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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Marvel Your MQL5 Customers with a Usable Cocktail of Technologies!
Marvel Your MQL5 Customers with a Usable Cocktail of Technologies!

Marvel Your MQL5 Customers with a Usable Cocktail of Technologies!

MQL5 provides programmers with a very complete set of functions and object-oriented API thanks to which they can do everything they want within the MetaTrader environment. However, Web Technology is an extremely versatile tool nowadays that may come to the rescue in some situations when you need to do something very specific, want to marvel your customers with something different or simply you do not have enough time to master a specific part of MT5 Standard Library. Today's exercise walks you through a practical example about how you can manage your development time at the same time as you also create an amazing tech cocktail.
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Price Action Analysis Toolkit Development (Part 27): Liquidity Sweep With MA Filter Tool

Price Action Analysis Toolkit Development (Part 27): Liquidity Sweep With MA Filter Tool

Understanding the subtle dynamics behind price movements can give you a critical edge. One such phenomenon is the liquidity sweep, a deliberate strategy that large traders, especially institutions, use to push prices through key support or resistance levels. These levels often coincide with clusters of retail stop-loss orders, creating pockets of liquidity that big players can exploit to enter or exit sizeable positions with minimal slippage.
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How to create a custom True Strength Index indicator using MQL5

How to create a custom True Strength Index indicator using MQL5

Here is a new article about how to create a custom indicator. This time we will work with the True Strength Index (TSI) and will create an Expert Advisor based on it.
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An example of how to ensemble ONNX models in MQL5

An example of how to ensemble ONNX models in MQL5

ONNX (Open Neural Network eXchange) is an open format built to represent neural networks. In this article, we will show how to use two ONNX models in one Expert Advisor simultaneously.
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Backpropagation Neural Networks using MQL5 Matrices

Backpropagation Neural Networks using MQL5 Matrices

The article describes the theory and practice of applying the backpropagation algorithm in MQL5 using matrices. It provides ready-made classes along with script, indicator and Expert Advisor examples.
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Using PatchTST Machine Learning Algorithm for Predicting Next 24 Hours of Price Action

Using PatchTST Machine Learning Algorithm for Predicting Next 24 Hours of Price Action

In this article, we apply a relatively complex neural network algorithm released in 2023 called PatchTST for predicting the price action for the next 24 hours. We will use the official repository, make slight modifications, train a model for EURUSD, and apply it to making future predictions both in Python and MQL5.
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Build Self Optimizing Expert Advisors in MQL5 (Part 6): Self Adapting Trading Rules (II)

Build Self Optimizing Expert Advisors in MQL5 (Part 6): Self Adapting Trading Rules (II)

This article explores optimizing RSI levels and periods for better trading signals. We introduce methods to estimate optimal RSI values and automate period selection using grid search and statistical models. Finally, we implement the solution in MQL5 while leveraging Python for analysis. Our approach aims to be pragmatic and straightforward to help you solve potentially complicated problems, with simplicity.
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Developing a Replay System — Market simulation (Part 02): First experiments (II)

Developing a Replay System — Market simulation (Part 02): First experiments (II)

This time, let's try a different approach to achieve the 1 minute goal. However, this task is not as simple as one might think.
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Multiple indicators on one chart (Part 03): Developing definitions for users

Multiple indicators on one chart (Part 03): Developing definitions for users

Today we will update the functionality of the indicator system for the first time. In the previous article within the "Multiple indicators on one chart" we considered the basic code which allows using more than one indicator in a chart subwindow. But what was presented was just the starting base of a much larger system.
Using Assertions in MQL5 Programs
Using Assertions in MQL5 Programs

Using Assertions in MQL5 Programs

This article covers the use of assertions in MQL5 language. It provides two examples of the assertion mechanism and some general guidance for implementing assertions.
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Price Action Analysis Toolkit Development (Part 19): ZigZag Analyzer

Price Action Analysis Toolkit Development (Part 19): ZigZag Analyzer

Every price action trader manually uses trendlines to confirm trends and spot potential turning or continuation levels. In this series on developing a price action analysis toolkit, we introduce a tool focused on drawing slanted trendlines for easy market analysis. This tool simplifies the process for traders by clearly outlining key trends and levels essential for effective price action evaluation.
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Experiments with neural networks (Part 5): Normalizing inputs for passing to a neural network

Experiments with neural networks (Part 5): Normalizing inputs for passing to a neural network

Neural networks are an ultimate tool in traders' toolkit. Let's check if this assumption is true. MetaTrader 5 is approached as a self-sufficient medium for using neural networks in trading. A simple explanation is provided.
Prices in DoEasy library (part 59): Object to store data of one tick
Prices in DoEasy library (part 59): Object to store data of one tick

