MQL5 Programming Articles
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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Using the TesterWithdrawal() Function for Modeling the Withdrawals of Profit
This article describes the usage of the TesterWithDrawal() function for estimating risks in trade systems which imply the withdrawing of a certain part of assets during their operation. In addition, it describes the effect of this function on the algorithm of calculation of the drawdown of equity in the strategy tester. This function is useful when optimizing parameter of your Expert Advisors.
Automating Trading Strategies in MQL5 (Part 25): Trendline Trader with Least Squares Fit and Dynamic Signal Generation
In this article, we develop a trendline trader program that uses least squares fit to detect support and resistance trendlines, generating dynamic buy and sell signals based on price touches and open positions based on generated signals.
Interview with Irina Korobeinikova (irishka.rf)
Having a female member on the MQL5.community is rare. This interview was inspired by a one of a kind case. Irina Korobeinikova (irishka.rf) is a fifteen-year-old programmer from Izhevsk. She is currently the only girl who actively participates in the "Jobs" service and is featured on the Top Developers list.
How to Secure Your Expert Advisor While Trading on the Moscow Exchange
The article delves into the trading methods ensuring the security of trading operations at the stock and low-liquidity markets through the example of Moscow Exchange's Derivatives Market. It brings practical approach to the trading theory described in the article "Principles of Exchange Pricing through the Example of Moscow Exchange's Derivatives Market".
Drawing Channels - Inside and Outside View
I guess it won't be an exaggeration, if I say the channels are the most popular tool for the analysis of market and making trade decisions after the moving averages. Without diving deeply into the mass of trade strategies that use channels and their components, we are going to discuss the mathematical basis and the practical implementation of an indicator, which draws a channel determined by three extremums on the screen of the client terminal.
Video: Simple automated trading – How to create a simple Expert Advisor with MQL5
The majority of students in my courses felt that MQL5 was really difficult to understand. In addition to this, they were searching for a straightforward method to automate a few processes. Find out how to begin working with MQL5 right now by reading the information contained in this article. Even if you have never done any form of programming before. And even in the event that you are unable to comprehend the previous illustrations that you have observed.
Learn how to design a trading system by Awesome Oscillator
In this new article in our series, we will learn about a new technical tool that may be useful in our trading. It is the Awesome Oscillator (AO) indicator. We will learn how to design a trading system by this indicator.
Neural Networks in Trading: A Multi-Agent Self-Adaptive Model (MASA)
I invite you to get acquainted with the Multi-Agent Self-Adaptive (MASA) framework, which combines reinforcement learning and adaptive strategies, providing a harmonious balance between profitability and risk management in turbulent market conditions.
Developing a cross-platform grider EA (part III): Correction-based grid with martingale
In this article, we will make an attempt to develop the best possible grid-based EA. As usual, this will be a cross-platform EA capable of working both with MetaTrader 4 and MetaTrader 5. The first EA was good enough, except that it could not make a profit over a long period of time. The second EA could work at intervals of more than several years. Unfortunately, it was unable to yield more than 50% of profit per year with a maximum drawdown of less than 50%.
Engineering Trading Discipline into Code (Part 1): Creating Structural Discipline in Live Trading with MQL5
Discipline becomes reliable when it is produced by system design, not willpower. Using MQL5, the article implements real-time constraints—trade-frequency caps and daily equity-based stops—that monitor behavior and trigger actions on breach. Readers gain a practical template for governance layers that stabilize execution under market pressure.
LifeHack for trader: four backtests are better than one
Before the first single test, every trader faces the same question — "Which of the four modes to use?" Each of the provided modes has its advantages and features, so we will do it the easy way - run all four modes at once with a single button! The article shows how to use the Win API and a little magic to see all four testing chart at the same time.
Python + MetaTrader 5: Fast Research Framework for Data, Features, and Prototypes
The article demonstrates how Python and MetaTrader 5 integration combines research flexibility and trade execution into a single workflow. Python is used for data analysis, feature selection and model training, while MetaTrader 5 is used for testing and trading automation. This approach simplifies the transfer of solutions into practice, increases reproducibility, and makes the development of trading systems faster and more structured.
Data Science and Machine Learning — Neural Network (Part 02): Feed forward NN Architectures Design
There are minor things to cover on the feed-forward neural network before we are through, the design being one of them. Let's see how we can build and design a flexible neural network to our inputs, the number of hidden layers, and the nodes for each of the network.
