Articles with MQL5 programming examples

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Access a huge collection of articles with code examples showing how to create indicators and trading robots for the MetaTrader platform in the MQL5 language. Source codes are attached to the articles, so you can open them in MetaEditor and run them to see how the applications work.

These articles will be useful both for those who have just started exploring automated trading and for professional traders with programming experience. They feature not only examples, but also contain new ideas.

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From Basic to Intermediate: Arrays and Strings (III)

From Basic to Intermediate: Arrays and Strings (III)

This article considers two aspects. First, how the standard library can convert binary values to other representations such as octal, decimal, and hexadecimal. Second, we will talk about how we can determine the width of our password based on the secret phrase, using the knowledge we have already acquired.
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From Basic to Intermediate: Indicator (V)

From Basic to Intermediate: Indicator (V)

In this article, we will look at how to handle user requests to change the chart plotting mode. This is necessary so that an indicator designed for the current chart plotting mode does not look strange or differ from what a MetaTrader 5 user expects.
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From Basic to Intermediate: Arrays and Strings (I)

From Basic to Intermediate: Arrays and Strings (I)

In today's article, we'll start exploring some special data types. To begin, we'll define what a string is and explain how to use some basic procedures. This will allow us to work with this type of data, which can be interesting, although sometimes a little confusing for beginners. The content presented here is intended solely for educational purposes. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.
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Overcoming Accessibility Challenges in MQL5 Trading Tools (Part II): Enabling EA Voice Using a Python Text-to-Speech Engine

Overcoming Accessibility Challenges in MQL5 Trading Tools (Part II): Enabling EA Voice Using a Python Text-to-Speech Engine

Let's discuss how we can make our Expert Advisors speech‑capable using text‑to‑speech technology, partnering Python and MQL5. After reading this article, you will walk away with a working example of an EA that speaks dynamic market information. You will master the application of TTS, the WebRequest function, and learn how Python libraries integrate with the MQL5 language to create a truly voice‑aware trading tool.
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Population optimization algorithms: Evolution of Social Groups (ESG)

Population optimization algorithms: Evolution of Social Groups (ESG)

We will consider the principle of constructing multi-population algorithms. As an example of this type of algorithm, we will have a look at the new custom algorithm - Evolution of Social Groups (ESG). We will analyze the basic concepts, population interaction mechanisms and advantages of this algorithm, as well as examine its performance in optimization problems.
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Overcoming Accessibility Problems in MQL5 Trading Tools (Part III): Bidirectional Speech Communication Between a Trader and an Expert Advisor

Overcoming Accessibility Problems in MQL5 Trading Tools (Part III): Bidirectional Speech Communication Between a Trader and an Expert Advisor

Build a local, bidirectional voice interface for MetaTrader 5 using MQL5 WebRequest and two Python services. The article implements offline speech recognition with Vosk, wake‑word detection, an HTTP command endpoint, and a text‑to‑speech server on localhost. You will wire an Expert Advisor that fetches commands, executes trades, and returns spoken confirmations for hands‑free operation.
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Forecasting in Trading Using Grey Models

Forecasting in Trading Using Grey Models

The article discusses the application of Grey models to forecasting financial time series. We will consider the operating principles of Grey models and the specifics of their application to financial series. We will also discuss the advantages and limitations of using these models in trading.
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Multiple Symbol Analysis With Python And MQL5 (Part II): Principal Components Analysis For Portfolio Optimization

Multiple Symbol Analysis With Python And MQL5 (Part II): Principal Components Analysis For Portfolio Optimization

Managing trading account risk is a challenge for all traders. How can we develop trading applications that dynamically learn high, medium, and low-risk modes for various symbols in MetaTrader 5? By using PCA, we gain better control over portfolio variance. I’ll demonstrate how to create applications that learn these three risk modes from market data fetched from MetaTrader 5.
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Overcoming The Limitation of Machine Learning (Part 4): Overcoming Irreducible Error Using Multiple Forecast Horizons

Overcoming The Limitation of Machine Learning (Part 4): Overcoming Irreducible Error Using Multiple Forecast Horizons

Machine learning is often viewed through statistical or linear algebraic lenses, but this article emphasizes a geometric perspective of model predictions. It demonstrates that models do not truly approximate the target but rather map it onto a new coordinate system, creating an inherent misalignment that results in irreducible error. The article proposes that multi-step predictions, comparing the model’s forecasts across different horizons, offer a more effective approach than direct comparisons with the target. By applying this method to a trading model, the article demonstrates significant improvements in profitability and accuracy without changing the underlying model.
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DoEasy. Controls (Part 33): Vertical ScrollBar

