Articles on MetaTrader 5 integration using MQL5

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Traders meet interesting challenges which often require an innovative approach. This category features articles that offer the most unexpected solutions for evaluating, analyzing and processing price data and trading results. The articles describe various integration solutions, including connection of databases and ICQ, use of OpenCL and social networks, use of Delphi and C#.

Read on to learn how to use specialized mathematical and neural packages, and much more. Become an author and share unique ideas with the MQL5.community members.

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Creating a Trading Administrator Panel in MQL5 (Part VIII): Analytics Panel

Creating a Trading Administrator Panel in MQL5 (Part VIII): Analytics Panel

Today, we delve into incorporating useful trading metrics within a specialized window integrated into the Admin Panel EA. This discussion focuses on the implementation of MQL5 to develop an Analytics Panel and highlights the value of the data it provides to trading administrators. The impact is largely educational, as valuable lessons are drawn from the development process, benefiting both upcoming and experienced developers. This feature demonstrates the limitless opportunities this development series offers in equipping trade managers with advanced software tools. Additionally, we'll explore the implementation of the PieChart and ChartCanvas classes as part of the continued expansion of the Trading Administrator panel’s capabilities.
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Building AI-Powered Trading Systems in MQL5 (Part 5): Adding a Collapsible Sidebar with Chat Popups

Building AI-Powered Trading Systems in MQL5 (Part 5): Adding a Collapsible Sidebar with Chat Popups

In Part 5 of our MQL5 AI trading system series, we enhance the ChatGPT-integrated Expert Advisor by introducing a collapsible sidebar, improving navigation with small and large history popups for seamless chat selection, while maintaining multiline input handling, persistent encrypted chat storage, and AI-driven trade signal generation from chart data.
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Population optimization algorithms: Binary Genetic Algorithm (BGA). Part II

Population optimization algorithms: Binary Genetic Algorithm (BGA). Part II

In this article, we will look at the binary genetic algorithm (BGA), which models the natural processes that occur in the genetic material of living things in nature.
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Black Hole Algorithm (BHA)

Black Hole Algorithm (BHA)

The Black Hole Algorithm (BHA) uses the principles of black hole gravity to optimize solutions. In this article, we will look at how BHA attracts the best solutions while avoiding local extremes, and why this algorithm has become a powerful tool for solving complex problems. Learn how simple ideas can lead to impressive results in the world of optimization.
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Integrating Computer Vision into Trading in MQL5 (Part 1): Creating Basic Functions

Integrating Computer Vision into Trading in MQL5 (Part 1): Creating Basic Functions

The EURUSD forecasting system with the use of computer vision and deep learning. Learn how convolutional neural networks can recognize complex price patterns in the foreign exchange market and predict exchange rate movements with up to 54% accuracy. The article shares the methodology for creating an algorithm that uses artificial intelligence technologies for visual analysis of charts instead of traditional technical indicators. The author demonstrates the process of transforming price data into "images", their processing by a neural network, and a unique opportunity to peer into the "consciousness" of AI through activation maps and attention heatmaps. Practical Python code using the MetaTrader 5 library allows readers to reproduce the system and apply it in their own trading.
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Category Theory in MQL5 (Part 2)

Category Theory in MQL5 (Part 2)

Category Theory is a diverse and expanding branch of Mathematics which as of yet is relatively uncovered in the MQL5 community. These series of articles look to introduce and examine some of its concepts with the overall goal of establishing an open library that attracts comments and discussion while hopefully furthering the use of this remarkable field in Traders' strategy development.
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Atomic Orbital Search (AOS) algorithm: Modification

Atomic Orbital Search (AOS) algorithm: Modification

In the second part of the article, we will continue developing a modified version of the AOS (Atomic Orbital Search) algorithm focusing on specific operators to improve its efficiency and adaptability. After analyzing the fundamentals and mechanics of the algorithm, we will discuss ideas for improving its performance and the ability to analyze complex solution spaces, proposing new approaches to extend its functionality as an optimization tool.
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Time series clustering in causal inference

