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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From Novice to Expert: Animated News Headline Using MQL5 (VIII) — Quick Trade Buttons for News Trading

From Novice to Expert: Animated News Headline Using MQL5 (VIII) — Quick Trade Buttons for News Trading

While algorithmic trading systems manage automated operations, many news traders and scalpers prefer active control during high-impact news events and fast-paced market conditions, requiring rapid order execution and management. This underscores the need for intuitive front-end tools that integrate real-time news feeds, economic calendar data, indicator insights, AI-driven analytics, and responsive trading controls.
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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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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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Building A Candlestick Trend Constraint Model (Part 6): All in one integration

Building A Candlestick Trend Constraint Model (Part 6): All in one integration

One major challenge is managing multiple chart windows of the same pair running the same program with different features. Let's discuss how to consolidate several integrations into one main program. Additionally, we will share insights on configuring the program to print to a journal and commenting on the successful signal broadcast on the chart interface. Find more information in this article as we progress the article series.
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From Novice to Expert: Animated News Headline Using MQL5 (IV) — Locally hosted AI model market insights

From Novice to Expert: Animated News Headline Using MQL5 (IV) — Locally hosted AI model market insights

In today's discussion, we explore how to self-host open-source AI models and use them to generate market insights. This forms part of our ongoing effort to expand the News Headline EA, introducing an AI Insights Lane that transforms it into a multi-integration assistive tool. The upgraded EA aims to keep traders informed through calendar events, financial breaking news, technical indicators, and now AI-generated market perspectives—offering timely, diverse, and intelligent support to trading decisions. Join the conversation as we explore practical integration strategies and how MQL5 can collaborate with external resources to build a powerful and intelligent trading work terminal.
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From Novice to Expert: Backend Operations Monitor using MQL5

From Novice to Expert: Backend Operations Monitor using MQL5

Using a ready-made solution in trading without concerning yourself with the internal workings of the system may sound comforting, but this is not always the case for developers. Eventually, an upgrade, misperformance, or unexpected error will arise, and it becomes essential to trace exactly where the issue originates to diagnose and resolve it quickly. Today’s discussion focuses on uncovering what normally happens behind the scenes of a trading Expert Advisor, and on developing a custom dedicated class for displaying and logging backend processes using MQL5. This gives both developers and traders the ability to quickly locate errors, monitor behavior, and access diagnostic information specific to each EA.
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Creating a Trading Administrator Panel in MQL5 (Part VI): Multiple Functions Interface (I)

Creating a Trading Administrator Panel in MQL5 (Part VI): Multiple Functions Interface (I)

The Trading Administrator's role goes beyond just Telegram communications; they can also engage in various control activities, including order management, position tracking, and interface customization. In this article, we’ll share practical insights on expanding our program to support multiple functionalities in MQL5. This update aims to overcome the current Admin Panel's limitation of focusing primarily on communication, enabling it to handle a broader range of tasks.
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Developing a multi-currency Expert Advisor (Part 11): Automating the optimization (first steps)

Developing a multi-currency Expert Advisor (Part 11): Automating the optimization (first steps)

To get a good EA, we need to select multiple good sets of parameters of trading strategy instances for it. This can be done manually by running optimization on different symbols and then selecting the best results. But it is better to delegate this work to the program and engage in more productive activities.
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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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Developing an MQTT client for Metatrader 5: a TDD approach — Part 4

Developing an MQTT client for Metatrader 5: a TDD approach — Part 4

This article is the fourth part of a series describing our development steps of a native MQL5 client for the MQTT protocol. In this part, we describe what MQTT v5.0 Properties are, their semantics, how we are reading some of them, and provide a brief example of how Properties can be used to extend the protocol.
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Propensity score in causal inference

Propensity score in causal inference

The article examines the topic of matching in causal inference. Matching is used to compare similar observations in a data set. This is necessary to correctly determine causal effects and get rid of bias. The author explains how this helps in building trading systems based on machine learning, which become more stable on new data they were not trained on. The propensity score plays a central role and is widely used in causal inference.
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Developing an MQTT client for MetaTrader 5: a TDD approach — Final

