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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News Trading Made Easy (Part 6): Performing Trades (III)

News Trading Made Easy (Part 6): Performing Trades (III)

In this article news filtration for individual news events based on their IDs will be implemented. In addition, previous SQL queries will be improved to provide additional information or reduce the query's runtime. Furthermore, the code built in the previous articles will be made functional.
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Building A Candlestick Trend Constraint Model (Part 8): Expert Advisor Development (II)

Building A Candlestick Trend Constraint Model (Part 8): Expert Advisor Development (II)

Think about an independent Expert Advisor. Previously, we discussed an indicator-based Expert Advisor that also partnered with an independent script for drawing risk and reward geometry. Today, we will discuss the architecture of an MQL5 Expert Advisor, that integrates, all the features in one program.
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DoEasy. Controls (Part 16): TabControl WinForms object — several rows of tab headers, stretching headers to fit the container

DoEasy. Controls (Part 16): TabControl WinForms object — several rows of tab headers, stretching headers to fit the container

In this article, I will continue the development of TabControl and implement the arrangement of tab headers on all four sides of the control for all modes of setting the size of headers: Normal, Fixed and Fill To Right.
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Master MQL5 from beginner to pro (Part V): Fundamental control flow operators

Master MQL5 from beginner to pro (Part V): Fundamental control flow operators

This article explores the key operators used to modify the program's execution flow: conditional statements, loops, and switch statements. Utilizing these operators will allow the functions we create to behave more "intelligently".
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Price Action Analysis Toolkit Development (Part 29): Boom and Crash Interceptor EA

Price Action Analysis Toolkit Development (Part 29): Boom and Crash Interceptor EA

Discover how the Boom & Crash Interceptor EA transforms your charts into a proactive alert system-spotting explosive moves with lightning-fast velocity scans, volatility surge checks, trend confirmation, and pivot-zone filters. With crisp green “Boom” and red “Crash” arrows guiding your every decision, this tool cuts through the noise and lets you capitalize on market spikes like never before. Dive in to see how it works and why it can become your next essential edge.
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Moving to MQL5 Algo Forge (Part 2): Working with Multiple Repositories

Moving to MQL5 Algo Forge (Part 2): Working with Multiple Repositories

In this article, we are considering one of the possible approaches to organizing the storage of the project's source code in a public repository. We will distribute the code across different branches to establish clear and convenient rules for the project development.
Vladimir Tsyrulnik: The Essense of my program is improvisation! (ATC 2010)
Vladimir Tsyrulnik: The Essense of my program is improvisation! (ATC 2010)

Vladimir Tsyrulnik: The Essense of my program is improvisation! (ATC 2010)

Vladimir Tsyrulnik is the holder of one of the brightest highs of the current Championship. By the end of the third trading week Vladimir's Expert Advisor was on the sixth position. The IMEX algorithm the Expert Advisor is based on was developed by Vladimir. To learn more about this algorithm, we had an interview with Vladimir.
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Neural Networks in Trading: Hyperbolic Latent Diffusion Model (Final Part)

Neural Networks in Trading: Hyperbolic Latent Diffusion Model (Final Part)

The use of anisotropic diffusion processes for encoding the initial data in a hyperbolic latent space, as proposed in the HypDIff framework, assists in preserving the topological features of the current market situation and improves the quality of its analysis. In the previous article, we started implementing the proposed approaches using MQL5. Today we will continue the work we started and will bring it to its logical conclusion.
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Robustness Testing on Expert Advisors

Robustness Testing on Expert Advisors

In strategy development, there are many intricate details to consider, many of which are not highlighted for beginner traders. As a result, many traders, myself included, have had to learn these lessons the hard way. This article is based on my observations of common pitfalls that most beginner traders encounter when developing strategies on MQL5. It will offer a range of tips, tricks, and examples to help identify the disqualification of an EA and test the robustness of our own EAs in an easy-to-implement way. The goal is to educate readers, helping them avoid future scams when purchasing EAs as well as preventing mistakes in their own strategy development.
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Category Theory in MQL5 (Part 20): A detour to Self-Attention and the Transformer

Category Theory in MQL5 (Part 20): A detour to Self-Attention and the Transformer

