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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Population optimization algorithms: Gravitational Search Algorithm (GSA)

Population optimization algorithms: Gravitational Search Algorithm (GSA)

GSA is a population optimization algorithm inspired by inanimate nature. Thanks to Newton's law of gravity implemented in the algorithm, the high reliability of modeling the interaction of physical bodies allows us to observe the enchanting dance of planetary systems and galactic clusters. In this article, I will consider one of the most interesting and original optimization algorithms. The simulator of the space objects movement is provided as well.
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Continuous walk-forward optimization (Part 8): Program improvements and fixes

Continuous walk-forward optimization (Part 8): Program improvements and fixes

The program has been modified based on comments and requests from users and readers of this article series. This article contains a new version of the auto optimizer. This version implements requested features and provides other improvements, which I found when working with the program.
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Price Action Analysis Toolkit Development (Part 35): Training and Deploying Predictive Models

Price Action Analysis Toolkit Development (Part 35): Training and Deploying Predictive Models

Historical data is far from “trash”—it’s the foundation of any robust market analysis. In this article, we’ll take you step‑by‑step from collecting that history to using it to train a predictive model, and finally deploying that model for live price forecasts. Read on to learn how!
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Price Action Analysis Toolkit Development (Part 31): Python Candlestick Recognition Engine (I) — Manual Detection

Price Action Analysis Toolkit Development (Part 31): Python Candlestick Recognition Engine (I) — Manual Detection

Candlestick patterns are fundamental to price-action trading, offering valuable insights into potential market reversals or continuations. Envision a reliable tool that continuously monitors each new price bar, identifies key formations such as engulfing patterns, hammers, dojis, and stars, and promptly notifies you when a significant trading setup is detected. This is precisely the functionality we have developed. Whether you are new to trading or an experienced professional, this system provides real-time alerts for candlestick patterns, enabling you to focus on executing trades with greater confidence and efficiency. Continue reading to learn how it operates and how it can enhance your trading strategy.
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Building AI-Powered Trading Systems in MQL5 (Part 4): Overcoming Multiline Input, Ensuring Chat Persistence, and Generating Signals

Building AI-Powered Trading Systems in MQL5 (Part 4): Overcoming Multiline Input, Ensuring Chat Persistence, and Generating Signals

In this article, we enhance the ChatGPT-integrated program in MQL5 overcoming multiline input limitations with improved text rendering, introducing a sidebar for navigating persistent chat storage using AES256 encryption and ZIP compression, and generating initial trade signals through chart data integration.
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Creating a Trading Administrator Panel in MQL5 (Part I): Building a Messaging Interface

Creating a Trading Administrator Panel in MQL5 (Part I): Building a Messaging Interface

This article discusses the creation of a Messaging Interface for MetaTrader 5, aimed at System Administrators, to facilitate communication with other traders directly within the platform. Recent integrations of social platforms with MQL5 allow for quick signal broadcasting across different channels. Imagine being able to validate sent signals with just a click—either "YES" or "NO." Read on to learn more.
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Algorithmic Trading Without the Routine: Quick Trade Analysis in MetaTrader 5 with SQLite

Algorithmic Trading Without the Routine: Quick Trade Analysis in MetaTrader 5 with SQLite

The article presents a minimal working set for maintaining a trading journal in MQL5 using SQLite: a table structure for trades, signals, and events, indices, prepared statements and trades, as well as standard analytical SQL queries. Integration with the statistics dashboard in MetaTrader 5 and working with the database via MetaEditor are demonstrated. The approach allows automating the journal, accelerating calculations, and performing analysis without complicating the EA code.
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Price Action Analysis Toolkit Development (Part 31): Python Candlestick Recognition Engine (I) — Manual Detection

Price Action Analysis Toolkit Development (Part 31): Python Candlestick Recognition Engine (I) — Manual Detection