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

This article is the last part of a series describing our development steps of a native MQL5 client for the MQTT 5.0 protocol. Although the library is not production-ready yet, in this part, we will use our client to update a custom symbol with ticks (or rates) sourced from another broker. Please, see the bottom of this article for more information about the library's current status, what is missing for it to be fully compliant with the MQTT 5.0 protocol, a possible roadmap, and how to follow and contribute to its development.
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Connexus Helper (Part 5): HTTP Methods and Status Codes

Connexus Helper (Part 5): HTTP Methods and Status Codes

In this article, we will understand HTTP methods and status codes, two very important pieces of communication between client and server on the web. Understanding what each method does gives you the control to make requests more precisely, informing the server what action you want to perform and making it more efficient.
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The base class of population algorithms as the backbone of efficient optimization

The base class of population algorithms as the backbone of efficient optimization

The article represents a unique research attempt to combine a variety of population algorithms into a single class to simplify the application of optimization methods. This approach not only opens up opportunities for the development of new algorithms, including hybrid variants, but also creates a universal basic test stand. This stand becomes a key tool for choosing the optimal algorithm depending on a specific task.
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Dialectic Search (DA)

Dialectic Search (DA)

The article introduces the dialectical algorithm (DA), a new global optimization method inspired by the philosophical concept of dialectics. The algorithm exploits a unique division of the population into speculative and practical thinkers. Testing shows impressive performance of up to 98% on low-dimensional problems and overall efficiency of 57.95%. The article explains these metrics and presents a detailed description of the algorithm and the results of experiments on different types of functions.
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Evolutionary trading algorithm with reinforcement learning and extinction of feeble individuals (ETARE)

Evolutionary trading algorithm with reinforcement learning and extinction of feeble individuals (ETARE)

In this article, I introduce an innovative trading algorithm that combines evolutionary algorithms with deep reinforcement learning for Forex trading. The algorithm uses the mechanism of extinction of inefficient individuals to optimize the trading strategy.
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MQL5 Wizard Techniques you should know (Part 58): Reinforcement Learning (DDPG) with Moving Average and Stochastic Oscillator Patterns

MQL5 Wizard Techniques you should know (Part 58): Reinforcement Learning (DDPG) with Moving Average and Stochastic Oscillator Patterns

Moving Average and Stochastic Oscillator are very common indicators whose collective patterns we explored in the prior article, via a supervised learning network, to see which “patterns-would-stick”. We take our analyses from that article, a step further by considering the effects' reinforcement learning, when used with this trained network, would have on performance. Readers should note our testing is over a very limited time window. Nonetheless, we continue to harness the minimal coding requirements afforded by the MQL5 wizard in showcasing this.
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Blood inheritance optimization (BIO)

Blood inheritance optimization (BIO)

I present to you my new population optimization algorithm - Blood Inheritance Optimization (BIO), inspired by the human blood group inheritance system. In this algorithm, each solution has its own "blood type" that determines the way it evolves. Just as in nature where a child's blood type is inherited according to specific rules, in BIO new solutions acquire their characteristics through a system of inheritance and mutations.
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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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Developing a multi-currency Expert Advisor (Part 9): Collecting optimization results for single trading strategy instances

Developing a multi-currency Expert Advisor (Part 9): Collecting optimization results for single trading strategy instances

Let's outline the main stages of the EA development. One of the first things to be done will be to optimize a single instance of the developed trading strategy. Let's try to collect all the necessary information about the tester passes during the optimization in one place.
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Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (V): AnalyticsPanel Class

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (V): AnalyticsPanel Class

In this discussion, we explore how to retrieve real-time market data and trading account information, perform various calculations, and display the results on a custom panel. To achieve this, we will dive deeper into developing an AnalyticsPanel class that encapsulates all these features, including panel creation. This effort is part of our ongoing expansion of the New Admin Panel EA, introducing advanced functionalities using modular design principles and best practices for code organization.
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MQL5 Wizard Techniques you should know (Part 21): Testing with Economic Calendar Data

MQL5 Wizard Techniques you should know (Part 21): Testing with Economic Calendar Data

Economic Calendar Data is not available for testing with Expert Advisors within Strategy Tester, by default. We look at how Databases could help in providing a work around this limitation. So, for this article we explore how SQLite databases can be used to archive Economic Calendar news such that wizard assembled Expert Advisors can use this to generate trade signals.
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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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Price Action Analysis Toolkit Development (Part 9): External Flow