Time series clustering in causal inference

Clustering algorithms in machine learning are important unsupervised learning algorithms that can divide the original data into groups with similar observations. By using these groups, you can analyze the market for a specific cluster, search for the most stable clusters using new data, and make causal inferences. The article proposes an original method for time series clustering in Python.
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MQL5 Wizard Techniques you should know (Part 64): Using Patterns of DeMarker and Envelope Channels with the White-Noise Kernel

MQL5 Wizard Techniques you should know (Part 64): Using Patterns of DeMarker and Envelope Channels with the White-Noise Kernel

The DeMarker Oscillator and the Envelopes' indicator are momentum and support/ resistance tools that can be paired when developing an Expert Advisor. We continue from our last article that introduced these pair of indicators by adding machine learning to the mix. We are using a recurrent neural network that uses the white-noise kernel to process vectorized signals from these two indicators. This is done in a custom signal class file that works with the MQL5 wizard to assemble an Expert Advisor.
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Population optimization algorithms: Bat algorithm (BA)

Population optimization algorithms: Bat algorithm (BA)

In this article, I will consider the Bat Algorithm (BA), which shows good convergence on smooth functions.
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Codex Pipelines: From Python to MQL5 for Indicator Selection — A Multi-Quarter Analysis of the FXI ETF

Codex Pipelines: From Python to MQL5 for Indicator Selection — A Multi-Quarter Analysis of the FXI ETF

We continue our look at how MetaTrader can be used outside its forex trading ‘comfort-zone’ by looking at another tradable asset in the form of the FXI ETF. Unlike in the last article where we tried to do ‘too-much’ by delving into not just indicator selection, but also considering indicator pattern combinations, for this article we will swim slightly upstream by focusing more on indicator selection. Our end product for this is intended as a form of pipeline that can help recommend indicators for various assets, provided we have a reasonable amount of their price history.
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Moving to MQL5 Algo Forge (Part 3): Using External Repositories in Your Own Projects

Moving to MQL5 Algo Forge (Part 3): Using External Repositories in Your Own Projects

Let's explore how you can start integrating external code from any repository in the MQL5 Algo Forge storage into your own project. In this article, we finally turn to this promising, yet more complex, task: how to practically connect and use libraries from third-party repositories within MQL5 Algo Forge.
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Creating a Trading Administrator Panel in MQL5 (Part VI):Trade Management Panel (II)

Creating a Trading Administrator Panel in MQL5 (Part VI):Trade Management Panel (II)

In this article, we enhance the Trade Management Panel of our multi-functional Admin Panel. We introduce a powerful helper function that simplifies the code, improving readability, maintainability, and efficiency. We will also demonstrate how to seamlessly integrate additional buttons and enhance the interface to handle a wider range of trading tasks. Whether managing positions, adjusting orders, or simplifying user interactions, this guide will help you develop a robust, user-friendly Trade Management Panel.
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Developing an MQTT client for MetaTrader 5: a TDD approach — Part 3

Developing an MQTT client for MetaTrader 5: a TDD approach — Part 3

This article is the third part of a series describing our development steps of a native MQL5 client for the MQTT protocol. In this part, we describe in detail how we are using Test-Driven Development to implement the Operational Behavior part of the CONNECT/CONNACK packet exchange. At the end of this step, our client MUST be able to behave appropriately when dealing with any of the possible server outcomes from a connection attempt.
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Websockets for MetaTrader 5: Asynchronous client connections with the Windows API

Websockets for MetaTrader 5: Asynchronous client connections with the Windows API

This article details the development of a custom dynamically linked library designed to facilitate asynchronous websocket client connections for MetaTrader programs.
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Developing a Multi-Currency Advisor (Part 27): Component for Displaying Multi-Line Text

Developing a Multi-Currency Advisor (Part 27): Component for Displaying Multi-Line Text

