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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Interview with Ruslan Ziyatdinov (ATC 2012)

Interview with Ruslan Ziyatdinov (ATC 2012)

The Championship keeps providing us with new discoveries, as well as new interesting Participants and unusual ideas implemented in the competition trading robots. While interviewing Ruslan Ziyatdinov (rusland1962), we learned about his simple approach to trading and found out why it is better to trade less frequently.
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Multilayer perceptron and backpropagation algorithm (Part 3): Integration with the Strategy Tester - Overview (I).

The multilayer perceptron is an evolution of the simple perceptron which can solve non-linear separable problems. Together with the backpropagation algorithm, this neural network can be effectively trained. In Part 3 of the Multilayer Perceptron and Backpropagation series, we'll see how to integrate this technique into the Strategy Tester. This integration will allow the use of complex data analysis aimed at making better decisions to optimize your trading strategies. In this article, we will discuss the advantages and problems of this technique.
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Introduction to MQL5 (Part 2): Navigating Predefined Variables, Common Functions, and Control Flow Statements

Embark on an illuminating journey with Part Two of our MQL5 series. These articles are not just tutorials, they're doorways to an enchanted realm where programming novices and wizards alike unite. What makes this journey truly magical? Part Two of our MQL5 series stands out with its refreshing simplicity, making complex concepts accessible to all. Engage with us interactively as we answer your questions, ensuring an enriching and personalized learning experience. Let's build a community where understanding MQL5 is an adventure for everyone. Welcome to the enchantment!
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Creating a Trading Administrator Panel in MQL5 (Part I): Building a Messaging Interface

This article discusses the creation of a Messaging Interface for MetaTrader 5, aimed at System Administrators, to facilitate communication with other traders directly within the platform. Recent integrations of social platforms with MQL5 allow for quick signal broadcasting across different channels. Imagine being able to validate sent signals with just a click—either "YES" or "NO." Read on to learn more.
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Developing a Replay System — Market simulation (Part 05): Adding Previews

We have managed to develop a way to implement the market replay system in a realistic and accessible way. Now let's continue our project and add data to improve the replay behavior.
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Neural networks made easy (Part 53): Reward decomposition

We have already talked more than once about the importance of correctly selecting the reward function, which we use to stimulate the desired behavior of the Agent by adding rewards or penalties for individual actions. But the question remains open about the decryption of our signals by the Agent. In this article, we will talk about reward decomposition in terms of transmitting individual signals to the trained Agent.
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Creating an MQL5-Telegram Integrated Expert Advisor (Part 3): Sending Chart Screenshots with Captions from MQL5 to Telegram

In this article, we create an MQL5 Expert Advisor that encodes chart screenshots as image data and sends them to a Telegram chat via HTTP requests. By integrating photo encoding and transmission, we enhance the existing MQL5-Telegram system with visual trading insights directly within Telegram.
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Wrapping ONNX models in classes

Object-oriented programming enables creation of a more compact code that is easy to read and modify. Here we will have a look at the example for three ONNX models.
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Developing a multi-currency Expert Advisor (Part 13): Automating the second stage — selection into groups

Developing a multi-currency Expert Advisor (Part 13): Automating the second stage — selection into groups

We have already implemented the first stage of the automated optimization. We perform optimization for different symbols and timeframes according to several criteria and store information about the results of each pass in the database. Now we are going to select the best groups of parameter sets from those found at the first stage.
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Forex spread trading using seasonality

Forex spread trading using seasonality

The article examines the possibilities of generating and providing reporting data on the use of the seasonality factor when trading spreads on Forex.
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Developing a trading Expert Advisor from scratch (Part 23): New order system (VI)

Developing a trading Expert Advisor from scratch (Part 23): New order system (VI)

We will make the order system more flexible. Here we will consider changes to the code that will make it more flexible, which will allow us to change position stop levels much faster.
Testing Visualization: Account State Charts

