MQL5 Programming Articles

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Study the MQL5 language for programming trading strategies in numerous published articles mostly written by you - the community members. The articles are grouped into categories to help you quicker find answers to any questions related to programming: Integration, Tester, Trading Strategies, etc.

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Engineering Trading Discipline into Code (Part 2): Building a Daily Trade Limit Enforcer for All Trades in MQL5

Engineering Trading Discipline into Code (Part 2): Building a Daily Trade Limit Enforcer for All Trades in MQL5

We have developed a system that enforces a daily trade limit to keep you aligned with your trading rules. It monitors all executed trades across the account and automatically intervenes once the defined limit is reached, preventing any further activity. By embedding control directly into the platform, the system ensures discipline is maintained even when market pressure rises.
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MQL5 Cookbook — Services

MQL5 Cookbook — Services

The article describes the versatile capabilities of services — MQL5 programs that do not require binding graphs. I will also highlight the differences of services from other MQL5 programs and emphasize the nuances of the developer's work with services. As examples, the reader is offered various tasks covering a wide range of functionality that can be implemented as a service.
Creating Documentation Based on MQL5 Source Code
Creating Documentation Based on MQL5 Source Code

Creating Documentation Based on MQL5 Source Code

This article considers creation of documentation for MQL5 code starting with the automated markup of required tags. It also provides the description of how to use the Doxygen software, how to properly configure it and how to receive results in different formats, including html, HtmlHelp and PDF.
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Creating an EA that works automatically (Part 06): Account types (I)

Creating an EA that works automatically (Part 06): Account types (I)

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. Our EA in its current state can work in any situation but it is not yet ready for automation. We still have to work on a few points.
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Learn how to design a trading system by DeMarker

Learn how to design a trading system by DeMarker

Here is a new article in our series about how to design a trading system by the most popular technical indicators. In this article, we will present how to create a trading system by the DeMarker indicator.
Building a Spectrum Analyzer
Building a Spectrum Analyzer

Building a Spectrum Analyzer

This article is intended to get its readers acquainted with a possible variant of using graphical objects of the MQL5 language. It analyses an indicator, which implements a panel of managing a simple spectrum analyzer using the graphical objects. The article is meant for readers acquianted with basics of MQL5.
Timeseries in DoEasy library (part 45): Multi-period indicator buffers
Timeseries in DoEasy library (part 45): Multi-period indicator buffers

Timeseries in DoEasy library (part 45): Multi-period indicator buffers

In this article, I will start the improvement of the indicator buffer objects and collection class for working in multi-period and multi-symbol modes. I am going to consider the operation of buffer objects for receiving and displaying data from any timeframe on the current symbol chart.
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Learn how to design a trading system by Force Index

Learn how to design a trading system by Force Index

Welcome to a new article in our series about how to design a trading system by the most popular technical indicators. In this article, we will learn about a new technical indicator and how to create a trading system using the Force Index indicator.
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Creating an EA that works automatically (Part 12): Automation (IV)

Creating an EA that works automatically (Part 12): Automation (IV)

If you think automated systems are simple, then you probably don't fully understand what it takes to create them. In this article, we will talk about the problem that kills a lot of Expert Advisors. The indiscriminate triggering of orders is a possible solution to this problem.
Graphics in DoEasy library (Part 89): Programming standard graphical objects. Basic functionality
Graphics in DoEasy library (Part 89): Programming standard graphical objects. Basic functionality

Graphics in DoEasy library (Part 89): Programming standard graphical objects. Basic functionality

Currently, the library is able to track standard graphical objects on the client terminal chart, including their removal and modification of some of their parameters. At the moment, it lacks the ability to create standard graphical objects from custom programs.
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MetaTrader 5 Machine Learning Blueprint (Part 5): Sequential Bootstrapping—Debiasing Labels, Improving Returns

MetaTrader 5 Machine Learning Blueprint (Part 5): Sequential Bootstrapping—Debiasing Labels, Improving Returns