We digress in our series by pondering at part of the algorithm to chatGPT. Are there any similarities or concepts borrowed from natural transformations? We attempt to answer these and other questions in a fun piece, with our code in a signal class format.
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Multiple Symbol Analysis With Python And MQL5 (Part 3): Triangular Exchange Rates

Multiple Symbol Analysis With Python And MQL5 (Part 3): Triangular Exchange Rates

Traders often face drawdowns from false signals, while waiting for confirmation can lead to missed opportunities. This article introduces a triangular trading strategy using Silver’s pricing in Dollars (XAGUSD) and Euros (XAGEUR), along with the EURUSD exchange rate, to filter out noise. By leveraging cross-market relationships, traders can uncover hidden sentiment and refine their entries in real time.
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Neural networks made easy (Part 47): Continuous action space

Neural networks made easy (Part 47): Continuous action space

In this article, we expand the range of tasks of our agent. The training process will include some aspects of money and risk management, which are an integral part of any trading strategy.
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Price Action Analysis Toolkit Development (Part 15): Introducing Quarters Theory (I) — Quarters Drawer Script

Price Action Analysis Toolkit Development (Part 15): Introducing Quarters Theory (I) — Quarters Drawer Script

Points of support and resistance are critical levels that signal potential trend reversals and continuations. Although identifying these levels can be challenging, once you pinpoint them, you’re well-prepared to navigate the market. For further assistance, check out the Quarters Drawer tool featured in this article, it will help you identify both primary and minor support and resistance levels.
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Reimagining Classic Strategies (Part II): Bollinger Bands Breakouts

Reimagining Classic Strategies (Part II): Bollinger Bands Breakouts

This article explores a trading strategy that integrates Linear Discriminant Analysis (LDA) with Bollinger Bands, leveraging categorical zone predictions for strategic market entry signals.
Interview with Tim Fass (ATC 2011)
Interview with Tim Fass (ATC 2011)

Interview with Tim Fass (ATC 2011)

A student from Germany Tim Fass (Tim) is participating in the Automated Trading Championship for the first time. Nevertheless, his Expert Advisor The_Wild_13 already got featured at the very top of the Championship rating and seems to be holding his position in the top ten. Tim told us about his Expert Advisor, his faith in the success of simple strategies and his wildest dreams.
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Neural Networks in Trading: Enhancing Transformer Efficiency by Reducing Sharpness (Final Part)

Neural Networks in Trading: Enhancing Transformer Efficiency by Reducing Sharpness (Final Part)

SAMformer offers a solution to the key drawbacks of Transformer models in long-term time series forecasting, such as training complexity and poor generalization on small datasets. Its shallow architecture and sharpness-aware optimization help avoid suboptimal local minima. In this article, we will continue to implement approaches using MQL5 and evaluate their practical value.
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Self Optimizing Expert Advisors in MQL5 (Part 17): Ensemble Intelligence

Self Optimizing Expert Advisors in MQL5 (Part 17): Ensemble Intelligence

All algorithmic trading strategies are difficult to set up and maintain, regardless of complexity—a challenge shared by beginners and experts alike. This article introduces an ensemble framework where supervised models and human intuition work together to overcome their shared limitations. By aligning a moving average channel strategy with a Ridge Regression model on the same indicators, we achieve centralized control, faster self-correction, and profitability from otherwise unprofitable systems.
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MQL5 Trading Toolkit (Part 8): How to Implement and Use the History Manager EX5 Library in Your Codebase

MQL5 Trading Toolkit (Part 8): How to Implement and Use the History Manager EX5 Library in Your Codebase

Discover how to effortlessly import and utilize the History Manager EX5 library in your MQL5 source code to process trade histories in your MetaTrader 5 account in this series' final article. With simple one-line function calls in MQL5, you can efficiently manage and analyze your trading data. Additionally, you will learn how to create different trade history analytics scripts and develop a price-based Expert Advisor as practical use-case examples. The example EA leverages price data and the History Manager EX5 library to make informed trading decisions, adjust trade volumes, and implement recovery strategies based on previously closed trades.
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Integrate Your Own LLM into EA (Part 5): Develop and Test Trading Strategy with LLMs(IV) — Test Trading Strategy

