MQL4 and 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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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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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!
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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Neural networks made easy (Part 15): Data clustering using MQL5

Neural networks made easy (Part 15): Data clustering using MQL5

We continue to consider the clustering method. In this article, we will create a new CKmeans class to implement one of the most common k-means clustering methods. During tests, the model managed to identify about 500 patterns.
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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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Formulating Dynamic Multi-Pair EA (Part 3): Mean Reversion and Momentum Strategies

Formulating Dynamic Multi-Pair EA (Part 3): Mean Reversion and Momentum Strategies

In this article, we will explore the third part of our journey in formulating a Dynamic Multi-Pair Expert Advisor (EA), focusing specifically on integrating Mean Reversion and Momentum trading strategies. We will break down how to detect and act on price deviations from the mean (Z-score), and how to measure momentum across multiple forex pairs to determine trade direction.
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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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High frequency arbitrage trading system in Python using MetaTrader 5

High frequency arbitrage trading system in Python using MetaTrader 5

In this article, we will create an arbitration system that remains legal in the eyes of brokers, creates thousands of synthetic prices on the Forex market, analyzes them, and successfully trades for profit.
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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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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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From Novice to Expert: Creating a Liquidity Zone Indicator

From Novice to Expert: Creating a Liquidity Zone Indicator

The extent of liquidity zones and the magnitude of the breakout range are key variables that substantially affect the probability of a retest occurring. In this discussion, we outline the complete process for developing an indicator that incorporates these ratios.
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Population optimization algorithms: Grey Wolf Optimizer (GWO)

Population optimization algorithms: Grey Wolf Optimizer (GWO)

Let's consider one of the newest modern optimization algorithms - Grey Wolf Optimization. The original behavior on test functions makes this algorithm one of the most interesting among the ones considered earlier. This is one of the top algorithms for use in training neural networks, smooth functions with many variables.
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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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Data Science and Machine Learning (Part 23): Why LightGBM and XGBoost outperform a lot of AI models?

Data Science and Machine Learning (Part 23): Why LightGBM and XGBoost outperform a lot of AI models?

These advanced gradient-boosted decision tree techniques offer superior performance and flexibility, making them ideal for financial modeling and algorithmic trading. Learn how to leverage these tools to optimize your trading strategies, improve predictive accuracy, and gain a competitive edge in the financial markets.
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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.
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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Tips from a professional programmer (Part III): Logging. Connecting to the Seq log collection and analysis system

Tips from a professional programmer (Part III): Logging. Connecting to the Seq log collection and analysis system

Implementation of the Logger class for unifying and structuring messages which are printed to the Experts log. Connection to the Seq log collection and analysis system. Monitoring log messages online.
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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Graph Theory: Dijkstra's Algorithm Applied in Trading

Graph Theory: Dijkstra's Algorithm Applied in Trading

Dijkstra's algorithm, a classic shortest-path solution in graph theory, can optimize trading strategies by modeling market networks. Traders can use it to find the most efficient routes in the candlestick chart data.
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Creating a Dynamic Multi-Symbol, Multi-Period Relative Strength Indicator (RSI) Indicator Dashboard in MQL5

Creating a Dynamic Multi-Symbol, Multi-Period Relative Strength Indicator (RSI) Indicator Dashboard in MQL5

In this article, we develop a dynamic multi-symbol, multi-period RSI indicator dashboard in MQL5, providing traders real-time RSI values across various symbols and timeframes. The dashboard features interactive buttons, real-time updates, and color-coded indicators to help traders make informed decisions.
Graphics in DoEasy library (Part 93): Preparing functionality for creating composite graphical objects
Graphics in DoEasy library (Part 93): Preparing functionality for creating composite graphical objects

Graphics in DoEasy library (Part 93): Preparing functionality for creating composite graphical objects

In this article, I will start developing the functionality for creating composite graphical objects. The library will support creating composite graphical objects allowing those objects have any hierarchy of connections. I will prepare all the necessary classes for subsequent implementation of such objects.
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Neural networks made easy (Part 25): Practicing Transfer Learning

Neural networks made easy (Part 25): Practicing Transfer Learning

In the last two articles, we developed a tool for creating and editing neural network models. Now it is time to evaluate the potential use of Transfer Learning technology using practical examples.
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Building AI-Powered Trading Systems in MQL5 (Part 1): Implementing JSON Handling for AI APIs

Building AI-Powered Trading Systems in MQL5 (Part 1): Implementing JSON Handling for AI APIs

In this article, we develop a JSON parsing framework in MQL5 to handle data exchange for AI API integration, focusing on a JSON class for processing JSON structures. We implement methods to serialize and deserialize JSON data, supporting various data types like strings, numbers, and objects, essential for communicating with AI services like ChatGPT, enabling future AI-driven trading systems by ensuring accurate data handling and manipulation.
How we developed the MetaTrader Signals service and Social Trading
How we developed the MetaTrader Signals service and Social Trading

How we developed the MetaTrader Signals service and Social Trading

We continue to enhance the Signals service, improve the mechanisms, add new functions and fix flaws. The MetaTrader Signals Service of 2012 and the current MetaTrader Signals Service are like two completely different services. Currently, we are implementing A Virtual Hosting Cloud service which consists of a network of servers to support specific versions of the MetaTrader client terminal.
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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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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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News Trading Made Easy (Part 1): Creating a Database