Candlestick patterns are fundamental to price-action trading, offering valuable insights into potential market reversals or continuations. Envision a reliable tool that continuously monitors each new price bar, identifies key formations such as engulfing patterns, hammers, dojis, and stars, and promptly notifies you when a significant trading setup is detected. This is precisely the functionality we have developed. Whether you are new to trading or an experienced professional, this system provides real-time alerts for candlestick patterns, enabling you to focus on executing trades with greater confidence and efficiency. Continue reading to learn how it operates and how it can enhance your trading strategy.
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Creating a Trading Administrator Panel in MQL5 (Part I): Building a Messaging Interface

Creating a Trading Administrator Panel in MQL5 (Part I): Building a Messaging Interface

This article discusses the creation of a Messaging Interface for MetaTrader 5, aimed at System Administrators, to facilitate communication with other traders directly within the platform. Recent integrations of social platforms with MQL5 allow for quick signal broadcasting across different channels. Imagine being able to validate sent signals with just a click—either "YES" or "NO." Read on to learn more.
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Improve Your Trading Charts With Interactive GUI's in MQL5 (Part II): Movable GUI (II)

Improve Your Trading Charts With Interactive GUI's in MQL5 (Part II): Movable GUI (II)

Unlock the potential of dynamic data representation in your trading strategies and utilities with our in-depth guide to creating movable GUIs in MQL5. Delve into the fundamental principles of object-oriented programming and discover how to design and implement single or multiple movable GUIs on the same chart with ease and efficiency.
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Introduction to MQL5 (Part 29): Mastering API and WebRequest Function in MQL5 (III)

Introduction to MQL5 (Part 29): Mastering API and WebRequest Function in MQL5 (III)

In this article, we continue mastering API and WebRequest in MQL5 by retrieving candlestick data from an external source. We focus on splitting the server response, cleaning the data, and extracting essential elements such as opening time and OHLC values for multiple daily candles, preparing the data for further analysis.
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Integrating Hidden Markov Models in MetaTrader 5

Integrating Hidden Markov Models in MetaTrader 5

In this article we demonstrate how Hidden Markov Models trained using Python can be integrated into MetaTrader 5 applications. Hidden Markov Models are a powerful statistical tool used for modeling time series data, where the system being modeled is characterized by unobservable (hidden) states. A fundamental premise of HMMs is that the probability of being in a given state at a particular time depends on the process's state at the previous time slot.
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Building AI-Powered Trading Systems in MQL5 (Part 3): Upgrading to a Scrollable Single Chat-Oriented UI

Building AI-Powered Trading Systems in MQL5 (Part 3): Upgrading to a Scrollable Single Chat-Oriented UI

In this article, we upgrade the ChatGPT-integrated program in MQL5 to a scrollable single chat-oriented UI, enhancing conversation history display with timestamps and dynamic scrolling. The system builds on JSON parsing to manage multi-turn messages, supporting customizable scrollbar modes and hover effects for improved user interaction.
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Modified Grid-Hedge EA in MQL5 (Part III): Optimizing Simple Hedge Strategy (I)

Modified Grid-Hedge EA in MQL5 (Part III): Optimizing Simple Hedge Strategy (I)

In this third part, we revisit the Simple Hedge and Simple Grid Expert Advisors (EAs) developed earlier. Our focus shifts to refining the Simple Hedge EA through mathematical analysis and a brute force approach, aiming for optimal strategy usage. This article delves deep into the mathematical optimization of the strategy, setting the stage for future exploration of coding-based optimization in later installments.
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Integrating MQL5 with data processing packages (Part 5): Adaptive Learning and Flexibility

Integrating MQL5 with data processing packages (Part 5): Adaptive Learning and Flexibility

This part focuses on building a flexible, adaptive trading model trained on historical XAUUSD data, preparing it for ONNX export and potential integration into live trading systems.
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Developing a multi-currency Expert Advisor (Part 22): Starting the transition to hot swapping of settings

Developing a multi-currency Expert Advisor (Part 22): Starting the transition to hot swapping of settings

