Articles with examples of trading robots developed in MQL5

icon

An Expert Advisor is the 'pinnacle' of programming and the desired goal of every automated trading developer. Read the articles in this section to create your own trading robot. By following the described steps you will learn how to create, debug and test automated trading systems.

The articles not only teach MQL5 programming, but also show how to implement trading ideas and techniques. You will learn how to program a trailing stop, how to apply money management, how to get the indicator values, and much more.

Add a new article
latest | best
preview
Triangular arbitrage with predictions

Triangular arbitrage with predictions

This article simplifies triangular arbitrage, showing you how to use predictions and specialized software to trade currencies smarter, even if you're new to the market. Ready to trade with expertise?
preview
From Novice to Expert: Animated News Headline Using MQL5 (II)

From Novice to Expert: Animated News Headline Using MQL5 (II)

Today, we take another step forward by integrating an external news API as the source of headlines for our News Headline EA. In this phase, we’ll explore various news sources—both established and emerging—and learn how to access their APIs effectively. We'll also cover methods for parsing the retrieved data into a format optimized for display within our Expert Advisor. Join the discussion as we explore the benefits of accessing news headlines and the economic calendar directly on the chart, all within a compact, non-intrusive interface.
preview
Developing a trading Expert Advisor from scratch (Part 20): New order system (III)

Developing a trading Expert Advisor from scratch (Part 20): New order system (III)

We continue to implement the new order system. The creation of such a system requires a good command of MQL5, as well as an understanding of how the MetaTrader 5 platform actually works and what resources it provides.
preview
Neural networks made easy (Part 37): Sparse Attention

Neural networks made easy (Part 37): Sparse Attention

In the previous article, we discussed relational models which use attention mechanisms in their architecture. One of the specific features of these models is the intensive utilization of computing resources. In this article, we will consider one of the mechanisms for reducing the number of computational operations inside the Self-Attention block. This will increase the general performance of the model.
preview
Creating an Interactive Graphical User Interface in MQL5 (Part 2): Adding Controls and Responsiveness

Creating an Interactive Graphical User Interface in MQL5 (Part 2): Adding Controls and Responsiveness

Enhancing the MQL5 GUI panel with dynamic features can significantly improve the trading experience for users. By incorporating interactive elements, hover effects, and real-time data updates, the panel becomes a powerful tool for modern traders.
preview
Raw Code Optimization and Tweaking for Improving Back-Test Results

Raw Code Optimization and Tweaking for Improving Back-Test Results

Enhance your MQL5 code by optimizing logic, refining calculations, and reducing execution time to improve back-test accuracy. Fine-tune parameters, optimize loops, and eliminate inefficiencies for better performance.
preview
Build Self Optimizing Expert Advisors With MQL5 And Python (Part II): Tuning Deep Neural Networks

Build Self Optimizing Expert Advisors With MQL5 And Python (Part II): Tuning Deep Neural Networks

Machine learning models come with various adjustable parameters. In this series of articles, we will explore how to customize your AI models to fit your specific market using the SciPy library.
preview
Introduction to MQL5 (Part 11): A Beginner's Guide to Working with Built-in Indicators in MQL5 (II)

Introduction to MQL5 (Part 11): A Beginner's Guide to Working with Built-in Indicators in MQL5 (II)

Discover how to develop an Expert Advisor (EA) in MQL5 using multiple indicators like RSI, MA, and Stochastic Oscillator to detect hidden bullish and bearish divergences. Learn to implement effective risk management and automate trades with detailed examples and fully commented source code for educational purposes!
preview
Self Optimizing Expert Advisors in MQL5 (Part 15): Linear System Identification