News Trading Made Easy (Part 1): Creating a Database

News trading can be complicated and overwhelming, in this article we will go through steps to obtain news data. Additionally we will learn about the MQL5 Economic Calendar and what it has to offer.
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Developing Trend Trading Strategies Using Machine Learning

Developing Trend Trading Strategies Using Machine Learning

This study introduces a novel methodology for the development of trend-following trading strategies. This section describes the process of annotating training data and using it to train classifiers. This process yields fully operational trading systems designed to run on MetaTrader 5.
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How to build and optimize a volatility-based trading system (Chaikin Volatility - CHV)

How to build and optimize a volatility-based trading system (Chaikin Volatility - CHV)

In this article, we will provide another volatility-based indicator named Chaikin Volatility. We will understand how to build a custom indicator after identifying how it can be used and constructed. We will share some simple strategies that can be used and then test them to understand which one can be better.
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The MQL5 Standard Library Explorer (Part 1): Introduction with CTrade, CiMA, and CiATR

The MQL5 Standard Library Explorer (Part 1): Introduction with CTrade, CiMA, and CiATR

The MQL5 Standard Library plays a vital role in developing trading algorithms for MetaTrader 5. In this discussion series, our goal is to master its application to simplify the creation of efficient trading tools for MetaTrader 5. These tools include custom Expert Advisors, indicators, and other utilities. We begin today by developing a trend-following Expert Advisor using the CTrade, CiMA, and CiATR classes. This is an especially important topic for everyone—whether you are a beginner or an experienced developer. Join this discussion to discover more.
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Population optimization algorithms: Harmony Search (HS)

Population optimization algorithms: Harmony Search (HS)

In the current article, I will study and test the most powerful optimization algorithm - harmonic search (HS) inspired by the process of finding the perfect sound harmony. So what algorithm is now the leader in our rating?
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Econometric tools for forecasting volatility: GARCH model

Econometric tools for forecasting volatility: GARCH model

The article describes the properties of the non-linear model of conditional heteroscedasticity (GARCH). The iGARCH indicator has been built on its basis for predicting volatility one step ahead. The ALGLIB numerical analysis library is used to estimate the model parameters.
Nikolay Ivanov (Techno): "What is important for programs is the accuracy of their algorithms"
Nikolay Ivanov (Techno): "What is important for programs is the accuracy of their algorithms"

Nikolay Ivanov (Techno): "What is important for programs is the accuracy of their algorithms"

A programmer from Krasnoyarsk Nikolay Ivanov (Techno) is a leader among the developers in terms of the number of completed orders - he has implemented already more than 200 applications in the Jobs service. In this interview, he is talking about the Jobs service, its specific features and challengers faced by programmers.
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Neural networks made easy (Part 76): Exploring diverse interaction patterns with Multi-future Transformer

Neural networks made easy (Part 76): Exploring diverse interaction patterns with Multi-future Transformer

This article continues the topic of predicting the upcoming price movement. I invite you to get acquainted with the Multi-future Transformer architecture. Its main idea is to decompose the multimodal distribution of the future into several unimodal distributions, which allows you to effectively simulate various models of interaction between agents on the scene.
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MQL5 Cookbook — Macroeconomic events database

MQL5 Cookbook — Macroeconomic events database

The article discusses the possibilities of handling databases based on the SQLite engine. The CDatabase class has been formed for convenience and efficient use of OOP principles. It is subsequently involved in the creation and management of the database of macroeconomic events. The article provides the examples of using multiple methods of the CDatabase class.
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Neural Networks in Trading: Parameter-Efficient Transformer with Segmented Attention (Final Part)

Neural Networks in Trading: Parameter-Efficient Transformer with Segmented Attention (Final Part)

In the previous work, we discussed the theoretical aspects of the PSformer framework, which includes two major innovations in the classical Transformer architecture: the Parameter Shared (PS) mechanism and attention to spatio-temporal segments (SegAtt). In this article, we continue the work we started on implementing the proposed approaches using MQL5.
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Developing a trading Expert Advisor from scratch (Part 9): A conceptual leap (II)

Developing a trading Expert Advisor from scratch (Part 9): A conceptual leap (II)

In this article, we will place Chart Trade in a floating window. In the previous part, we created a basic system which enables the use of templates within a floating window.
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Implementing the Generalized Hurst Exponent and the Variance Ratio test in MQL5

Implementing the Generalized Hurst Exponent and the Variance Ratio test in MQL5

In this article, we investigate how the Generalized Hurst Exponent and the Variance Ratio test can be utilized to analyze the behaviour of price series in MQL5.
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DoEasy. Controls (Part 6): Panel control, auto resizing the container to fit inner content

DoEasy. Controls (Part 6): Panel control, auto resizing the container to fit inner content

In the article, I will continue my work on the Panel WinForms object and implement its auto resizing to fit the general size of Dock objects located inside the panel. Besides, I will add the new properties to the Symbol library object.
MT4TerminalSync - System for the Synchronization of MetaTrader 4 Terminals
MT4TerminalSync - System for the Synchronization of MetaTrader 4 Terminals

MT4TerminalSync - System for the Synchronization of MetaTrader 4 Terminals

This article is devoted to the topic "Widening possibilities of MQL4 programs by using functions of operating systems and other means of program development". The article describes an example of a program system that implements the task of the synchronization of several terminal copies based on a single source template.