Testing Visualization: Account State Charts

Enjoy the process of testing with charts, displaying the balance - now all the necessary information is always in view!
Creation of an Automated Trading System

Creation of an Automated Trading System

You must admit that it sounds alluringly - you become a fortunate possessor of a program that can develop for you a profitable automated trading system (ATC) within a few minutes. All you need is to enter desirable inputs and press Enter. And - here you are, take your ATC tested and having positive expected payoff. Where thousands of people spend thousands of hours on developing that very unique ATC, which will "wine and dine", these statements soundб to put it mildly, very hollow. On the one hand, this really looks a little larger than life... However, to my mind, this problem can be solved.
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Trading with the MQL5 Economic Calendar (Part 6): Automating Trade Entry with News Event Analysis and Countdown Timers

Trading with the MQL5 Economic Calendar (Part 6): Automating Trade Entry with News Event Analysis and Countdown Timers

In this article, we implement automated trade entry using the MQL5 Economic Calendar by applying user-defined filters and time offsets to identify qualifying news events. We compare forecast and previous values to determine whether to open a BUY or SELL trade. Dynamic countdown timers display the remaining time until news release and reset automatically after a trade.
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Neural networks made easy (Part 20): Autoencoders

Neural networks made easy (Part 20): Autoencoders

We continue to study unsupervised learning algorithms. Some readers might have questions regarding the relevance of recent publications to the topic of neural networks. In this new article, we get back to studying neural networks.
Graphical Interfaces X: Updates for the Rendered table and code optimization (build 10)

Graphical Interfaces X: Updates for the Rendered table and code optimization (build 10)

We continue to complement the Rendered table (CCanvasTable) with new features. The table will now have: highlighting of the rows when hovered; ability to add an array of icons for each cell and a method for switching them; ability to set or modify the cell text during the runtime, and more.
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Trading with the MQL5 Economic Calendar (Part 9): Elevating News Interaction with a Dynamic Scrollbar and Polished Display

Trading with the MQL5 Economic Calendar (Part 9): Elevating News Interaction with a Dynamic Scrollbar and Polished Display

In this article, we enhance the MQL5 Economic Calendar with a dynamic scrollbar for intuitive news navigation. We ensure seamless event display and efficient updates. We validate the responsive scrollbar and polished dashboard through testing.
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Integrate Your Own LLM into EA (Part 5): Develop and Test Trading Strategy with LLMs (III) – Adapter-Tuning

Integrate Your Own LLM into EA (Part 5): Develop and Test Trading Strategy with LLMs (III) – Adapter-Tuning

With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to their needs, deploy them locally, and then apply them to algorithmic trading. This series of articles will take a step-by-step approach to achieve this goal.
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Integrate Your Own LLM into EA (Part 2): Example of Environment Deployment

Integrate Your Own LLM into EA (Part 2): Example of Environment Deployment

With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to their needs, deploy them locally, and then apply them to algorithmic trading. This series of articles will take a step-by-step approach to achieve this goal.
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Advanced Variables and Data Types in MQL5

Advanced Variables and Data Types in MQL5

Variables and data types are very important topics not only in MQL5 programming but also in any programming language. MQL5 variables and data types can be categorized as simple and advanced ones. In this article, we will identify and learn about advanced ones because we already mentioned simple ones in a previous article.
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Price Action Analysis Toolkit Development (Part 7): Signal Pulse EA

Price Action Analysis Toolkit Development (Part 7): Signal Pulse EA

Unlock the potential of multi-timeframe analysis with 'Signal Pulse,' an MQL5 Expert Advisor that integrates Bollinger Bands and the Stochastic Oscillator to deliver accurate, high-probability trading signals. Discover how to implement this strategy and effectively visualize buy and sell opportunities using custom arrows. Ideal for traders seeking to enhance their judgment through automated analysis across multiple timeframes.
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Building A Candlestick Trend Constraint Model(Part 3): Detecting changes in trends while using this system