DoEasy. Controls (Part 33): Vertical ScrollBar

In this article, we will continue the development of graphical elements of the DoEasy library and add vertical scrolling of form object controls, as well as some useful functions and methods that will be required in the future.
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Bacterial Chemotaxis Optimization (BCO)

Bacterial Chemotaxis Optimization (BCO)

The article presents the original version of the Bacterial Chemotaxis Optimization (BCO) algorithm and its modified version. We will take a closer look at all the differences, with a special focus on the new version of BCOm, which simplifies the bacterial movement mechanism, reduces the dependence on positional history, and uses simpler math than the computationally heavy original version. We will also conduct the tests and summarize the results.
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MQL5 Trading Toolkit (Part 5): Expanding the History Management EX5 Library with Position Functions

MQL5 Trading Toolkit (Part 5): Expanding the History Management EX5 Library with Position Functions

Discover how to create exportable EX5 functions to efficiently query and save historical position data. In this step-by-step guide, we will expand the History Management EX5 library by developing modules that retrieve key properties of the most recently closed position. These include net profit, trade duration, pip-based stop loss, take profit, profit values, and various other important details.
All about Automated Trading Championship: Interviews with the Participants'06
All about Automated Trading Championship: Interviews with the Participants'06

All about Automated Trading Championship: Interviews with the Participants'06

Interviews with the Participants of Automated Trading Championship 2006 demonstrated a great variety of views of automated trading and trading as a whole. You can see yourselves which ideas turned out to work better during the Championship and which of them could not pass the critical verification through a three-month long "test-drive" on a contest account.
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The MQL5 Standard Library Explorer (Part 6): Optimizing a generated Expert Advisor

The MQL5 Standard Library Explorer (Part 6): Optimizing a generated Expert Advisor

In this discussion, we follow up on the previously developed multi-signal Expert Advisor with the objective of exploring and applying available optimization methods. The aim is to determine whether the trading performance of the EA can be meaningfully improved through systematic optimization based on historical data.
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Developing a Replay System (Part 65): Playing the service (VI)

Developing a Replay System (Part 65): Playing the service (VI)

In this article, we will look at how to implement and solve the mouse pointer issue when using it in conjunction with a replay/simulation application. The content presented here is intended solely for educational purposes. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.
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From Basic to Intermediate: Events (I)

From Basic to Intermediate: Events (I)

Given everything that has been shown so far, I think we can now start implementing some kind of application to run some symbol directly on the chart. However, first we need to talk about a concept that can be rather confusing for beginners. Namely, it's the fact that applications developed in MQL5 and intended for display on a chart are not created in the same way as we have seen so far. In this article, we'll begin to understand this a little better.
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Creating a Trading Administrator Panel in MQL5 (Part VII): Trusted User, Recovery and Cryptography

Creating a Trading Administrator Panel in MQL5 (Part VII): Trusted User, Recovery and Cryptography

Security prompts, such as those triggered every time you refresh the chart, add a new pair to the chat with the Admin Panel EA, or restart the terminal, can become tedious. In this discussion, we will explore and implement a feature that tracks the number of login attempts to identify a trusted user. After a set number of failed attempts, the application will transition to an advanced login procedure, which also facilitates passcode recovery for users who may have forgotten it. Additionally, we will cover how cryptography can be effectively integrated into the Admin Panel to enhance security.
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Gating mechanisms in ensemble learning

Gating mechanisms in ensemble learning

In this article, we continue our exploration of ensemble models by discussing the concept of gates, specifically how they may be useful in combining model outputs to enhance either prediction accuracy or model generalization.
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Database Is Easy (Part 1): A Lightweight ORM Framework for MQL5 Using SQLite

Database Is Easy (Part 1): A Lightweight ORM Framework for MQL5 Using SQLite

This article presents a structured way to manage SQLite data in MQL5 through an ORM layer for MetaTrader 5. It introduces core classes for entity modeling and database access, a fluent CRUD API, reflection hooks for OnGet/OnSet, and macros to define models quickly. Practical code shows creating tables, binding fields, inserting, updating, querying, and deleting records. Developers gain reusable, type-safe components that minimize repetitive SQL.
Method of Determining Errors in Code by Commenting
Method of Determining Errors in Code by Commenting