Prices in DoEasy library (part 59): Object to store data of one tick

From this article on, start creating library functionality to work with price data. Today, create an object class which will store all price data which arrived with yet another tick.
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Master MQL5 from beginner to pro (Part II): Basic data types and use of variable

Master MQL5 from beginner to pro (Part II): Basic data types and use of variable

This is a continuation of the series for beginners. In this article, we'll look at how to create constants and variables, write dates, colors, and other useful data. We will learn how to create enumerations like days of the week or line styles (solid, dotted, etc.). Variables and expressions are the basis of programming. They are definitely present in 99% of programs, so understanding them is critical. Therefore, if you are new to programming, this article can be very useful for you. Required programming knowledge level: very basic, within the limits of my previous article (see the link at the beginning).
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ALGLIB numerical analysis library in MQL5

ALGLIB numerical analysis library in MQL5

The article takes a quick look at the ALGLIB 3.19 numerical analysis library, its applications and new algorithms that can improve the efficiency of financial data analysis.
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Developing a trading Expert Advisor from scratch (Part 28): Towards the future (III)

Developing a trading Expert Advisor from scratch (Part 28): Towards the future (III)

There is still one task which our order system is not up to, but we will FINALLY figure it out. The MetaTrader 5 provides a system of tickets which allows creating and correcting order values. The idea is to have an Expert Advisor that would make the same ticket system faster and more efficient.
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Moral expectation in trading

Moral expectation in trading

This article is about moral expectation. We will look at several examples of its use in trading, as well as the results that can be achieved with its help.
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Neural networks made easy (Part 16): Practical use of clustering

Neural networks made easy (Part 16): Practical use of clustering

In the previous article, we have created a class for data clustering. In this article, I want to share variants of the possible application of obtained results in solving practical trading tasks.
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Market Profile indicator

Market Profile indicator

In this article, we will consider Market Profile indicator. We will find out what lies behind this name, try to understand its operation principles and have a look at its terminal version (MarketProfile).
Better Programmer (Part 03): Give Up doing these 5 things to become a successful MQL5 Programmer
Better Programmer (Part 03): Give Up doing these 5 things to become a successful MQL5 Programmer

Better Programmer (Part 03): Give Up doing these 5 things to become a successful MQL5 Programmer

This is the must-read article for anyone wanting to improve their programming career. This article series is aimed at making you the best programmer you can possibly be, no matter how experienced you are. The discussed ideas work for MQL5 programming newbies as well as professionals.
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Introduction to MQL5 (Part 12): A Beginner's Guide to Building Custom Indicators

Introduction to MQL5 (Part 12): A Beginner's Guide to Building Custom Indicators

Learn how to build a custom indicator in MQL5. With a project-based approach. This beginner-friendly guide covers indicator buffers, properties, and trend visualization, allowing you to learn step-by-step.
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Data label for time series  mining(Part 1):Make a dataset with trend markers through the EA operation chart

Data label for time series mining(Part 1):Make a dataset with trend markers through the EA operation chart

This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy of our model, and even help the model make a qualitative leap!
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Data Science and Machine Learning (Part 12): Can Self-Training Neural Networks Help You Outsmart the Stock Market?

Data Science and Machine Learning (Part 12): Can Self-Training Neural Networks Help You Outsmart the Stock Market?

Are you tired of constantly trying to predict the stock market? Do you wish you had a crystal ball to help you make more informed investment decisions? Self-trained neural networks might be the solution you've been looking for. In this article, we explore whether these powerful algorithms can help you "ride the wave" and outsmart the stock market. By analyzing vast amounts of data and identifying patterns, self-trained neural networks can make predictions that are often more accurate than human traders. Discover how you can use this cutting-edge technology to maximize your profits and make smarter investment decisions.
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MQL5 Wizard Techniques you should know (Part 48): Bill Williams Alligator

MQL5 Wizard Techniques you should know (Part 48): Bill Williams Alligator

The Alligator Indicator, which was the brain child of Bill Williams, is a versatile trend identification indicator that yields clear signals and is often combined with other indicators. The MQL5 wizard classes and assembly allow us to test a variety of signals on a pattern basis, and so we consider this indicator as well.
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DoEasy. Controls (Part 3): Creating bound controls

DoEasy. Controls (Part 3): Creating bound controls

In this article, I will create subordinate controls bound to the base element. The development will be performed using the base control functionality. In addition, I will tinker with the graphical element shadow object a bit since it still suffers from some logic errors when applied to any of the objects capable of having a shadow.
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Neural networks made easy (Part 67): Using past experience to solve new tasks

Neural networks made easy (Part 67): Using past experience to solve new tasks

In this article, we continue discussing methods for collecting data into a training set. Obviously, the learning process requires constant interaction with the environment. However, situations can be different.
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MQL5 Wizard techniques you should know (Part 03): Shannon's Entropy