Sequential bootstrapping reshapes bootstrap sampling for financial machine learning by actively avoiding temporally overlapping labels, producing more independent training samples, sharper uncertainty estimates, and more robust trading models. This practical guide explains the intuition, shows the algorithm step‑by‑step, provides optimized code patterns for large datasets, and demonstrates measurable performance gains through simulations and real backtests.
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Neural networks made easy (Part 30): Genetic algorithms

Neural networks made easy (Part 30): Genetic algorithms

Today I want to introduce you to a slightly different learning method. We can say that it is borrowed from Darwin's theory of evolution. It is probably less controllable than the previously discussed methods but it allows training non-differentiable models.
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Learn how to design a trading system by Accumulation/Distribution (AD)

Learn how to design a trading system by Accumulation/Distribution (AD)

Welcome to the new article from our series about learning how to design trading systems based on the most popular technical indicators. In this article, we will learn about a new technical indicator called Accumulation/Distribution indicator and find out how to design an MQL5 trading system based on simple AD trading strategies.
Statistical Estimations
Statistical Estimations

Statistical Estimations

Estimation of statistical parameters of a sequence is very important, since most of mathematical models and methods are based on different assumptions. For example, normality of distribution law or dispersion value, or other parameters. Thus, when analyzing and forecasting of time series we need a simple and convenient tool that allows quickly and clearly estimating the main statistical parameters. The article shortly describes the simplest statistical parameters of a random sequence and several methods of its visual analysis. It offers the implementation of these methods in MQL5 and the methods of visualization of the result of calculations using the Gnuplot application.
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Building AI-Powered Trading Systems in MQL5 (Part 2): Developing a ChatGPT-Integrated Program with User Interface

Building AI-Powered Trading Systems in MQL5 (Part 2): Developing a ChatGPT-Integrated Program with User Interface

In this article, we develop a ChatGPT-integrated program in MQL5 with a user interface, leveraging the JSON parsing framework from Part 1 to send prompts to OpenAI’s API and display responses on a MetaTrader 5 chart. We implement a dashboard with an input field, submit button, and response display, handling API communication and text wrapping for user interaction.
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Ready-made templates for including indicators to Expert Advisors (Part 3): Trend indicators

Ready-made templates for including indicators to Expert Advisors (Part 3): Trend indicators

In this reference article, we will look at standard indicators from the Trend Indicators category. We will create ready-to-use templates for indicator use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.
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Building A Candlestick Trend Constraint Model(Part 2): Merging Native Indicators

Building A Candlestick Trend Constraint Model(Part 2): Merging Native Indicators

This article focuses on taking advantage of in-built meta trader 5 indicators to screen out off-trend signals. Advancing from the previous article we will explore how to do it using MQL5 code to communicate our idea to the final program.
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Crow Search Algorithm (CSA)

Crow Search Algorithm (CSA)

The Crow Search Algorithm (CSA) is an elegant metaheuristic inspired by crows’ ability to hide food and find other crows' caches, solving optimization problems by balancing following successful solutions with random exploration of the search space. Let's find out how well the algorithm performs.
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Working with ONNX models in float16 and float8 formats

Working with ONNX models in float16 and float8 formats

Data formats used to represent machine learning models play a crucial role in their effectiveness. In recent years, several new types of data have emerged, specifically designed for working with deep learning models. In this article, we will focus on two new data formats that have become widely adopted in modern models.
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Gradient boosting in transductive and active machine learning

Gradient boosting in transductive and active machine learning

In this article, we will consider active machine learning methods utilizing real data, as well discuss their pros and cons. Perhaps you will find these methods useful and will include them in your arsenal of machine learning models. Transduction was introduced by Vladimir Vapnik, who is the co-inventor of the Support-Vector Machine (SVM).
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How to add Trailing Stop using Parabolic SAR