Automating Trading Strategies in MQL5 (Part 8): Building an Expert Advisor with Butterfly Harmonic Patterns
In this article, we build an MQL5 Expert Advisor to detect Butterfly harmonic patterns. We identify pivot points and validate Fibonacci levels to confirm the pattern. We then visualize the pattern on the chart and automatically execute trades when confirmed.
Gradient Boosting (CatBoost) in the development of trading systems. A naive approach
Training the CatBoost classifier in Python and exporting the model to mql5, as well as parsing the model parameters and a custom strategy tester. The Python language and the MetaTrader 5 library are used for preparing the data and for training the model.
The Player of Trading Based on Deal History
The player of trading. Only four words, no explanation is needed. Thoughts about a small box with buttons come to your mind. Press one button - it plays, move the lever - the playback speed changes. In reality, it is pretty similar. In this article, I want to show my development that plays trade history almost like it is in real time. The article covers some nuances of OOP, working with indicators and managing charts.
Neural networks made easy (Part 12): Dropout
As the next step in studying neural networks, I suggest considering the methods of increasing convergence during neural network training. There are several such methods. In this article we will consider one of them entitled Dropout.
Price Action Analysis Toolkit Development (Part 36): Unlocking Direct Python Access to MetaTrader 5 Market Streams
Harness the full potential of your MetaTrader 5 terminal by leveraging Python’s data-science ecosystem and the official MetaTrader 5 client library. This article demonstrates how to authenticate and stream live tick and minute-bar data directly into Parquet storage, apply sophisticated feature engineering with Ta and Prophet, and train a time-aware Gradient Boosting model. We then deploy a lightweight Flask service to serve trade signals in real time. Whether you’re building a hybrid quant framework or enhancing your EA with machine learning, you’ll walk away with a robust, end-to-end pipeline for data-driven algorithmic trading.
Graphical Interfaces VII: The Tabs Control (Chapter 2)
The first chapter of seventh part introduced three classes of controls for creating tables: text label table (CLabelsTable), edit box table (CTable) and rendered table (CCanvasTable). In this article (chapter two) we are going to consider the Tabs control.
Library for easy and quick development of MetaTrader programs (part XVI): Symbol collection events
In this article, we will create a new base class of all library objects adding the event functionality to all its descendants and develop the class for tracking symbol collection events based on the new base class. We will also change account and account event classes for developing the new base object functionality.
Universal Regression Model for Market Price Prediction
The market price is formed out of a stable balance between demand and supply which, in turn, depend on a variety of economic, political and psychological factors. Differences in nature as well as causes of influence of these factors make it difficult to directly consider all the components. This article sets forth an attempt to predict the market price on the basis of an elaborated regression model.
Price Action Analysis Toolkit Development (Part 44): Building a VWMA Crossover Signal EA in MQL5
This article introduces a VWMA crossover signal tool for MetaTrader 5, designed to help traders identify potential bullish and bearish reversals by combining price action with trading volume. The EA generates clear buy and sell signals directly on the chart, features an informative panel, and allows for full user customization, making it a practical addition to your trading strategy.
Social Trading. Can a profitable signal be made even better?
Most subscribers choose a trade signal by the beauty of the balance curve and by the number of subscribers. This is why many today's providers care of beautiful statistics rather than of real signal quality, often playing with lot sizes and artificially reducing the balance curve to an ideal appearance. This paper deals with the reliability criteria and the methods a provider may use to enhance its signal quality. An exemplary analysis of a specific signal history is presented, as well as methods that would help a provider to make it more profitable and less risky.
Graphics in DoEasy library (Part 76): Form object and predefined color themes
In this article, I will describe the concept of building various library GUI design themes, create the Form object, which is a descendant of the graphical element class object, and prepare data for creating shadows of the library graphical objects, as well as for further development of the functionality.
Installing MetaTrader 5 and Other MetaQuotes Apps on HarmonyOS NEXT
Easily install MetaTrader 5 and other MetaQuotes apps on HarmonyOS NEXT devices using DroiTong. A detailed step-by-step guide for your phone or laptop.
MQL5 Cookbook: ОСО Orders
Any trader's trading activity involves various mechanisms and interrelationships including relations among orders. This article suggests a solution of OCO orders processing. Standard library classes are extensively involved, as well as new data types are created herein.