If we are going to automate periodic optimization, we need to think about auto updates of the settings of the EAs already running on the trading account. This should also allow us to run the EA in the strategy tester and change its settings within a single run.
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Graph Theory: Heuristic Search Algorithm (A-Star) Applied in Trading

Graph Theory: Heuristic Search Algorithm (A-Star) Applied in Trading

The article applies the A* heuristic to market structure by modeling validated swing highs and lows as graph nodes and weighting edges with ATR‑normalized distance, spread, and noise penalties. The engine searches the most efficient route to infer trade direction and targets, then filters signals by directional ratio, total path cost, and opposing swings. It anchors TP to the final node and SL to prior structure, with on‑chart visualization and configurable inputs.
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Advanced Memory Management and Optimization Techniques in MQL5

Advanced Memory Management and Optimization Techniques in MQL5

Discover practical techniques to optimize memory usage in MQL5 trading systems. Learn to build efficient, stable, and fast-performing Expert Advisors and indicators. We’ll explore how memory really works in MQL5, the common traps that slow your systems down or cause them to fail, and — most importantly — how to fix them.
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Artificial Algae Algorithm (AAA)

Artificial Algae Algorithm (AAA)

The article considers the Artificial Algae Algorithm (AAA) based on biological processes characteristic of microalgae. The algorithm includes spiral motion, evolutionary process and adaptation, which allows it to solve optimization problems. The article provides an in-depth analysis of the working principles of AAA and its potential in mathematical modeling, highlighting the connection between nature and algorithmic solutions.
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Developing a trading Expert Advisor from scratch (Part 17): Accessing data on the web (III)

Developing a trading Expert Advisor from scratch (Part 17): Accessing data on the web (III)

In this article we continue considering how to obtain data from the web and to use it in an Expert Advisor. This time we will proceed to developing an alternative system.
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Building a Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (III)

Building a Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (III)

Welcome to the third installment of our trend series! Today, we’ll delve into the use of divergence as a strategy for identifying optimal entry points within the prevailing daily trend. We’ll also introduce a custom profit-locking mechanism, similar to a trailing stop-loss, but with unique enhancements. In addition, we’ll upgrade the Trend Constraint Expert to a more advanced version, incorporating a new trade execution condition to complement the existing ones. As we move forward, we’ll continue to explore the practical application of MQL5 in algorithmic development, providing you with more in-depth insights and actionable techniques.
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Building A Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (I)

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

Today, we will explore the possibilities of incorporating multiple strategies into an Expert Advisor (EA) using MQL5. Expert Advisors provide broader capabilities than just indicators and scripts, allowing for more sophisticated trading approaches that can adapt to changing market conditions. Find, more in this article discussion.
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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.
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ALGLIB library optimization methods (Part II)

ALGLIB library optimization methods (Part II)

In this article, we will continue to study the remaining optimization methods from the ALGLIB library, paying special attention to their testing on complex multidimensional functions. This will allow us not only to evaluate the efficiency of each algorithm, but also to identify their strengths and weaknesses in different conditions.
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Creating an MQL5-Telegram Integrated Expert Advisor (Part 6): Adding Responsive Inline Buttons

Creating an MQL5-Telegram Integrated Expert Advisor (Part 6): Adding Responsive Inline Buttons

In this article, we integrate interactive inline buttons into an MQL5 Expert Advisor, allowing real-time control via Telegram. Each button press triggers specific actions and sends responses back to the user. We also modularize functions for handling Telegram messages and callback queries efficiently.
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Portfolio Risk Model using Kelly Criterion and Monte Carlo Simulation

Portfolio Risk Model using Kelly Criterion and Monte Carlo Simulation

For decades, traders have been using the Kelly Criterion formula to determine the optimal proportion of capital to allocate to an investment or bet to maximize long-term growth while minimizing the risk of ruin. However, blindly following Kelly Criterion using the result of a single backtest is often dangerous for individual traders, as in live trading, trading edge diminishes over time, and past performance is no predictor of future result. In this article, I will present a realistic approach to applying the Kelly Criterion for one or more EA's risk allocation in MetaTrader 5, incorporating Monte Carlo simulation results from Python.
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Developing a robot in Python and MQL5 (Part 2): Model selection, creation and training, Python custom tester