Self Optimizing Expert Advisors in MQL5 (Part 15): Linear System Identification

Trading strategies may be challenging to improve because we often don’t fully understand what the strategy is doing wrong. In this discussion, we introduce linear system identification, a branch of control theory. Linear feedback systems can learn from data to identify a system’s errors and guide its behavior toward intended outcomes. While these methods may not provide fully interpretable explanations, they are far more valuable than having no control system at all. Let’s explore linear system identification and observe how it may help us as algorithmic traders to maintain control over our trading applications.
preview
MQL5 Trading Tools (Part 8): Enhanced Informational Dashboard with Draggable and Minimizable Features

MQL5 Trading Tools (Part 8): Enhanced Informational Dashboard with Draggable and Minimizable Features

In this article, we develop an enhanced informational dashboard that upgrades the previous part by adding draggable and minimizable features for improved user interaction, while maintaining real-time monitoring of multi-symbol positions and account metrics.
preview
Creating an MQL5-Telegram Integrated Expert Advisor (Part 4): Modularizing Code Functions for Enhanced Reusability

Creating an MQL5-Telegram Integrated Expert Advisor (Part 4): Modularizing Code Functions for Enhanced Reusability

In this article, we refactor the existing code used for sending messages and screenshots from MQL5 to Telegram by organizing it into reusable, modular functions. This will streamline the process, allowing for more efficient execution and easier code management across multiple instances.
preview
Mastering Kagi Charts in MQL5 (Part 2): Implementing Automated Kagi-Based Trading

Mastering Kagi Charts in MQL5 (Part 2): Implementing Automated Kagi-Based Trading

Learn how to build a complete Kagi-based trading Expert Advisor in MQL5, from signal construction to order execution, visual markers, and a three-stage trailing stop. Includes full code, testing results, and a downloadable set file.
preview
Trading with the MQL5 Economic Calendar (Part 9): Elevating News Interaction with a Dynamic Scrollbar and Polished Display

Trading with the MQL5 Economic Calendar (Part 9): Elevating News Interaction with a Dynamic Scrollbar and Polished Display

In this article, we enhance the MQL5 Economic Calendar with a dynamic scrollbar for intuitive news navigation. We ensure seamless event display and efficient updates. We validate the responsive scrollbar and polished dashboard through testing.
preview
Neural networks made easy (Part 18): Association rules

Neural networks made easy (Part 18): Association rules

As a continuation of this series of articles, let's consider another type of problems within unsupervised learning methods: mining association rules. This problem type was first used in retail, namely supermarkets, to analyze market baskets. In this article, we will talk about the applicability of such algorithms in trading.
preview
Mastering Kagi Charts in MQL5 (Part 2): Implementing Automated Kagi-Based Trading

Mastering Kagi Charts in MQL5 (Part 2): Implementing Automated Kagi-Based Trading

Learn how to build a complete Kagi-based trading Expert Advisor in MQL5, from signal construction to order execution, visual markers, and a three-stage trailing stop. Includes full code, testing results, and a downloadable set file.
preview
Multilayer perceptron and backpropagation algorithm (Part 3): Integration with the Strategy Tester - Overview (I).

Multilayer perceptron and backpropagation algorithm (Part 3): Integration with the Strategy Tester - Overview (I).

The multilayer perceptron is an evolution of the simple perceptron which can solve non-linear separable problems. Together with the backpropagation algorithm, this neural network can be effectively trained. In Part 3 of the Multilayer Perceptron and Backpropagation series, we'll see how to integrate this technique into the Strategy Tester. This integration will allow the use of complex data analysis aimed at making better decisions to optimize your trading strategies. In this article, we will discuss the advantages and problems of this technique.
preview
Neural networks made easy (Part 22): Unsupervised learning of recurrent models

Neural networks made easy (Part 22): Unsupervised learning of recurrent models

We continue to study unsupervised learning algorithms. This time I suggest that we discuss the features of autoencoders when applied to recurrent model training.
preview
Neural networks made easy (Part 56): Using nuclear norm to drive research