Building A Candlestick Trend Constraint Model(Part 3): Detecting changes in trends while using this system

This article explores how economic news releases, investor behavior, and various factors can influence market trend reversals. It includes a video explanation and proceeds by incorporating MQL5 code into our program to detect trend reversals, alert us, and take appropriate actions based on market conditions. This builds upon previous articles in the series.
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Creating a Trading Administrator Panel in MQL5 (Part III): Enhancing the GUI with Visual Styling (I)

Creating a Trading Administrator Panel in MQL5 (Part III): Enhancing the GUI with Visual Styling (I)

In this article, we will focus on visually styling the graphical user interface (GUI) of our Trading Administrator Panel using MQL5. We’ll explore various techniques and features available in MQL5 that allow for customization and optimization of the interface, ensuring it meets the needs of traders while maintaining an attractive aesthetic.
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Neural networks made easy (Part 66): Exploration problems in offline learning

Neural networks made easy (Part 66): Exploration problems in offline learning

Models are trained offline using data from a prepared training dataset. While providing certain advantages, its negative side is that information about the environment is greatly compressed to the size of the training dataset. Which, in turn, limits the possibilities of exploration. In this article, we will consider a method that enables the filling of a training dataset with the most diverse data possible.
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Building a Candlestick Trend Constraint Model (Part 8): Expert Advisor Development (I)

Building a Candlestick Trend Constraint Model (Part 8): Expert Advisor Development (I)

In this discussion, we will create our first Expert Advisor in MQL5 based on the indicator we made in the prior article. We will cover all the features required to make the process automatic, including risk management. This will extensively benefit the users to advance from manual execution of trades to automated systems.
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DoEasy. Controls (Part 5): Base WinForms object, Panel control, AutoSize parameter

DoEasy. Controls (Part 5): Base WinForms object, Panel control, AutoSize parameter

In the article, I will create the base object of all library WinForms objects and start implementing the AutoSize property of the Panel WinForms object — auto sizing for fitting the object internal content.
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DoEasy. Controls (Part 29): ScrollBar auxiliary control

DoEasy. Controls (Part 29): ScrollBar auxiliary control

In this article, I will start developing the ScrollBar auxiliary control element and its derivative objects — vertical and horizontal scrollbars. A scrollbar is used to scroll the content of the form if it goes beyond the container. Scrollbars are usually located at the bottom and to the right of the form. The horizontal one at the bottom scrolls content left and right, while the vertical one scrolls up and down.
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William Gann methods (Part II): Creating Gann Square indicator

William Gann methods (Part II): Creating Gann Square indicator

We will create an indicator based on the Gann's Square of 9, built by squaring time and price. We will prepare the code and test the indicator in the platform on different time intervals.
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Neural Networks in Trading: Scene-Aware Object Detection (HyperDet3D)

Neural Networks in Trading: Scene-Aware Object Detection (HyperDet3D)

We invite you to get acquainted with a new approach to detecting objects using hypernetworks. A hypernetwork generates weights for the main model, which allows taking into account the specifics of the current market situation. This approach allows us to improve forecasting accuracy by adapting the model to different trading conditions.
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Population optimization algorithms: Artificial Bee Colony (ABC)

Population optimization algorithms: Artificial Bee Colony (ABC)

In this article, we will study the algorithm of an artificial bee colony and supplement our knowledge with new principles of studying functional spaces. In this article, I will showcase my interpretation of the classic version of the algorithm.
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Building A Candlestick Trend Constraint Model (Part 1): For EAs And Technical Indicators

Building A Candlestick Trend Constraint Model (Part 1): For EAs And Technical Indicators

This article is aimed at beginners and pro-MQL5 developers. It provides a piece of code to define and constrain signal-generating indicators to trends in higher timeframes. In this way, traders can enhance their strategies by incorporating a broader market perspective, leading to potentially more robust and reliable trading signals.
Ten Basic Errors of a Newcomer in Trading