Price Action Analysis Toolkit Development (Part 9): External Flow

This article explores a new dimension of analysis using external libraries specifically designed for advanced analytics. These libraries, like pandas, provide powerful tools for processing and interpreting complex data, enabling traders to gain more profound insights into market dynamics. By integrating such technologies, we can bridge the gap between raw data and actionable strategies. Join us as we lay the foundation for this innovative approach and unlock the potential of combining technology with trading expertise.
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MQL5 Wizard Techniques you should know (Part 79): Using Gator Oscillator and Accumulation/Distribution Oscillator with Supervised Learning

MQL5 Wizard Techniques you should know (Part 79): Using Gator Oscillator and Accumulation/Distribution Oscillator with Supervised Learning

In the last piece, we concluded our look at the pairing of the gator oscillator and the accumulation/distribution oscillator when used in their typical setting of the raw signals they generate. These two indicators are complimentary as trend and volume indicators, respectively. We now follow up that piece, by examining the effect that supervised learning can have on enhancing some of the feature patterns we had reviewed. Our supervised learning approach is a CNN that engages with kernel regression and dot product similarity to size its kernels and channels. As always, we do this in a custom signal class file that works with the MQL5 wizard to assemble an Expert Advisor.
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Combinatorially Symmetric Cross Validation In MQL5

Combinatorially Symmetric Cross Validation In MQL5

In this article we present the implementation of Combinatorially Symmetric Cross Validation in pure MQL5, to measure the degree to which a overfitting may occure after optimizing a strategy using the slow complete algorithm of the Strategy Tester.
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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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From Novice to Expert: Animated News Headline Using MQL5 (VII) — Post Impact Strategy for News Trading

From Novice to Expert: Animated News Headline Using MQL5 (VII) — Post Impact Strategy for News Trading

The risk of whipsaw is extremely high during the first minute following a high-impact economic news release. In that brief window, price movements can be erratic and volatile, often triggering both sides of pending orders. Shortly after the release—typically within a minute—the market tends to stabilize, resuming or correcting the prevailing trend with more typical volatility. In this section, we’ll explore an alternative approach to news trading, aiming to assess its effectiveness as a valuable addition to a trader’s toolkit. Continue reading for more insights and details in this discussion.
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From Novice to Expert: Animated News Headline Using MQL5 (I)

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

News accessibility is a critical factor when trading on the MetaTrader 5 terminal. While numerous news APIs are available, many traders face challenges in accessing and integrating them effectively into their trading environment. In this discussion, we aim to develop a streamlined solution that brings news directly onto the chart—where it’s most needed. We'll accomplish this by building a News Headline Expert Advisor that monitors and displays real-time news updates from API sources.
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Royal Flush Optimization (RFO)

Royal Flush Optimization (RFO)

The original Royal Flush Optimization algorithm offers a new approach to solving optimization problems, replacing the classic binary coding of genetic algorithms with a sector-based approach inspired by poker principles. RFO demonstrates how simplifying basic principles can lead to an efficient and practical optimization method. The article presents a detailed analysis of the algorithm and test results.
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Developing a multi-currency Expert Advisor (Part 7): Selecting a group based on forward period

Developing a multi-currency Expert Advisor (Part 7): Selecting a group based on forward period

Previously, we evaluated the selection of a group of trading strategy instances, with the aim of improving the results of their joint operation, only on the same time period, in which the optimization of individual instances was carried out. Let's see what happens in the forward period.
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MQL5 Wizard Techniques you should know (Part 66): Using Patterns of FrAMA and the Force Index with the Dot Product Kernel

MQL5 Wizard Techniques you should know (Part 66): Using Patterns of FrAMA and the Force Index with the Dot Product Kernel

The FrAMA Indicator and the Force Index Oscillator are trend and volume tools that could be paired when developing an Expert Advisor. We continue from our last article that introduced this pair by considering machine learning applicability to the pair. We are using a convolution neural network that uses the dot-product kernel in making forecasts with these indicators’ inputs. This is done in a custom signal class file that works with the MQL5 wizard to assemble an Expert Advisor.
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Adaptive Social Behavior Optimization (ASBO): Schwefel, Box-Muller Method