Creating an Indicator with Graphical Control Options
Those who are familiar with market sentiments, know the MACD indicator (its full name is Moving Average Convergence/Divergence) - the powerful tool for analyzing the price movement, used by traders from the very first moments of appearance of the computer analysis methods. In this article we'll consider possible modifications of MACD and implement them in one indicator with the possibility to graphically switch between the modifications.
Simple Mean Reversion Trading Strategy
Mean reversion is a type of contrarian trading where the trader expects the price to return to some form of equilibrium which is generally measured by a mean or another central tendency statistic.
Statistical Carry Trade Strategy
An algorithm of statistical protection of open positive swap positions from unwanted price movements. This article features a variant of the carry trade protection strategy that allows to compensate for potential risk of the price movement in the direction opposite to that of the open position.
How to Create an Interactive MQL5 Dashboard/Panel Using the Controls Class (Part 1): Setting Up the Panel
In this article, we create an interactive trading dashboard using the Controls class in MQL5, designed to streamline trading operations. The panel features a title, navigation buttons for Trade, Close, and Information, and specialized action buttons for executing trades and managing positions. By the end of the article, you will have a foundational panel ready for further enhancements in future installments.
Developing a trading Expert Advisor from scratch (Part 7): Adding Volume at Price (I)
This is one of the most powerful indicators currently existing. Anyone who trades trying to have a certain degree of confidence must have this indicator on their chart. Most often the indicator is used by those who prefer “tape reading” while trading. Also, this indicator can be utilized by those who use only Price Action while trading.
Library for easy and quick development of MetaTrader programs (part XII): Account object class and collection of account objects
In the previous article, we defined position closure events for MQL4 in the library and got rid of the unused order properties. Here we will consider the creation of the Account object, develop the collection of account objects and prepare the functionality for tracking account events.
Visualizing trading strategy optimization in MetaTrader 5
The article implements an MQL application with a graphical interface for extended visualization of the optimization process. The graphical interface applies the last version of EasyAndFast library. Many users may ask why they need graphical interfaces in MQL applications. This article demonstrates one of multiple cases where they can be useful for traders.
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.
Building AI-Powered Trading Systems in MQL5 (Part 7): Further Modularization and Automated Trading
In this article, we enhance the AI-powered trading system's modularity by separating UI components into a dedicated include file. The system now automates trade execution based on AI-generated signals, parsing JSON responses for BUY/SELL/NONE with entry/SL/TP, visualizing patterns like engulfing or divergences on charts with arrows, lines, and labels, and optional auto-signal checks on new bars.
Neural networks made easy (Part 8): Attention mechanisms
In previous articles, we have already tested various options for organizing neural networks. We also considered convolutional networks borrowed from image processing algorithms. In this article, I suggest considering Attention Mechanisms, the appearance of which gave impetus to the development of language models.
Learn how to design a trading system by VIDYA
Welcome to a new article from our series about learning how to design a trading system by the most popular technical indicators, in this article we will learn about a new technical tool and learn how to design a trading system by Variable Index Dynamic Average (VIDYA).
The Liquidity Grab Trading Strategy
The liquidity grab trading strategy is a key component of Smart Money Concepts (SMC), which seeks to identify and exploit the actions of institutional players in the market. It involves targeting areas of high liquidity, such as support or resistance zones, where large orders can trigger price movements before the market resumes its trend. This article explains the concept of liquidity grab in detail and outlines the development process of the liquidity grab trading strategy Expert Advisor in MQL5.
Price Action Analysis Toolkit Development (Part 53): Pattern Density Heatmap for Support and Resistance Zone Discovery
This article introduces the Pattern Density Heatmap, a price‑action mapping tool that transforms repeated candlestick pattern detections into statistically significant support and resistance zones. Rather than treating each signal in isolation, the EA aggregates detections into fixed price bins, scores their density with optional recency weighting, and confirms levels against higher‑timeframe data. The resulting heatmap reveals where the market has historically reacted—levels that can be used proactively for trade timing, risk management, and strategy confidence across any trading style.
Graphical Interfaces X: Time control, List of checkboxes control and table sorting (build 6)
Development of the library for creating graphical interfaces continues. The Time and List of checkboxes controls will be covered this time. In addition, the CTable class now provides the ability to sort data in ascending or descending order.