Ten Basic Errors of a Newcomer in Trading

There are ten basic errors of a newcomer intrading: trading at market opening, undue hurry in taking profit, adding of lots in a losing position, closing positions starting with the best one, revenge, the most preferable positions, trading by the principle of 'bought for ever', closing of a profitable strategic position on the first day, closing of a position when alerted to open an opposite position, doubts.
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Timeseries in DoEasy library (part 50): Multi-period multi-symbol standard indicators with a shift

Timeseries in DoEasy library (part 50): Multi-period multi-symbol standard indicators with a shift

In the article, let’s improve library methods for correct display of multi-symbol multi-period standard indicators, which lines are displayed on the current symbol chart with a shift set in the settings. As well, let’s put things in order in methods of work with standard indicators and remove the redundant code to the library area in the final indicator program.
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Data Science and Machine Learning(Part 14): Finding Your Way in the Markets with Kohonen Maps

Data Science and Machine Learning(Part 14): Finding Your Way in the Markets with Kohonen Maps

Are you looking for a cutting-edge approach to trading that can help you navigate complex and ever-changing markets? Look no further than Kohonen maps, an innovative form of artificial neural networks that can help you uncover hidden patterns and trends in market data. In this article, we'll explore how Kohonen maps work, and how they can be used to develop smarter, more effective trading strategies. Whether you're a seasoned trader or just starting out, you won't want to miss this exciting new approach to trading.
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MetaTrader 5 Machine Learning Blueprint (Part 1): Data Leakage and Timestamp Fixes

MetaTrader 5 Machine Learning Blueprint (Part 1): Data Leakage and Timestamp Fixes

Before we can even begin to make use of ML in our trading on MetaTrader 5, it’s crucial to address one of the most overlooked pitfalls—data leakage. This article unpacks how data leakage, particularly the MetaTrader 5 timestamp trap, can distort our model's performance and lead to unreliable trading signals. By diving into the mechanics of this issue and presenting strategies to prevent it, we pave the way for building robust machine learning models that deliver trustworthy predictions in live trading environments.
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Introduction to MQL5 (Part 17): Building Expert Advisors for Trend Reversals

Introduction to MQL5 (Part 17): Building Expert Advisors for Trend Reversals

This article teaches beginners how to build an Expert Advisor (EA) in MQL5 that trades based on chart pattern recognition using trend line breakouts and reversals. By learning how to retrieve trend line values dynamically and compare them with price action, readers will be able to develop EAs capable of identifying and trading chart patterns such as ascending and descending trend lines, channels, wedges, triangles, and more.
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Introduction to MQL5 (Part 8): Beginner's Guide to Building Expert Advisors (II)

Introduction to MQL5 (Part 8): Beginner's Guide to Building Expert Advisors (II)

This article addresses common beginner questions from MQL5 forums and demonstrates practical solutions. Learn to perform essential tasks like buying and selling, obtaining candlestick prices, and managing automated trading aspects such as trade limits, trading periods, and profit/loss thresholds. Get step-by-step guidance to enhance your understanding and implementation of these concepts in MQL5.
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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.
Betting Modeling as Means of Developing "Market Intuition"

Betting Modeling as Means of Developing "Market Intuition"

The article dwells on the notion of "market intuition" and ways of developing it. The method described in the article is based on the modeling of financial betting in the form of a simple game.
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Creating an MQL5-Telegram Integrated Expert Advisor (Part 2): Sending Signals from MQL5 to Telegram

Creating an MQL5-Telegram Integrated Expert Advisor (Part 2): Sending Signals from MQL5 to Telegram

In this article, we create an MQL5-Telegram integrated Expert Advisor that sends moving average crossover signals to Telegram. We detail the process of generating trading signals from moving average crossovers, implementing the necessary code in MQL5, and ensuring the integration works seamlessly. The result is a system that provides real-time trading alerts directly to your Telegram group chat.
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