Neural networks made easy (Part 56): Using nuclear norm to drive research

The study of the environment in reinforcement learning is a pressing problem. We have already looked at some approaches previously. In this article, we will have a look at yet another method based on maximizing the nuclear norm. It allows agents to identify environmental states with a high degree of novelty and diversity.
preview
Neural Networks in Trading: An Ensemble of Agents with Attention Mechanisms (MASAAT)

Neural Networks in Trading: An Ensemble of Agents with Attention Mechanisms (MASAAT)

We introduce the Multi-Agent Self-Adaptive Portfolio Optimization Framework (MASAAT), which combines attention mechanisms and time series analysis. MASAAT generates a set of agents that analyze price series and directional changes, enabling the identification of significant fluctuations in asset prices at different levels of detail.
preview
Data Science and Machine Learning (Part 22): Leveraging Autoencoders Neural Networks for Smarter Trades by Moving from Noise to Signal

Data Science and Machine Learning (Part 22): Leveraging Autoencoders Neural Networks for Smarter Trades by Moving from Noise to Signal

In the fast-paced world of financial markets, separating meaningful signals from the noise is crucial for successful trading. By employing sophisticated neural network architectures, autoencoders excel at uncovering hidden patterns within market data, transforming noisy input into actionable insights. In this article, we explore how autoencoders are revolutionizing trading practices, offering traders a powerful tool to enhance decision-making and gain a competitive edge in today's dynamic markets.
preview
Creating a Trading Administrator Panel in MQL5 (Part III): Enhancing the GUI with Visual Styling (I)

Creating a Trading Administrator Panel in MQL5 (Part III): Enhancing the GUI with Visual Styling (I)

In this article, we will focus on visually styling the graphical user interface (GUI) of our Trading Administrator Panel using MQL5. We’ll explore various techniques and features available in MQL5 that allow for customization and optimization of the interface, ensuring it meets the needs of traders while maintaining an attractive aesthetic.
preview
From Novice to Expert: Animated News Headline Using MQL5 (IX) — Multiple Symbol Management on a single chart for News Trading

From Novice to Expert: Animated News Headline Using MQL5 (IX) — Multiple Symbol Management on a single chart for News Trading

News trading often requires managing multiple positions and symbols within a very short time due to heightened volatility. In today’s discussion, we address the challenges of multi-symbol trading by integrating this feature into our News Headline EA. Join us as we explore how algorithmic trading with MQL5 makes multi-symbol trading more efficient and powerful.
preview
MQL5 Trading Tools (Part 2): Enhancing the Interactive Trade Assistant with Dynamic Visual Feedback

MQL5 Trading Tools (Part 2): Enhancing the Interactive Trade Assistant with Dynamic Visual Feedback

In this article, we upgrade our Trade Assistant Tool by adding drag-and-drop panel functionality and hover effects to make the interface more intuitive and responsive. We refine the tool to validate real-time order setups, ensuring accurate trade configurations relative to market prices. We also backtest these enhancements to confirm their reliability.
preview
Building AI-Powered Trading Systems in MQL5 (Part 6): Introducing Chat Deletion and Search Functionality

Building AI-Powered Trading Systems in MQL5 (Part 6): Introducing Chat Deletion and Search Functionality

In Part 6 of our MQL5 AI trading system series, we advance the ChatGPT-integrated Expert Advisor by introducing chat deletion functionality through interactive delete buttons in the sidebar, small/large history popups, and a new search popup, allowing traders to manage and organize persistent conversations efficiently while maintaining encrypted storage and AI-driven signals from chart data.
preview
Neural networks made easy (Part 54): Using random encoder for efficient research (RE3)

Neural networks made easy (Part 54): Using random encoder for efficient research (RE3)

Whenever we consider reinforcement learning methods, we are faced with the issue of efficiently exploring the environment. Solving this issue often leads to complication of the algorithm and training of additional models. In this article, we will look at an alternative approach to solving this problem.
preview
Automating Black-Scholes Greeks: Advanced Scalping and Microstructure Trading

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.
preview
Quantitative analysis in MQL5: Implementing a promising algorithm