Integrate Your Own LLM into EA (Part 5): Develop and Test Trading Strategy with LLMs(IV) — Test Trading Strategy

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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MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library

MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library

Learn how to create a developer's toolkit for managing various position operations with MQL5. In this article, I will demonstrate how to create a library of functions (ex5) that will perform simple to advanced position management operations, including automatic handling and reporting of the different errors that arise when dealing with position management tasks with MQL5.
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Developing a trading Expert Advisor from scratch (Part 26): Towards the future (I)

Developing a trading Expert Advisor from scratch (Part 26): Towards the future (I)

Today we will take our order system to the next level. But before that, we need to solve a few problems. Now we have some questions that are related to how we want to work and what things we do during the trading day.
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MQL5 Wizard Techniques you should know (Part 71): Using Patterns of MACD and the OBV

MQL5 Wizard Techniques you should know (Part 71): Using Patterns of MACD and the OBV

The Moving-Average-Convergence-Divergence (MACD) oscillator and the On-Balance-Volume (OBV) oscillator are another pair of indicators that could be used in conjunction within an MQL5 Expert Advisor. This pairing, as is practice in these article series, is complementary with the MACD affirming trends while OBV checks volume. As usual, we use the MQL5 wizard to build and test any potential these two may possess.
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GIT: What is it?

GIT: What is it?

In this article, I will introduce a very important tool for developers. If you are not familiar with GIT, read this article to get an idea of what it is and how to use it with MQL5.
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Mastering File Operations in MQL5: From Basic I/O to Building a Custom CSV Reader

Mastering File Operations in MQL5: From Basic I/O to Building a Custom CSV Reader

This article focuses on essential MQL5 file-handling techniques, spanning trade logs, CSV processing, and external data integration. It offers both conceptual understanding and hands-on coding guidance. Readers will learn to build a custom CSV importer class step-by-step, gaining practical skills for real-world applications.
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Neural Networks in Trading: Using Language Models for Time Series Forecasting

Neural Networks in Trading: Using Language Models for Time Series Forecasting

We continue to study time series forecasting models. In this article, we get acquainted with a complex algorithm built on the use of a pre-trained language model.
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Feature Engineering With Python And MQL5 (Part I): Forecasting Moving Averages For Long-Range AI Models

Feature Engineering With Python And MQL5 (Part I): Forecasting Moving Averages For Long-Range AI Models

The moving averages are by far the best indicators for our AI models to predict. However, we can improve our accuracy even further by carefully transforming our data. This article will demonstrate, how you can build AI Models capable of forecasting further into the future than you may currently be practicing without significant drops to your accuracy levels. It is truly remarkable, how useful the moving averages are.
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MQL5 Wizard Techniques you should know (Part 17): Multicurrency Trading

MQL5 Wizard Techniques you should know (Part 17): Multicurrency Trading

Trading across multiple currencies is not available by default when an expert advisor is assembled via the wizard. We examine 2 possible hacks traders can make when looking to test their ideas off more than one symbol at a time.
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Developing a multi-currency Expert Advisor (Part 12): Developing prop trading level risk manager

Developing a multi-currency Expert Advisor (Part 12): Developing prop trading level risk manager

In the EA being developed, we already have a certain mechanism for controlling drawdown. But it is probabilistic in nature, as it is based on the results of testing on historical price data. Therefore, the drawdown can sometimes exceed the maximum expected values (although with a small probability). Let's try to add a mechanism that ensures guaranteed compliance with the specified drawdown level.
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Seasonality Filtering and time period for Deep Learning ONNX models with python for EA

Seasonality Filtering and time period for Deep Learning ONNX models with python for EA

Can we benefit from seasonality when creating models for Deep Learning with Python? Does filtering data for the ONNX models help to get better results? What time period should we use? We will cover all of this over this article.
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DoEasy. Controls (Part 24): Hint auxiliary WinForms object

DoEasy. Controls (Part 24): Hint auxiliary WinForms object

In this article, I will revise the logic of specifying the base and main objects for all WinForms library objects, develop a new Hint base object and several of its derived classes to indicate the possible direction of moving the separator.
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Population optimization algorithms: Saplings Sowing and Growing up (SSG)

Population optimization algorithms: Saplings Sowing and Growing up (SSG)