How to add Trailing Stop using Parabolic SAR

When creating a trading strategy, we need to test a variety of protective stop options. Here is where a dynamic pulling up of the Stop Loss level following the price comes to mind. The best candidate for this is the Parabolic SAR indicator. It is difficult to think of anything simpler and visually clearer.
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Visual evaluation of optimization results

Visual evaluation of optimization results

In this article, we will consider how to build graphs of all optimization passes and to select the optimal custom criterion. We will also see how to create a desired solution with little MQL5 knowledge, using the articles published on the website and forum comments.
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MQL5 Wizard techniques you should know (Part 01): Regression Analysis

MQL5 Wizard techniques you should know (Part 01): Regression Analysis

Todays trader is a philomath who is almost always (either consciously or not...) looking up new ideas, trying them out, choosing to modify them or discard them; an exploratory process that should cost a fair amount of diligence. This clearly places a premium on the trader's time and the need to avoid mistakes. These series of articles will proposition that the MQL5 wizard should be a mainstay for traders. Why? Because not only does the trader save time by assembling his new ideas with the MQL5 wizard, and greatly reduce mistakes from duplicate coding; he is ultimately set-up to channel his energy on the few critical areas of his trading philosophy.
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How to choose an Expert Advisor: Twenty strong criteria to reject a trading bot

How to choose an Expert Advisor: Twenty strong criteria to reject a trading bot

This article tries to answer the question: how can we choose the right expert advisors? Which are the best for our portfolio, and how can we filter the large trading bots list available on the market? This article will present twenty clear and strong criteria to reject an expert advisor. Each criterion will be presented and well explained to help you make a more sustained decision and build a more profitable expert advisor collection for your profits.
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Learn how to design a trading system by Chaikin Oscillator

Learn how to design a trading system by Chaikin Oscillator

Welcome to our new article from our series about learning how to design a trading system by the most popular technical indicator. Through this new article, we will learn how to design a trading system by the Chaikin Oscillator indicator.
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Data Science and Machine Learning (Part 04): Predicting Current Stock Market Crash

Data Science and Machine Learning (Part 04): Predicting Current Stock Market Crash

In this article I am going to attempt to use our logistic model to predict the stock market crash based upon the fundamentals of the US economy, the NETFLIX and APPLE are the stocks we are going to focus on, Using the previous market crashes of 2019 and 2020 let's see how our model will perform in the current dooms and glooms.
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Moving Average in MQL5 from scratch: Plain and simple

Moving Average in MQL5 from scratch: Plain and simple

Using simple examples, we will examine the principles of calculating moving averages, as well as learn about the ways to optimize indicator calculations, including moving averages.
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MQL5 Wizard techniques you should know (Part 06): Fourier Transform

MQL5 Wizard techniques you should know (Part 06): Fourier Transform

The Fourier transform introduced by Joseph Fourier is a means of deconstructing complex data wave points into simple constituent waves. This feature could be resourceful to traders and this article takes a look at that.
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Introduction to MQL5 (Part 10): A Beginner's Guide to Working with Built-in Indicators in MQL5

Introduction to MQL5 (Part 10): A Beginner's Guide to Working with Built-in Indicators in MQL5

This article introduces working with built-in indicators in MQL5, focusing on creating an RSI-based Expert Advisor (EA) using a project-based approach. You'll learn to retrieve and utilize RSI values, handle liquidity sweeps, and enhance trade visualization using chart objects. Additionally, the article emphasizes effective risk management, including setting percentage-based risk, implementing risk-reward ratios, and applying risk modifications to secure profits.
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Automating Trading Strategies in MQL5 (Part 48): Order Blocks, Inducement, Break of Structure

Automating Trading Strategies in MQL5 (Part 48): Order Blocks, Inducement, Break of Structure