If there is a need to display text on a chart, we can use the Comment() function. But its capabilities are quite limited. Therefore, in this article, we will create our own component - a full-screen dialog window capable of displaying multi-line text with flexible font settings and scrolling support.
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Python-MetaTrader 5 Strategy Tester (Part 03): MetaTrader 5-Like Trading Operations — Handling and Managing

Python-MetaTrader 5 Strategy Tester (Part 03): MetaTrader 5-Like Trading Operations — Handling and Managing

In this article we introduce Python-MetaTrader5-like ways of handling trading operations such as opening, closing, and modifying orders in the simulator. To ensure the simulation behaves like MetaTrader 5, a strict validation layer for trade requests is implemented, taking into account symbol trading parameters and typical brokerage restrictions.
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Brain Storm Optimization algorithm (Part II): Multimodality

Brain Storm Optimization algorithm (Part II): Multimodality

In the second part of the article, we will move on to the practical implementation of the BSO algorithm, conduct tests on test functions and compare the efficiency of BSO with other optimization methods.
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Multi-Threaded Trading Robot with Machine Learning: From Concept to Implementation

Multi-Threaded Trading Robot with Machine Learning: From Concept to Implementation

The article presents a step-by-step development of a multi-threaded trading robot with machine learning in Python and MetaTrader 5. The system architecture is considered – from data collection and creation of technical indicators to training XGBoost models with portfolio risk management. The implementation of data augmentation, feature clustering via Gaussian Mixture Models, and flow coordination for parallel trading of multiple currency pairs is described in detail.
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Creating an MQL5-Telegram Integrated Expert Advisor (Part 7): Command Analysis for Indicator Automation on Charts

Creating an MQL5-Telegram Integrated Expert Advisor (Part 7): Command Analysis for Indicator Automation on Charts

In this article, we explore how to integrate Telegram commands with MQL5 to automate the addition of indicators on trading charts. We cover the process of parsing user commands, executing them in MQL5, and testing the system to ensure smooth indicator-based trading
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Codex Pipelines, from Python to MQL5, for Indicator Selection: A Multi-Quarter Analysis of the XLF ETF with Machine Learning

Codex Pipelines, from Python to MQL5, for Indicator Selection: A Multi-Quarter Analysis of the XLF ETF with Machine Learning

We continue our look at how the selection of indicators can be pipelined when facing a ‘none-typical’ MetaTrader asset. MetaTrader 5 is primarily used to trade forex, and that is good given the liquidity on offer, however the case for trading outside of this ‘comfort-zone’, is growing bolder with not just the overnight rise of platforms like Robinhood, but also the relentless pursuit of an edge for most traders. We consider the XLF ETF for this article and also cap our revamped pipeline with a simple MLP.
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Python-MetaTrader 5 Strategy Tester (Part 05): Multi-Symbols and Timeframes Strategy Tester

Python-MetaTrader 5 Strategy Tester (Part 05): Multi-Symbols and Timeframes Strategy Tester

This article presents a MetaTrader 5–compatible backtesting workflow that scales across symbols and timeframes. We use HistoryManager to parallelize data collection, synchronize bars and ticks from all timeframes, and run symbol‑isolated OnTick handlers in threads. You will learn how modelling modes affect speed/accuracy, when to rely on terminal data, how to reduce I/O with event‑driven updates, and how to assemble a complete multicurrency trading robot.
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Price Action Analysis Toolkit Development (Part 8): Metrics Board

Price Action Analysis Toolkit Development (Part 8): Metrics Board

As one of the most powerful Price Action analysis toolkits, the Metrics Board is designed to streamline market analysis by instantly providing essential market metrics with just a click of a button. Each button serves a specific function, whether it’s analyzing high/low trends, volume, or other key indicators. This tool delivers accurate, real-time data when you need it most. Let’s dive deeper into its features in this article.
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Across Neighbourhood Search (ANS)

