MQL4 and 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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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.
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.
Creating Custom Indicators in MQL5 (Part 2): Building a Gauge-Style RSI Display with Canvas and Needle Mechanics
In this article, we develop a gauge-style RSI indicator in MQL5 that visualizes Relative Strength Index values on a circular scale with a dynamic needle, color-coded ranges for overbought and oversold levels, and customizable legends. We utilize the Canvas class to draw elements like arcs, ticks, and pies, ensuring smooth updates on new RSI data.
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.
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.
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.
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.
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)
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.
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.
Developing an MQTT client for MetaTrader 5: a TDD approach — Part 3
This article is the third part of a series describing our development steps of a native MQL5 client for the MQTT protocol. In this part, we describe in detail how we are using Test-Driven Development to implement the Operational Behavior part of the CONNECT/CONNACK packet exchange. At the end of this step, our client MUST be able to behave appropriately when dealing with any of the possible server outcomes from a connection attempt.
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
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.
Category Theory in MQL5 (Part 2)
Category Theory is a diverse and expanding branch of Mathematics which as of yet is relatively uncovered in the MQL5 community. These series of articles look to introduce and examine some of its concepts with the overall goal of establishing an open library that attracts comments and discussion while hopefully furthering the use of this remarkable field in Traders' strategy development.
Alexander Anufrenko: "A danger foreseen is half avoided" (ATC 2010)
The risky development of Alexander Anufrenko (Anufrenko321) had been featured among the top three of the Championship for three weeks. Having suffered a catastrophic Stop Loss last week, his Expert Advisor lost about $60,000, but now once again he is approaching the leaders. In this interview the author of this interesting EA is describing the operating principles and characteristics of his application.
DoEasy. Controls (Part 28): Bar styles in the ProgressBar control
In this article, I will develop display styles and description text for the progress bar of the ProgressBar control.
Neural Networks in Trading: An Agent with Layered Memory (Final Part)
We continue our work on creating the FinMem framework, which uses layered memory approaches that mimic human cognitive processes. This allows the model not only to effectively process complex financial data but also to adapt to new signals, significantly improving the accuracy and effectiveness of investment decisions in dynamically changing markets.
MQL5 Wizard Techniques you should know (Part 84): Using Patterns of Stochastic Oscillator and the FrAMA - Conclusion
The Stochastic Oscillator and the Fractal Adaptive Moving Average are an indicator pairing that could be used for their ability to compliment each other within an MQL5 Expert Advisor. We introduced this pairing in the last article, and now look to wrap up by considering its 5 last signal patterns. In exploring this, as always, we use the MQL5 wizard to build and test out their potential.
Neural Networks Made Easy (Part 93): Adaptive Forecasting in Frequency and Time Domains (Final Part)
In this article, we continue the implementation of the approaches of the ATFNet model, which adaptively combines the results of 2 blocks (frequency and time) within time series forecasting.
DoEasy. Controls (Part 17): Cropping invisible object parts, auxiliary arrow buttons WinForms objects
In this article, I will create the functionality for hiding object sections located beyond their containers. Besides, I will create auxiliary arrow button objects to be used as part of other WinForms objects.
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.
Practicing the development of trading strategies
In this article, we will make an attempt to develop our own trading strategy. Any trading strategy must be based on some kind of statistical advantage. Moreover, this advantage should exist for a long time.
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.
From Novice to Expert: Reporting EA — Setting up the work flow
Brokerages often provide trading account reports at regular intervals, based on a predefined schedule. These firms, through their API technologies, have access to your account activity and trading history, allowing them to generate performance reports on your behalf. Similarly, the MetaTrader 5 terminal stores detailed records of your trading activity, which can be leveraged using MQL5 to create fully customized reports and define personalized delivery methods.
Quantum computing and trading: A fresh approach to price forecasts
The article describes an innovative approach to forecasting price movements in financial markets using quantum computing. The main focus is on the application of the Quantum Phase Estimation (QPE) algorithm to find prototypes of price patterns allowing traders to significantly speed up the market data analysis.
Developing a multi-currency Expert Advisor (Part 4): Pending virtual orders and saving status
Having started developing a multi-currency EA, we have already achieved some results and managed to carry out several code improvement iterations. However, our EA was unable to work with pending orders and resume operation after the terminal restart. Let's add these features.