Method of Determining Errors in Code by Commenting

The article describes a method of searching the errors in the MQL4 code that is based on commenting. This method is found to be a useful one in case of problems occuring during the compilation caused by the errors in a reasonably large code.
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The Group Method of Data Handling: Implementing the Multilayered Iterative Algorithm in MQL5

The Group Method of Data Handling: Implementing the Multilayered Iterative Algorithm in MQL5

In this article we describe the implementation of the Multilayered Iterative Algorithm of the Group Method of Data Handling in MQL5.
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Developing a Replay System (Part 52): Things Get Complicated (IV)

Developing a Replay System (Part 52): Things Get Complicated (IV)

In this article, we will change the mouse pointer to enable the interaction with the control indicator to ensure reliable and stable operation.
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Category Theory in MQL5 (Part 11): Graphs

Category Theory in MQL5 (Part 11): Graphs

This article is a continuation in a series that look at Category Theory implementation in MQL5. In here we examine how Graph-Theory could be integrated with monoids and other data structures when developing a close-out strategy to a trading system.
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Price Action Analysis Toolkit Development (Part 77): Building a Searchable Indicator Panel for MetaTrader 5

Price Action Analysis Toolkit Development (Part 77): Building a Searchable Indicator Panel for MetaTrader 5

A modular indicator search system for MetaTrader 5 that replaces manual navigation through built-in indicator categories with a searchable interface. The application integrates an indicator catalog, search engine, chart launcher, and graphical panel, allowing indicators to be located, filtered, and attached to the appropriate chart window from a single interface.
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Population optimization algorithms: Binary Genetic Algorithm (BGA). Part I

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

In this article, we will explore various methods used in binary genetic and other population algorithms. We will look at the main components of the algorithm, such as selection, crossover and mutation, and their impact on the optimization. In addition, we will study data presentation methods and their impact on optimization results.
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Market Simulation (Part 05): Creating the C_Orders Class (II)

Market Simulation (Part 05): Creating the C_Orders Class (II)

In this article, I will explain how Chart Trade, together with the Expert Advisor, will process a request to close all of the users' open positions. This may sound simple, but there are a few complications that you need to know how to manage.
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Developing an MQL5 RL agent with RestAPI integration (Part 4): Organizing functions in classes in MQL5

Developing an MQL5 RL agent with RestAPI integration (Part 4): Organizing functions in classes in MQL5

This article discusses the transition from procedural coding to object-oriented programming (OOP) in MQL5 with an emphasis on integration with the REST API. Today we will discuss how to organize HTTP request functions (GET and POST) into classes. We will take a closer look at code refactoring and show how to replace isolated functions with class methods. The article contains practical examples and tests.
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Market Simulation (Part 03): A Matter of Performance

Market Simulation (Part 03): A Matter of Performance

Often we have to take a step back and then move forward. In this article, we will show all the changes necessary to ensure that the Mouse and Chart Trade indicators do not break. As a bonus, we'll also cover other changes that have occurred in other header files that will be widely used in the future.
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From Basic to Intermediate: Template and Typename (IV)

From Basic to Intermediate: Template and Typename (IV)

In this article, we will take a very close look at how to solve the problem posed at the end of the previous article. There was an attempt to create a template of such type so that to be able to create a template for data union.
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Building a Correlation-Aware Portfolio Risk Monitor in MQL5

Building a Correlation-Aware Portfolio Risk Monitor in MQL5

The article quantifies correlation and portfolio risk in MetaTrader 5: from time-aligned returns to a covariance matrix, true portfolio variance against the independent-sum assumption, and position-level risk attribution. A MetaTrader 5 service runs in the background, shows the metrics on a small chart panel, and pushes alerts when risk thresholds are crossed. Source code is provided for an example script, a reusable risk engine class, and the service.
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Eigenvectors and eigenvalues: Exploratory data analysis in MetaTrader 5

Eigenvectors and eigenvalues: Exploratory data analysis in MetaTrader 5

In this article we explore different ways in which the eigenvectors and eigenvalues can be applied in exploratory data analysis to reveal unique relationships in data.
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The MQL5 Standard Library Explorer (Part 12): Multi-Timeframe Composite-Score Dashboard

The MQL5 Standard Library Explorer (Part 12): Multi-Timeframe Composite-Score Dashboard