Across Neighbourhood Search (ANS)

The article reveals the potential of the ANS algorithm as an important step in the development of flexible and intelligent optimization methods that can take into account the specifics of the problem and the dynamics of the environment in the search space.
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Artificial Atom Algorithm (A3)

Artificial Atom Algorithm (A3)

The article describes implementation of the A3 algorithm - a metaheuristic optimization method inspired by chemical processes - in MQL5. Only two adjustable parameters, compactness and a small population, ensure high operating speed with sufficient quality of solutions.
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Category Theory in MQL5 (Part 7): Multi, Relative and Indexed Domains

Category Theory in MQL5 (Part 7): Multi, Relative and Indexed Domains

Category Theory is a diverse and expanding branch of Mathematics which is only recently getting some coverage in the MQL5 community. These series of articles look to explore and examine some of its concepts & axioms with the overall goal of establishing an open library that provides insight while also hopefully furthering the use of this remarkable field in Traders' strategy development.
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Developing an MQL5 Reinforcement Learning agent with RestAPI integration (Part 1): How to use RestAPIs in MQL5

Developing an MQL5 Reinforcement Learning agent with RestAPI integration (Part 1): How to use RestAPIs in MQL5

In this article we will talk about the importance of APIs (Application Programming Interface) for interaction between different applications and software systems. We will see the role of APIs in simplifying interactions between applications, allowing them to efficiently share data and functionality.
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Market Reactions and Trading Strategies in Response to Dividend Announcements: Evaluating the Efficient Market Hypothesis in Stock Trading

Market Reactions and Trading Strategies in Response to Dividend Announcements: Evaluating the Efficient Market Hypothesis in Stock Trading

In this article, we will analyse the impact of dividend announcements on stock market returns and see how investors can earn more returns than those offered by the market when they expect a company to announce dividends. In doing so, we will also check the validity of the Efficient Market Hypothesis in the context of the Indian Stock Market.
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MQL5 Wizard Techniques you should know (Part 57): Supervised Learning with Moving Average and Stochastic Oscillator

MQL5 Wizard Techniques you should know (Part 57): Supervised Learning with Moving Average and Stochastic Oscillator

Moving Average and Stochastic Oscillator are very common indicators that some traders may not use a lot because of their lagging nature. In a 3-part ‘miniseries' that considers the 3 main forms of machine learning, we look to see if this bias against these indicators is justified, or they might be holding an edge. We do our examination in wizard assembled Expert Advisors.
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Adaptive Malaysian Engulfing Indicator (Part 2): Optimized Retest Bar Range

Adaptive Malaysian Engulfing Indicator (Part 2): Optimized Retest Bar Range

The article adds a self-adaptive layer to the Malaysian Engulfing indicator by optimizing the retest bar range with a constrained brute-force search scored by MFE and MAE. It details the data model, helper routines, and an MQL5 implementation that gathers historical setups, computes excursions, and selects the best parameter. Readers learn how to remove manual tuning and run the indicator with context-appropriate settings across symbols and timeframes.
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Creating a Trading Administrator Panel in MQL5 (Part II): Enhancing Responsiveness and Quick Messaging

Creating a Trading Administrator Panel in MQL5 (Part II): Enhancing Responsiveness and Quick Messaging

In this article, we will enhance the responsiveness of the Admin Panel that we previously created. Additionally, we will explore the significance of quick messaging in the context of trading signals.
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From Novice to Expert: Animated News Headline Using MQL5 (X)—Multiple Symbol Chart View for News Trading

From Novice to Expert: Animated News Headline Using MQL5 (X)—Multiple Symbol Chart View for News Trading