Saplings Sowing and Growing up (SSG) algorithm is inspired by one of the most resilient organisms on the planet demonstrating outstanding capability for survival in a wide variety of conditions.
Interview with Alexander Topchylo (ATC 2010)
Interview with Alexander Topchylo (ATC 2010)

Interview with Alexander Topchylo (ATC 2010)

Alexander Topchylo (Better) is the winner of the Automated Trading Championship 2007. Alexander is an expert in neural networks - his Expert Advisor based on a neural network was on top of best EAs of year 2007. In this interview Alexander tells us about his life after the Championships, his own business and new algorithms for trading systems.
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Gain An Edge Over Any Market (Part II): Forecasting Technical Indicators

Gain An Edge Over Any Market (Part II): Forecasting Technical Indicators

Did you know that we can gain more accuracy forecasting certain technical indicators than predicting the underlying price of a traded symbol? Join us to explore how to leverage this insight for better trading strategies.
Interview with Andrea Zani (ATC 2011)
Interview with Andrea Zani (ATC 2011)

Interview with Andrea Zani (ATC 2011)

On the eleventh week of the Automated Trading Championship, Andrea Zani (sbraer) got featured very close to the top five of the competition. It is on the sixth place with about 47,000 USD now. Andrea's Expert Advisor AZXY has made only one losing deal, which was at the very beginning of the Championship. Since then, its equity curve has been steadily growing.
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From Novice to Expert: Collaborative Debugging in MQL5

From Novice to Expert: Collaborative Debugging in MQL5

Problem-solving can establish a concise routine for mastering complex skills, such as programming in MQL5. This approach allows you to concentrate on solving problems while simultaneously developing your skills. The more problems you tackle, the more advanced expertise is transferred to your brain. Personally, I believe that debugging is the most effective way to master programming. Today, we will walk through the code-cleaning process and discuss the best techniques for transforming a messy program into a clean, functional one. Read through this article and uncover valuable insights.
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MQL5 Wizard Techniques you should know (Part 19): Bayesian Inference

MQL5 Wizard Techniques you should know (Part 19): Bayesian Inference

Bayesian inference is the adoption of Bayes Theorem to update probability hypothesis as new information is made available. This intuitively leans to adaptation in time series analysis, and so we have a look at how we could use this in building custom classes not just for the signal but also money-management and trailing-stops.
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Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part I)

Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part I)

We will breakdown the main MQL5 code into specified code snippets to illustrate the integration of Telegram and WhatsApp for receiving signal notifications from the Trend Constraint indicator we are creating in this article series. This will help traders, both novices and experienced developers, grasp the concept easily. First, we will cover the setup of MetaTrader 5 for notifications and its significance to the user. This will help developers in advance to take notes to further apply in their systems.
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Introduction to MQL5 (Part 21): Automating Harmonic Pattern Detection

Introduction to MQL5 (Part 21): Automating Harmonic Pattern Detection

Learn how to detect and display the Gartley harmonic pattern in MetaTrader 5 using MQL5. This article explains each step of the process, from identifying swing points to applying Fibonacci ratios and plotting the full pattern on the chart for clear visual confirmation.
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Data Science and Machine Learning (Part 17): Money in the Trees? The Art and Science of Random Forests in Forex Trading

Data Science and Machine Learning (Part 17): Money in the Trees? The Art and Science of Random Forests in Forex Trading

Discover the secrets of algorithmic alchemy as we guide you through the blend of artistry and precision in decoding financial landscapes. Unearth how Random Forests transform data into predictive prowess, offering a unique perspective on navigating the complex terrain of stock markets. Join us on this journey into the heart of financial wizardry, where we demystify the role of Random Forests in shaping market destiny and unlocking the doors to lucrative opportunities
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Automating Trading Strategies in MQL5 (Part 39): Statistical Mean Reversion with Confidence Intervals and Dashboard

Automating Trading Strategies in MQL5 (Part 39): Statistical Mean Reversion with Confidence Intervals and Dashboard

In this article, we develop an MQL5 Expert Advisor for statistical mean reversion trading, calculating moments like mean, variance, skewness, kurtosis, and Jarque-Bera statistics over a specified period to identify non-normal distributions and generate buy/sell signals based on confidence intervals with adaptive thresholds