The article implements CMultiTimeframeMatrix, a reusable dashboard that maps symbols vs. timeframes and displays a numeric, colour‑coded score. The score combines trend, momentum, and volatility, updates by timer, and respects performance constraints. You will learn how to build the UI with CAppDialog/CLabel, compute metrics via CMatrixDouble, and embed the component into a thin EA for a consistent, real-time overview.
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From Basic to Intermediate: Definitions (I)

From Basic to Intermediate: Definitions (I)

In this article we will do things that many will find strange and completely out of context, but which, if used correctly, will make your learning much more fun and interesting: we will be able to build quite interesting things based on what is shown here. This will allow you to better understand the syntax of the MQL5 language. The materials provided here are for educational purposes only. It should not be considered in any way as a final application. Its purpose is not to explore the concepts presented.
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The MQL5 Standard Library Explorer (Part 12): Multi-Timeframe Composite-Score Dashboard

The MQL5 Standard Library Explorer (Part 12): Multi-Timeframe Composite-Score Dashboard

The article implements CMultiTimeframeMatrix, a reusable dashboard that maps symbols vs. timeframes and displays a numeric, colour‑coded score. The score combines trend, momentum, and volatility, updates by timer, and respects performance constraints. You will learn how to build the UI with CAppDialog/CLabel, compute metrics via CMatrixDouble, and embed the component into a thin EA for a consistent, real-time overview.
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Engineering Trading Discipline into Code (Part 6): Building a Unified Discipline Framework in MQL5

Engineering Trading Discipline into Code (Part 6): Building a Unified Discipline Framework in MQL5

The article introduces a unified MQL5 discipline framework that consolidates the symbol whitelist, trading‑hours and news filters, and daily trade‑limit modules under CDisciplineEngine.mqh. It explains centralized trade validation and state synchronization shared by a chart dashboard and an enforcement Expert Advisor. Readers learn how to authorize orders through a single gate, monitor permissions in real time, and automatically enforce rules across the terminal.
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Meta-Labeling the Classics (Part 1): Filtering and Sizing RSI Trades

Meta-Labeling the Classics (Part 1): Filtering and Sizing RSI Trades

RSI accumulates losses in trending conditions by firing at every threshold crossing regardless of market regime. A Random Forest secondary classifier trained on 12 contextual features — RSI momentum slope, EMA50 trend velocity, ATR-normalised trend stretch, and nine others — filters raw signals and scales position size by classifier confidence on EURUSD H1. Results compare plain RSI, meta-filtered RSI, and bet-sized RSI across a 16-month out-of-sample period with per-trade metrics and drawdown diagnostics.
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Population optimization algorithms: Micro Artificial immune system (Micro-AIS)

Population optimization algorithms: Micro Artificial immune system (Micro-AIS)

The article considers an optimization method based on the principles of the body's immune system - Micro Artificial Immune System (Micro-AIS) - a modification of AIS. Micro-AIS uses a simpler model of the immune system and simple immune information processing operations. The article also discusses the advantages and disadvantages of Micro-AIS compared to conventional AIS.
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From Novice to Expert: Systematic Profit Conservation Using Candle Range Theory

From Novice to Expert: Systematic Profit Conservation Using Candle Range Theory

A hybrid exit engine for MQL5 replaces static TPs with CRT-derived structural levels. The CRT_ProfitConserve class secures a partial at the first level and then trails the remaining position by structural anchors rather than fixed pips. The article walks through the class API, essential methods, and example usage in EAs, providing a clear path to embed CRT-based exits into existing strategies.
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GoertzelBrain: Adaptive Spectral Cycle Detection with Neural Network Ensemble in MQL5

GoertzelBrain: Adaptive Spectral Cycle Detection with Neural Network Ensemble in MQL5

GoertzelBrain combines Goertzel spectral analysis with an online‑trained neural network ensemble to convert cycle features into a directional confirmation signal. The indicator builds a compact feature vector from the dominant period, amplitude, confidence and their dynamics, plus local volatility, and outputs +1, −1 or 0. The article provides the full MQL5 implementation, explains the architecture and feature engineering, and shows how to use it as a directional filter.
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MQL5 Wizard Techniques you should know (Part 18): Neural Architecture Search with Eigen Vectors

MQL5 Wizard Techniques you should know (Part 18): Neural Architecture Search with Eigen Vectors

Neural Architecture Search, an automated approach at determining the ideal neural network settings can be a plus when facing many options and large test data sets. We examine how when paired Eigen Vectors this process can be made even more efficient.