Today we will develop a multi-chart view system using chart objects. The goal is to enhance news trading by applying MQL5 algorithms that help reduce trader reaction time during periods of high volatility, such as major news releases. In this case, we provide traders with an integrated way to monitor multiple major symbols within a single all-in-one news trading tool. Our work is continuously advancing with the News Headline EA, which now features a growing set of functions that add real value both for traders using fully automated systems and for those who prefer manual trading assisted by algorithms. Explore more knowledge, insights, and practical ideas by clicking through and joining this discussion.
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From Novice to Expert: Adaptive Risk Management for Liquidity Strategies

From Novice to Expert: Adaptive Risk Management for Liquidity Strategies

In this article, we explore practical and robust risk management techniques specifically tailored for liquidity-based trading. You will learn how to protect positions during retests, handle false breakouts with confidence, and identify signs of potential level manipulation. By the end, you will have built an adaptive Expert Advisor capable of managing zone flips and executing strategic pending orders with integrated risk control.
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Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part III)

Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part III)

This part of the article series is dedicated to integrating WhatsApp with MetaTrader 5 for notifications. We have included a flow chart to simplify understanding and will discuss the importance of security measures in integration. The primary purpose of indicators is to simplify analysis through automation, and they should include notification methods for alerting users when specific conditions are met. Discover more in this article.
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Developing a multi-currency Expert Advisor (Part 8): Load testing and handling a new bar

Developing a multi-currency Expert Advisor (Part 8): Load testing and handling a new bar

As we progressed, we used more and more simultaneously running instances of trading strategies in one EA. Let's try to figure out how many instances we can get to before we hit resource limitations.
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Forex arbitrage trading: Analyzing synthetic currencies movements and their mean reversion

Forex arbitrage trading: Analyzing synthetic currencies movements and their mean reversion

In this article, we will examine the movements of synthetic currencies using Python and MQL5 and explore how feasible Forex arbitrage is today. We will also consider ready-made Python code for analyzing synthetic currencies and share more details on what synthetic currencies are in Forex.
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Quantitative approach to risk management: Applying VaR model to optimize multi-currency portfolio using Python and MetaTrader 5

Quantitative approach to risk management: Applying VaR model to optimize multi-currency portfolio using Python and MetaTrader 5

This article explores the potential of the Value at Risk (VaR) model for multi-currency portfolio optimization. Using the power of Python and the functionality of MetaTrader 5, we demonstrate how to implement VaR analysis for efficient capital allocation and position management. From theoretical foundations to practical implementation, the article covers all aspects of applying one of the most robust risk calculation systems – VaR – in algorithmic trading.
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Custom Debugging and Profiling Tools for MQL5 Development (Part I): Advanced Logging

Custom Debugging and Profiling Tools for MQL5 Development (Part I): Advanced Logging

Learn how to implement a powerful custom logging framework for MQL5 that goes beyond simple Print() statements by supporting severity levels, multiple output handlers, and automated file rotation—all configurable on‐the‐fly. Integrate the singleton CLogger with ConsoleLogHandler and FileLogHandler to capture contextual, timestamped logs in both the Experts tab and persistent files. Streamline debugging and performance tracing in your Expert Advisors with clear, customizable log formats and centralized control.
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Market Simulation (Part 20): First steps with SQL (III)

Market Simulation (Part 20): First steps with SQL (III)

Although we can perform operations on a database containing about 10 records, the material is absorbed much better when we work with a file that contains more than 15 thousand records. That is, if we tried to create such a database manually, this task would be enormous. However, it is difficult to find such a database, even for educational purposes, that is available for download. But in reality, we don’t need to resort to that — we can use MetaTrader 5 to create a database for ourselves. In today's article, we will look at how to do this.
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Fibonacci in Forex (Part I): Examining the Price-Time Relationship

Fibonacci in Forex (Part I): Examining the Price-Time Relationship

How does the market observe Fibonacci-based relationships? This sequence, where each subsequent number is equal to the sum of the two previous ones (1, 1, 2, 3, 5, 8, 13, 21...), not only describes the growth of the rabbit population. We will consider the Pythagorean hypothesis that everything in the world is subject to certain relationships of numbers...