Adaptive Social Behavior Optimization (ASBO): Schwefel, Box-Muller Method

This article provides a fascinating insight into the world of social behavior in living organisms and its influence on the creation of a new mathematical model - ASBO (Adaptive Social Behavior Optimization). We will examine how the principles of leadership, neighborhood, and cooperation observed in living societies inspire the development of innovative optimization algorithms.
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MQL5 Wizard Techniques you should know (Part 62): Using Patterns of ADX and CCI with Reinforcement-Learning TRPO

MQL5 Wizard Techniques you should know (Part 62): Using Patterns of ADX and CCI with Reinforcement-Learning TRPO

The ADX Oscillator and CCI oscillator are trend following and momentum indicators that can be paired when developing an Expert Advisor. We continue where we left off in the last article by examining how in-use training, and updating of our developed model, can be made thanks to reinforcement-learning. We are using an algorithm we are yet to cover in these series, known as Trusted Region Policy Optimization. And, as always, Expert Advisor assembly by the MQL5 Wizard allows us to set up our model(s) for testing much quicker and also in a way where it can be distributed and tested with different signal types.
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Population optimization algorithms: Bird Swarm Algorithm (BSA)

Population optimization algorithms: Bird Swarm Algorithm (BSA)

The article explores the bird swarm-based algorithm (BSA) inspired by the collective flocking interactions of birds in nature. The different search strategies of individuals in BSA, including switching between flight, vigilance and foraging behavior, make this algorithm multifaceted. It uses the principles of bird flocking, communication, adaptability, leading and following to efficiently find optimal solutions.
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MQL5 Wizard Techniques you should know (Part 59): Reinforcement Learning (DDPG) with Moving Average and Stochastic Oscillator Patterns

MQL5 Wizard Techniques you should know (Part 59): Reinforcement Learning (DDPG) with Moving Average and Stochastic Oscillator Patterns

We continue our last article on DDPG with MA and stochastic indicators by examining other key Reinforcement Learning classes crucial for implementing DDPG. Though we are mostly coding in python, the final product, of a trained network will be exported to as an ONNX to MQL5 where we integrate it as a resource in a wizard assembled Expert Advisor.
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From Novice to Expert: Animated News Headline Using MQL5 (XI)—Correlation in News Trading

From Novice to Expert: Animated News Headline Using MQL5 (XI)—Correlation in News Trading

In this discussion, we will explore how the concept of Financial Correlation can be applied to improve decision-making efficiency when trading multiple symbols during major economic events announcement. The focus is on addressing the challenge of heightened risk exposure caused by increased volatility during news releases.
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Creating a Trading Administrator Panel in MQL5 (Part III): Extending Built-in Classes for Theme Management (II)

Creating a Trading Administrator Panel in MQL5 (Part III): Extending Built-in Classes for Theme Management (II)

In this discussion, we will carefully extend the existing Dialog library to incorporate theme management logic. Furthermore, we will integrate methods for theme switching into the CDialog, CEdit, and CButton classes utilized in our Admin Panel project. Continue reading for more insightful perspectives.
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Twitter Sentiment Analysis with Sockets

Twitter Sentiment Analysis with Sockets

This innovative trading bot integrates MetaTrader 5 with Python to leverage real-time social media sentiment analysis for automated trading decisions. By analyzing Twitter sentiment related to specific financial instruments, the bot translates social media trends into actionable trading signals. It utilizes a client-server architecture with socket communication, enabling seamless interaction between MT5's trading capabilities and Python's data processing power. The system demonstrates the potential of combining quantitative finance with natural language processing, offering a cutting-edge approach to algorithmic trading that capitalizes on alternative data sources.
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Artificial Bee Hive Algorithm (ABHA): Theory and methods

Artificial Bee Hive Algorithm (ABHA): Theory and methods

In this article, we will consider the Artificial Bee Hive Algorithm (ABHA) developed in 2009. The algorithm is aimed at solving continuous optimization problems. We will look at how ABHA draws inspiration from the behavior of a bee colony, where each bee has a unique role that helps them find resources more efficiently.