Developing a robot in Python and MQL5 (Part 2): Model selection, creation and training, Python custom tester

We continue the series of articles on developing a trading robot in Python and MQL5. Today we will solve the problem of selecting and training a model, testing it, implementing cross-validation, grid search, as well as the problem of model ensemble.
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Black-Scholes Greeks: Gamma and Delta

Black-Scholes Greeks: Gamma and Delta

Gamma and Delta measure how an option’s value reacts to changes in the underlying asset’s price. Delta represents the rate of change of the option’s price relative to the underlying, while Gamma measures how Delta itself changes as price moves. Together, they describe an option’s directional sensitivity and convexity—critical for dynamic hedging and volatility-based trading strategies.
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From Novice to Expert: Predictive Price Pathways

From Novice to Expert: Predictive Price Pathways

Fibonacci levels provide a practical framework that markets often respect, highlighting price zones where reactions are more likely. In this article, we build an expert advisor that applies Fibonacci retracement logic to anticipate likely future moves and trade retracements with pending orders. Explore the full workflow—from swing detection to level plotting, risk controls, and execution.
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Population optimization algorithms: Invasive Weed Optimization (IWO)

Population optimization algorithms: Invasive Weed Optimization (IWO)

The amazing ability of weeds to survive in a wide variety of conditions has become the idea for a powerful optimization algorithm. IWO is one of the best algorithms among the previously reviewed ones.
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Building AI-Powered Trading Systems in MQL5 (Part 9): Creating an AI Signal Dispatcher

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
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Building AI-Powered Trading Systems in MQL5 (Part 9): Creating an AI Signal Dispatcher

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
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Population optimization algorithms: Monkey algorithm (MA)

Population optimization algorithms: Monkey algorithm (MA)

In this article, I will consider the Monkey Algorithm (MA) optimization algorithm. The ability of these animals to overcome difficult obstacles and get to the most inaccessible tree tops formed the basis of the idea of the MA algorithm.
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Price Action Analysis Toolkit Development (Part 12): External Flow (III) TrendMap

Price Action Analysis Toolkit Development (Part 12): External Flow (III) TrendMap

The flow of the market is determined by the forces between bulls and bears. There are specific levels that the market respects due to the forces acting on them. Fibonacci and VWAP levels are especially powerful in influencing market behavior. Join me in this article as we explore a strategy based on VWAP and Fibonacci levels for signal generation.
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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.
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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.
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Circle Search Algorithm (CSA)

Circle Search Algorithm (CSA)

The article presents a new metaheuristic optimization Circle Search Algorithm (CSA) based on the geometric properties of a circle. The algorithm uses the principle of moving points along tangents to find the optimal solution, combining the phases of global exploration and local exploitation.
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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.
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Developing an MQL5 RL agent with RestAPI integration (Part 2): MQL5 functions for HTTP interaction with the tic-tac-toe game REST API

Developing an MQL5 RL agent with RestAPI integration (Part 2): MQL5 functions for HTTP interaction with the tic-tac-toe game REST API

In this article we will talk about how MQL5 can interact with Python and FastAPI, using HTTP calls in MQL5 to interact with the tic-tac-toe game in Python. The article discusses the creation of an API using FastAPI for this integration and provides a test script in MQL5, highlighting the versatility of MQL5, the simplicity of Python, and the effectiveness of FastAPI in connecting different technologies to create innovative solutions.
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From Novice to Expert: Reporting EA — Setting up the work flow

From Novice to Expert: Reporting EA — Setting up the work flow

Brokerages often provide trading account reports at regular intervals, based on a predefined schedule. These firms, through their API technologies, have access to your account activity and trading history, allowing them to generate performance reports on your behalf. Similarly, the MetaTrader 5 terminal stores detailed records of your trading activity, which can be leveraged using MQL5 to create fully customized reports and define personalized delivery methods.