to make the tool visually engaging and responsive.
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.
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.
Building AI-Powered Trading Systems in MQL5 (Part 9): Creating an AI Signal Dispatcher
We turn the MQL5 AI trading assistant into a dispatch-driven system that routes seven trading actions through a single central dispatcher. A line-based key-value protocol constrains AI output, while each action maps to market or pending orders and instrument-aware stop levels. A canvas-based UI with a custom prompt editor and pixel-accurate text fitting makes signals consistent, auditable, and ready to render on the chart
Price Action Analysis Toolkit Development (Part 20): External Flow (IV) — Correlation Pathfinder
Correlation Pathfinder offers a fresh approach to understanding currency pair dynamics as part of the Price Action Analysis Toolkit Development Series. This tool automates data collection and analysis, providing insight into how pairs like EUR/USD and GBP/USD interact. Enhance your trading strategy with practical, real-time information that helps you manage risk and spot opportunities more effectively.
DoEasy. Controls (Part 26): Finalizing the ToolTip WinForms object and moving on to ProgressBar development
In this article, I will complete the development of the ToolTip control and start the development of the ProgressBar WinForms object. While working on objects, I will develop universal functionality for animating controls and their components.
Automating Black-Scholes Greeks: Advanced Scalping and Microstructure Trading
Gamma and Delta were originally developed as risk-management tools for hedging options exposure, but over time they evolved into powerful instruments for advanced scalping, order-flow modeling, and microstructure trading. Today, they serve as real-time indicators of price sensitivity and liquidity behavior, enabling traders to anticipate short-term volatility with remarkable precision.
Price Action Analysis Toolkit Development (Part 2): Analytical Comment Script
Aligned with our vision of simplifying price action, we are pleased to introduce another tool that can significantly enhance your market analysis and help you make well-informed decisions. This tool displays key technical indicators such as previous day's prices, significant support and resistance levels, and trading volume, while automatically generating visual cues on the chart.
Data Science and Machine Learning (Part 25): Forex Timeseries Forecasting Using a Recurrent Neural Network (RNN)
Recurrent neural networks (RNNs) excel at leveraging past information to predict future events. Their remarkable predictive capabilities have been applied across various domains with great success. In this article, we will deploy RNN models to predict trends in the forex market, demonstrating their potential to enhance forecasting accuracy in forex trading.
Integrate Your Own LLM into EA (Part 2): Example of Environment Deployment
With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to their needs, deploy them locally, and then apply them to algorithmic trading. This series of articles will take a step-by-step approach to achieve this goal.
Neural networks made easy (Part 73): AutoBots for predicting price movements
We continue to discuss algorithms for training trajectory prediction models. In this article, we will get acquainted with a method called "AutoBots".
Data label for timeseries mining (Part 2)：Make datasets with trend markers using Python
This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy of our model, and even help the model make a qualitative leap!
Developing Trading Strategies with the Parafrac and Parafrac V2 Oscillators: Single Entry Performance Insights
This article introduces the ParaFrac Oscillator and its V2 model as trading tools. It outlines three trading strategies developed using these indicators. Each strategy was tested and optimized to identify their strengths and weaknesses. Comparative analysis highlighted the performance differences between the original and V2 models.
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.
Swing Extremes and Pullbacks in MQL5 (Part 3): Defining Structural Validity Beyond Simple Highs/Lows
This article presents an MQL5 Expert Advisor that upgrades raw swing detection to a rule-based Structural Validation Engine. Swings are confirmed by a break of structure, displacement, liquidity sweeps, or time-based respect, then linked to a liquidity map and a structural state machine. The result is context-aware entries and stops anchored to validated levels, helping filter noise and systematize execution.
Data Science and ML(Part 30): The Power Couple for Predicting the Stock Market, Convolutional Neural Networks(CNNs) and Recurrent Neural Networks(RNNs)
In this article, We explore the dynamic integration of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) in stock market prediction. By leveraging CNNs' ability to extract patterns and RNNs' proficiency in handling sequential data. Let us see how this powerful combination can enhance the accuracy and efficiency of trading algorithms.
Neuro-symbolic systems in algorithmic trading: Combining symbolic rules and neural networks
The article describes the experience of developing a hybrid trading system that combines classical technical analysis with neural networks. The author provides a detailed analysis of the system architecture from basic pattern analysis and neural network structure to the mechanisms behind trading decisions, and shares real code and practical observations.
Introduction to MQL5 (Part 20): Introduction to Harmonic Patterns
In this article, we explore the fundamentals of harmonic patterns, their structures, and how they are applied in trading. You’ll learn about Fibonacci retracements, extensions, and how to implement harmonic pattern detection in MQL5, setting the foundation for building advanced trading tools and Expert Advisors.
Building AI-Powered Trading Systems in MQL5 (Part 9): Creating an AI Signal Dispatcher
We turn the MQL5 AI trading assistant into a dispatch-driven system that routes seven trading actions through a single central dispatcher. A line-based key-value protocol constrains AI output, while each action maps to market or pending orders and instrument-aware stop levels. A canvas-based UI with a custom prompt editor and pixel-accurate text fitting makes signals consistent, auditable, and ready to render on the chart
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).