Neural Networks Made Easy (Part 92): Adaptive Forecasting in Frequency and Time Domains
The authors of the FreDF method experimentally confirmed the advantage of combined forecasting in the frequency and time domains. However, the use of the weight hyperparameter is not optimal for non-stationary time series. In this article, we will get acquainted with the method of adaptive combination of forecasts in frequency and time domains.
Andrey Bolkonsky (abolk): "Any programmer knows that there is no software without bugs"
Andrey Bolkonsky (abolk) has been participating in the Jobs service since its opening. He has developed dozens of indicators and Expert Advisors for the MetaTrader 4 and MetaTrader 5 platforms. We will talk with Andrey about what a server is from the perspective of a programmer.
Quantization in machine learning (Part 1): Theory, sample code, analysis of implementation in CatBoost
The article considers the theoretical application of quantization in the construction of tree models and showcases the implemented quantization methods in CatBoost. No complex mathematical equations are used.
Neural networks made easy (Part 80): Graph Transformer Generative Adversarial Model (GTGAN)
In this article, I will get acquainted with the GTGAN algorithm, which was introduced in January 2024 to solve complex problems of generation architectural layouts with graph constraints.
Neural Networks in Trading: Transformer with Relative Encoding
Self-supervised learning can be an effective way to analyze large amounts of unlabeled data. The efficiency is provided by the adaptation of models to the specific features of financial markets, which helps improve the effectiveness of traditional methods. This article introduces an alternative attention mechanism that takes into account the relative dependencies and relationships between inputs.
Developing a Replay System (Part 27): Expert Advisor project — C_Mouse class (I)
In this article we will implement the C_Mouse class. It provides the ability to program at the highest level. However, talking about high-level or low-level programming languages is not about including obscene words or jargon in the code. It's the other way around. When we talk about high-level or low-level programming, we mean how easy or difficult the code is for other programmers to understand.
Neural networks made easy (Part 34): Fully Parameterized Quantile Function
We continue studying distributed Q-learning algorithms. In previous articles, we have considered distributed and quantile Q-learning algorithms. In the first algorithm, we trained the probabilities of given ranges of values. In the second algorithm, we trained ranges with a given probability. In both of them, we used a priori knowledge of one distribution and trained another one. In this article, we will consider an algorithm which allows the model to train for both distributions.
Population optimization algorithms: Nelder–Mead, or simplex search (NM) method
The article presents a complete exploration of the Nelder-Mead method, explaining how the simplex (function parameter space) is modified and rearranged at each iteration to achieve an optimal solution, and describes how the method can be improved.
Using association rules in Forex data analysis
How to apply predictive rules of supermarket retail analytics to the real Forex market? How are purchases of cookies, milk and bread related to stock exchange transactions? The article discusses an innovative approach to algorithmic trading based on the use of association rules.
Neural Networks in Trading: A Multi-Agent Self-Adaptive Model (Final Part)
In the previous article, we introduced the multi-agent self-adaptive framework MASA, which combines reinforcement learning approaches and self-adaptive strategies, providing a harmonious balance between profitability and risk in turbulent market conditions. We have built the functionality of individual agents within this framework. In this article, we will continue the work we started, bringing it to its logical conclusion.
Dimitar Manov: "I fear only extraordinary situations in the Championship" (ATC 2010)
In the recent review by Boris Odintsov the Expert Advisor of the Bulgarian Participant Dimitar Manov appeared among the most stable and reliable EAs. We decided to interview this developer and try to find the secret of his success. In this interview Dimitar has told us what situation would be unfavorable for his robot, why he's not using indicators and whether he is expecting to win the competition.
Brain Storm Optimization algorithm (Part II): Multimodality
In the second part of the article, we will move on to the practical implementation of the BSO algorithm, conduct tests on test functions and compare the efficiency of BSO with other optimization methods.
Integrating MQL5 with data processing packages (Part 2): Machine Learning and Predictive Analytics
In our series on integrating MQL5 with data processing packages, we delve in to the powerful combination of machine learning and predictive analysis. We will explore how to seamlessly connect MQL5 with popular machine learning libraries, to enable sophisticated predictive models for financial markets.
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