MQL5 Wizard techniques you should know (Part 03): Shannon's Entropy

Todays trader is a philomath who is almost always 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. These series of articles will proposition that the MQL5 wizard should be a mainstay for traders.
New Opportunities with MetaTrader 5
New Opportunities with MetaTrader 5

New Opportunities with MetaTrader 5

MetaTrader 4 gained its popularity with traders from all over the world, and it seemed like nothing more could be wished for. With its high processing speed, stability, wide array of possibilities for writing indicators, Expert Advisors, and informatory-trading systems, and the ability to chose from over a hundred different brokers, - the terminal greatly distinguished itself from the rest. But time doesn’t stand still, and we find ourselves facing a choice of MetaTrade 4 or MetaTrade 5. In this article, we will describe the main differences of the 5th generation terminal from our current favor.
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Developing an Expert Advisor from scratch (Part 30): CHART TRADE as an indicator?

Developing an Expert Advisor from scratch (Part 30): CHART TRADE as an indicator?

Today we are going to use Chart Trade again, but this time it will be an on-chart indicator which may or may not be present on the chart.
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Canvas based indicators: Filling channels with transparency

Canvas based indicators: Filling channels with transparency

In this article I'll introduce a method for creating custom indicators whose drawings are made using the class CCanvas from standard library and see charts properties for coordinates conversion. I'll approach specially indicators which need to fill the area between two lines using transparency.
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Neural networks made easy (Part 21): Variational autoencoders (VAE)

Neural networks made easy (Part 21): Variational autoencoders (VAE)

In the last article, we got acquainted with the Autoencoder algorithm. Like any other algorithm, it has its advantages and disadvantages. In its original implementation, the autoenctoder is used to separate the objects from the training sample as much as possible. This time we will talk about how to deal with some of its disadvantages.
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Advanced resampling and selection of CatBoost models by brute-force method

Advanced resampling and selection of CatBoost models by brute-force method

This article describes one of the possible approaches to data transformation aimed at improving the generalizability of the model, and also discusses sampling and selection of CatBoost models.
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Creating a ticker tape panel: Basic version

Creating a ticker tape panel: Basic version

Here I will show how to create screens with price tickers which are usually used to display quotes on the exchange. I will do it by only using MQL5, without using complex external programming.
Technical Analysis: What Do We Analyze?
Technical Analysis: What Do We Analyze?

Technical Analysis: What Do We Analyze?

This article tries to analyze several peculiarities of representation of quotes available in the MetaTrader client terminal. The article is general, it doesn't concern programming.
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Data Science and Machine Learning (Part 07): Polynomial Regression

Data Science and Machine Learning (Part 07): Polynomial Regression

Unlike linear regression, polynomial regression is a flexible model aimed to perform better at tasks the linear regression model could not handle, Let's find out how to make polynomial models in MQL5 and make something positive out of it.
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Category Theory in MQL5 (Part 14): Functors with Linear-Orders

Category Theory in MQL5 (Part 14): Functors with Linear-Orders

This article which is part of a broader series on Category Theory implementation in MQL5, delves into Functors. We examine how a Linear Order can be mapped to a set, thanks to Functors; by considering two sets of data that one would typically dismiss as having any connection.
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Timeseries in DoEasy library (part 54): Descendant classes of abstract base indicator

Timeseries in DoEasy library (part 54): Descendant classes of abstract base indicator

The article considers creation of classes of descendant objects of base abstract indicator. Such objects will provide access to features of creating indicator EAs, collecting and getting data value statistics of various indicators and prices. Also, create indicator object collection from which getting access to properties and data of each indicator created in the program will be possible.
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Automating Trading Strategies in MQL5 (Part 23): Zone Recovery with Trailing and Basket Logic

Automating Trading Strategies in MQL5 (Part 23): Zone Recovery with Trailing and Basket Logic

In this article, we enhance our Zone Recovery System by introducing trailing stops and multi-basket trading capabilities. We explore how the improved architecture uses dynamic trailing stops to lock in profits and a basket management system to handle multiple trade signals efficiently. Through implementation and backtesting, we demonstrate a more robust trading system tailored for adaptive market performance.
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Automating Trading Strategies in MQL5 (Part 20): Multi-Symbol Strategy Using CCI and AO

Automating Trading Strategies in MQL5 (Part 20): Multi-Symbol Strategy Using CCI and AO

In this article, we create a multi-symbol trading strategy using CCI and AO indicators to detect trend reversals. We cover its design, MQL5 implementation, and backtesting process. The article concludes with tips for performance improvement.
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Experiments with neural networks (Part 2): Smart neural network optimization

Experiments with neural networks (Part 2): Smart neural network optimization

In this article, I will use experimentation and non-standard approaches to develop a profitable trading system and check whether neural networks can be of any help for traders. MetaTrader 5 as a self-sufficient tool for using neural networks in trading.