We implement an MQL5 expert advisor that detects order blocks formed after consolidation breakouts and confirms them with fair value gaps. Each zone is validated by a break of structure and a preceding inducement, then filtered by the higher-timeframe trend. The program adds mitigation tracking, risk-based lot sizing, and two trailing stop modes, providing clear on-chart visuals and backtest-ready trade execution logic.
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Data Science and Machine Learning (Part 02): Logistic Regression

Data Science and Machine Learning (Part 02): Logistic Regression

Data Classification is a crucial thing for an algo trader and a programmer. In this article, we are going to focus on one of classification logistic algorithms that can probability help us identify the Yes's or No's, the Ups and Downs, Buys and Sells.
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Developing a trading Expert Advisor from scratch (Part 31): Towards the future (IV)

Developing a trading Expert Advisor from scratch (Part 31): Towards the future (IV)

We continue to remove separate parts from our EA. This is the last article within this series. And the last thing to be removed is the sound system. This can be a bit confusing if you haven't followed these article series.
DIY technical indicator
DIY technical indicator

DIY technical indicator

In this article, I will consider the algorithms allowing you to create your own technical indicator. You will learn how to obtain pretty complex and interesting results with very simple initial assumptions.
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How to Create an Interactive MQL5 Dashboard/Panel Using the Controls Class (Part 2): Adding Button Responsiveness

How to Create an Interactive MQL5 Dashboard/Panel Using the Controls Class (Part 2): Adding Button Responsiveness

In this article, we focus on transforming our static MQL5 dashboard panel into an interactive tool by enabling button responsiveness. We explore how to automate the functionality of the GUI components, ensuring they react appropriately to user clicks. By the end of the article, we establish a dynamic interface that enhances user engagement and trading experience.
Using Discriminant Analysis to Develop Trading Systems
Using Discriminant Analysis to Develop Trading Systems

Using Discriminant Analysis to Develop Trading Systems

When developing a trading system, there usually arises a problem of selecting the best combination of indicators and their signals. Discriminant analysis is one of the methods to find such combinations. The article gives an example of developing an EA for market data collection and illustrates the use of the discriminant analysis for building prognostic models for the FOREX market in Statistica software.
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From Novice to Expert: Creating an MTF CRT Overlay Indicator in MQL5

From Novice to Expert: Creating an MTF CRT Overlay Indicator in MQL5

Higher-timeframe CRT ranges are informative, yet traders often execute on lower timeframes without that context. We implement an MQL5 indicator that reads higher-timeframe OHLC, projects the full candle range, body, and wicks onto the active lower-timeframe chart, and marks entries, stops, and targets. This improves situational awareness and removes the need to switch windows.
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Experiments with neural networks (Part 6): Perceptron as a self-sufficient tool for price forecast

Experiments with neural networks (Part 6): Perceptron as a self-sufficient tool for price forecast

The article provides an example of using a perceptron as a self-sufficient price prediction tool by showcasing general concepts and the simplest ready-made Expert Advisor followed by the results of its optimization.
MQL5 Cloud Network: Are You Still Calculating?
MQL5 Cloud Network: Are You Still Calculating?

MQL5 Cloud Network: Are You Still Calculating?

It will soon be a year and a half since the MQL5 Cloud Network has been launched. This leading edge event ushered in a new era of algorithmic trading - now with a couple of clicks, traders can have hundreds and thousands of computing cores at their disposal for the optimization of their trading strategies.
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Creating an EA that works automatically (Part 03): New functions

Creating an EA that works automatically (Part 03): New functions

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. In the previous article, we started to develop an order system that we will use in our automated EA. However, we have created only one of the necessary functions.
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Timeseries in DoEasy library (part 58): Timeseries of indicator buffer data

Timeseries in DoEasy library (part 58): Timeseries of indicator buffer data

In conclusion of the topic of working with timeseries organise storage, search and sort of data stored in indicator buffers which will allow to further perform the analysis based on values of the indicators to be created on the library basis in programs. The general concept of all collection classes of the library allows to easily find necessary data in the corresponding collection. Respectively, the same will be possible in the class created today.