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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Developing a multi-currency Expert Advisor (Part 21): Preparing for an important experiment and optimizing the code

Developing a multi-currency Expert Advisor (Part 21): Preparing for an important experiment and optimizing the code

For further progress it would be good to see if we can improve the results by periodically re-running the automatic optimization and generating a new EA. The stumbling block in many debates about the use of parameter optimization is the question of how long the obtained parameters can be used for trading in the future period while maintaining the profitability and drawdown at the specified levels. And is it even possible to do this?
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Using association rules in Forex data analysis

Using association rules in Forex data analysis

How to apply predictive rules of supermarket retail analytics to the real Forex market? How are purchases of cookies, milk and bread related to stock exchange transactions? The article discusses an innovative approach to algorithmic trading based on the use of association rules.
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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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Algorithmic Trading Strategies: AI and Its Road to Golden Pinnacles

Algorithmic Trading Strategies: AI and Its Road to Golden Pinnacles

This article demonstrates an approach to creating trading strategies for gold using machine learning. Considering the proposed approach to the analysis and forecasting of time series from different angles, it is possible to determine its advantages and disadvantages in comparison with other ways of creating trading systems which are based solely on the analysis and forecasting of financial time series.
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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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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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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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MQL5 Wizard Techniques you should know (Part 61): Using Patterns of ADX and CCI with Supervised Learning

MQL5 Wizard Techniques you should know (Part 61): Using Patterns of ADX and CCI with Supervised Learning

The ADX Oscillator and CCI oscillator are trend following and momentum indicators that can be paired when developing an Expert Advisor. We look at how this can be systemized by using all the 3 main training modes of Machine Learning. Wizard Assembled Expert Advisors allow us to evaluate the patterns presented by these two indicators, and we start by looking at how Supervised-Learning can be applied with these Patterns.
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MQL5 Trading Toolkit (Part 4): Developing a History Management EX5 Library

MQL5 Trading Toolkit (Part 4): Developing a History Management EX5 Library

Learn how to retrieve, process, classify, sort, analyze, and manage closed positions, orders, and deal histories using MQL5 by creating an expansive History Management EX5 Library in a detailed step-by-step approach.
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Implementation of the Augmented Dickey Fuller test in MQL5

Implementation of the Augmented Dickey Fuller test in MQL5

In this article we demonstrate the implementation of the Augmented Dickey-Fuller test, and apply it to conduct cointegration tests using the Engle-Granger method.
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From Novice to Expert: Mastering Detailed Trading Reports with Reporting EA

From Novice to Expert: Mastering Detailed Trading Reports with Reporting EA

In this article, we delve into enhancing the details of trading reports and delivering the final document via email in PDF format. This marks a progression from our previous work, as we continue exploring how to harness the power of MQL5 and Python to generate and schedule trading reports in the most convenient and professional formats. Join us in this discussion to learn more about optimizing trading report generation within the MQL5 ecosystem.
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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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Price Action Analysis Toolkit Development (Part 34): Turning Raw Market Data into Predictive Models Using an Advanced Ingestion Pipeline

Price Action Analysis Toolkit Development (Part 34): Turning Raw Market Data into Predictive Models Using an Advanced Ingestion Pipeline

Have you ever missed a sudden market spike or been caught off‑guard when one occurred? The best way to anticipate live events is to learn from historical patterns. Intending to train an ML model, this article begins by showing you how to create a script in MetaTrader 5 that ingests historical data and sends it to Python for storage—laying the foundation for your spike‑detection system. Read on to see each step in action.
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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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Implementing Practical Modules from Other Languages in MQL5 (Part 02): Building the REQUESTS Library, Inspired by Python

Implementing Practical Modules from Other Languages in MQL5 (Part 02): Building the REQUESTS Library, Inspired by Python

In this article, we implement a module similar to requests offered in Python to make it easier to send and receive web requests in MetaTrader 5 using MQL5.
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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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Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (IV): Trade Management Panel class

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (IV): Trade Management Panel class

This discussion covers the updated TradeManagementPanel in our New_Admin_Panel EA. The update enhances the panel by using built-in classes to offer a user-friendly trade management interface. It includes trading buttons for opening positions and controls for managing existing trades and pending orders. A key feature is the integrated risk management that allows setting stop loss and take profit values directly in the interface. This update improves code organization for large programs and simplifies access to order management tools, which are often complex in the terminal.
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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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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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Building AI-Powered Trading Systems in MQL5 (Part 8): UI Polish with Animations, Timing Metrics, and Response Management Tools

Building AI-Powered Trading Systems in MQL5 (Part 8): UI Polish with Animations, Timing Metrics, and Response Management Tools

In this article, we enhance the AI-powered trading system in MQL5 with user interface improvements, including loading animations for request preparation and thinking phases, as well as timing metrics displayed in responses for better feedback. We add response management tools like regenerate buttons to re-query the AI and export options to save the last response to a file, streamlining interaction.
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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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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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Python-MetaTrader 5 Strategy Tester (Part 04): Tester 101

Python-MetaTrader 5 Strategy Tester (Part 04): Tester 101

In this fascinating article, we build our very first trading robot in the simulator and run a strategy testing action that resembles how the MetaTrader 5 strategy tester works, then compare the outcome produced in a custom simulation against our favorite terminal.
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Angular Analysis of Price Movements: A Hybrid Model for Predicting Financial Markets

Angular Analysis of Price Movements: A Hybrid Model for Predicting Financial Markets

What is angular analysis of financial markets? How to use price action angles and machine learning to make accurate forecasts with 67% accuracy? How to combine a regression and classification model with angular features and obtain a working algorithm? What does Gann have to do with it? Why are price movement angles a good indicator for machine learning?
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Building A Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (II)

Building A Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (II)

The number of strategies that can be integrated into an Expert Advisor is virtually limitless. However, each additional strategy increases the complexity of the algorithm. By incorporating multiple strategies, an Expert Advisor can better adapt to varying market conditions, potentially enhancing its profitability. Today, we will explore how to implement MQL5 for one of the prominent strategies developed by Richard Donchian, as we continue to enhance the functionality of our Trend Constraint Expert.
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Exploring Machine Learning in Unidirectional Trend Trading Using Gold as a Case Study

Exploring Machine Learning in Unidirectional Trend Trading Using Gold as a Case Study

This article discusses an approach to trading only in the chosen direction (buy or sell). For this purpose, the technique of causal inference and machine learning are used.
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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 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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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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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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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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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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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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MetaTrader 5 Machine Learning Blueprint (Part 6): Engineering a Production-Grade Caching System

MetaTrader 5 Machine Learning Blueprint (Part 6): Engineering a Production-Grade Caching System

Tired of watching progress bars instead of testing trading strategies? Traditional caching fails financial ML, leaving you with lost computations and frustrating restarts. We've engineered a sophisticated caching architecture that understands the unique challenges of financial data—temporal dependencies, complex data structures, and the constant threat of look-ahead bias. Our three-layer system delivers dramatic speed improvements while automatically invalidating stale results and preventing costly data leaks. Stop waiting for computations and start iterating at the pace the markets demand.
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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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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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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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MetaTrader tick info access from MQL5 services to Python application using sockets

MetaTrader tick info access from MQL5 services to Python application using sockets

Sometimes everything is not programmable in the MQL5 language. And even if it is possible to convert existing advanced libraries in MQL5, it would be time-consuming. This article tries to show that we can bypass Windows OS dependency by transporting tick information such as bid, ask and time with MetaTrader services to a Python application using sockets.
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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.