Quantitative analysis in MQL5: Implementing a promising algorithm

We will analyze the question of what quantitative analysis is and how it is used by major players. We will create one of the quantitative analysis algorithms in the MQL5 language.
preview
Neural networks made easy (Part 17): Dimensionality reduction

Neural networks made easy (Part 17): Dimensionality reduction

In this part we continue discussing Artificial Intelligence models. Namely, we study unsupervised learning algorithms. We have already discussed one of the clustering algorithms. In this article, I am sharing a variant of solving problems related to dimensionality reduction.
preview
Neural networks made easy (Part 75): Improving the performance of trajectory prediction models

Neural networks made easy (Part 75): Improving the performance of trajectory prediction models

The models we create are becoming larger and more complex. This increases the costs of not only their training as well as operation. However, the time required to make a decision is often critical. In this regard, let us consider methods for optimizing model performance without loss of quality.
preview
MQL5 Trading Tools (Part 7): Informational Dashboard for Multi-Symbol Position and Account Monitoring

MQL5 Trading Tools (Part 7): Informational Dashboard for Multi-Symbol Position and Account Monitoring

In this article, we develop an informational dashboard in MQL5 for monitoring multi-symbol positions and account metrics like balance, equity, and free margin. We implement a sortable grid with real-time updates, CSV export, and a glowing header effect to enhance usability and visual appeal.
preview
Wrapping ONNX models in classes

Wrapping ONNX models in classes

Object-oriented programming enables creation of a more compact code that is easy to read and modify. Here we will have a look at the example for three ONNX models.
preview
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.
preview
Creating an EA that works automatically (Part 07): Account types (II)

Creating an EA that works automatically (Part 07): Account types (II)

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. The trader should always be aware of what the automatic EA is doing, so that if it "goes off the rails", the trader could remove it from the chart as soon as possible and take control of the situation.
preview
Example of Auto Optimized Take Profits and Indicator Parameters with SMA and EMA

Example of Auto Optimized Take Profits and Indicator Parameters with SMA and EMA

This article presents a sophisticated Expert Advisor for forex trading, combining machine learning with technical analysis. It focuses on trading Apple stock, featuring adaptive optimization, risk management, and multiple strategies. Backtesting shows promising results with high profitability but also significant drawdowns, indicating potential for further refinement.
preview
From Novice to Expert: Collaborative Debugging in MQL5

From Novice to Expert: Collaborative Debugging in MQL5

Problem-solving can establish a concise routine for mastering complex skills, such as programming in MQL5. This approach allows you to concentrate on solving problems while simultaneously developing your skills. The more problems you tackle, the more advanced expertise is transferred to your brain. Personally, I believe that debugging is the most effective way to master programming. Today, we will walk through the code-cleaning process and discuss the best techniques for transforming a messy program into a clean, functional one. Read through this article and uncover valuable insights.
preview
MQL5 Trading Tools (Part 21): Adding Cyberpunk Theme to Regression Graphs

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.
preview
Predicting Renko Bars with CatBoost AI

Predicting Renko Bars with CatBoost AI

How to use Renko bars with AI? Let's look at Renko trading on Forex with forecast accuracy of up to 59.27%. We will explore the benefits of Renko bars for filtering market noise, learn why volume is more important than price patterns, and how to set the optimal Renko block size for EURUSD. This is a step-by-step guide on integrating CatBoost, Python, and MetaTrader 5 to create your own Renko Forex forecasting system. It is ideal for traders looking to go beyond traditional technical analysis.
preview
Price Action Analysis Toolkit Development Part (4): Analytics Forecaster EA

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.
preview
Introduction to MQL5 (Part 20): Introduction to Harmonic Patterns

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.
preview
Experiments with neural networks (Part 7): Passing indicators

Experiments with neural networks (Part 7): Passing indicators

Examples of passing indicators to a perceptron. The article describes general concepts and showcases the simplest ready-made Expert Advisor followed by the results of its optimization and forward test.