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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Category Theory in MQL5 (Part 17): Functors and Monoids

Category Theory in MQL5 (Part 17): Functors and Monoids

This article, the final in our series to tackle functors as a subject, revisits monoids as a category. Monoids which we have already introduced in these series are used here to aid in position sizing, together with multi-layer perceptrons.
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Cross-validation and basics of causal inference in CatBoost models, export to ONNX format

Cross-validation and basics of causal inference in CatBoost models, export to ONNX format

The article proposes the method of creating bots using machine learning.
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Population optimization algorithms: Simulated Isotropic Annealing (SIA) algorithm. Part II

Population optimization algorithms: Simulated Isotropic Annealing (SIA) algorithm. Part II

The first part was devoted to the well-known and popular algorithm - simulated annealing. We have thoroughly considered its pros and cons. The second part of the article is devoted to the radical transformation of the algorithm, which turns it into a new optimization algorithm - Simulated Isotropic Annealing (SIA).
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GUI: Tips and Tricks for creating your own Graphic Library in MQL

GUI: Tips and Tricks for creating your own Graphic Library in MQL

We'll go through the basics of GUI libraries so that you can understand how they work or even start making your own.
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Developing a Replay System (Part 29): Expert Advisor project — C_Mouse class (III)

Developing a Replay System (Part 29): Expert Advisor project — C_Mouse class (III)

After improving the C_Mouse class, we can focus on creating a class designed to create a completely new framework fr our analysis. We will not use inheritance or polymorphism to create this new class. Instead, we will change, or better said, add new objects to the price line. That's what we will do in this article. In the next one, we will look at how to change the analysis. All this will be done without changing the code of the C_Mouse class. Well, actually, it would be easier to achieve this using inheritance or polymorphism. However, there are other methods to achieve the same result.
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Developing an MQL5 Reinforcement Learning agent with RestAPI integration (Part 1): How to use RestAPIs in MQL5

Developing an MQL5 Reinforcement Learning agent with RestAPI integration (Part 1): How to use RestAPIs in MQL5

In this article we will talk about the importance of APIs (Application Programming Interface) for interaction between different applications and software systems. We will see the role of APIs in simplifying interactions between applications, allowing them to efficiently share data and functionality.
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Neural networks are easy (Part 59): Dichotomy of Control (DoC)

Neural networks are easy (Part 59): Dichotomy of Control (DoC)

In the previous article, we got acquainted with the Decision Transformer. But the complex stochastic environment of the foreign exchange market did not allow us to fully implement the potential of the presented method. In this article, I will introduce an algorithm that is aimed at improving the performance of algorithms in stochastic environments.
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Category Theory in MQL5 (Part 12): Orders

Category Theory in MQL5 (Part 12): Orders

This article which is part of a series that follows Category Theory implementation of Graphs in MQL5, delves in Orders. We examine how concepts of Order-Theory can support monoid sets in informing trade decisions by considering two major ordering types.
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Creating a market making algorithm in MQL5

Creating a market making algorithm in MQL5

How do market makers work? Let's consider this issue and create a primitive market-making algorithm.
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Modified Grid-Hedge EA in MQL5 (Part III): Optimizing Simple Hedge Strategy (I)

Modified Grid-Hedge EA in MQL5 (Part III): Optimizing Simple Hedge Strategy (I)

In this third part, we revisit the Simple Hedge and Simple Grid Expert Advisors (EAs) developed earlier. Our focus shifts to refining the Simple Hedge EA through mathematical analysis and a brute force approach, aiming for optimal strategy usage. This article delves deep into the mathematical optimization of the strategy, setting the stage for future exploration of coding-based optimization in later installments.
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Permuting price bars in MQL5

Permuting price bars in MQL5

In this article we present an algorithm for permuting price bars and detail how permutation tests can be used to recognize instances where strategy performance has been fabricated to deceive potential buyers of Expert Advisors.
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Indicator of historical positions on the chart as their profit/loss diagram

Indicator of historical positions on the chart as their profit/loss diagram

In this article, I will consider the option of obtaining information about closed positions based on their trading history. Besides, I will create a simple indicator that displays the approximate profit/loss of positions on each bar as a diagram.
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MQL5 Wizard Techniques you should know (Part 12): Newton Polynomial

MQL5 Wizard Techniques you should know (Part 12): Newton Polynomial

Newton’s polynomial, which creates quadratic equations from a set of a few points, is an archaic but interesting approach at looking at a time series. In this article we try to explore what aspects could be of use to traders from this approach as well as address its limitations.
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Population optimization algorithms: Intelligent Water Drops (IWD) algorithm

Population optimization algorithms: Intelligent Water Drops (IWD) algorithm

The article considers an interesting algorithm derived from inanimate nature - intelligent water drops (IWD) simulating the process of river bed formation. The ideas of this algorithm made it possible to significantly improve the previous leader of the rating - SDS. As usual, the new leader (modified SDSm) can be found in the attachment.
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Developing an MQTT client for MetaTrader 5: a TDD approach — Final

Developing an MQTT client for MetaTrader 5: a TDD approach — Final

This article is the last part of a series describing our development steps of a native MQL5 client for the MQTT 5.0 protocol. Although the library is not production-ready yet, in this part, we will use our client to update a custom symbol with ticks (or rates) sourced from another broker. Please, see the bottom of this article for more information about the library's current status, what is missing for it to be fully compliant with the MQTT 5.0 protocol, a possible roadmap, and how to follow and contribute to its development.
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Developing an MQTT client for MetaTrader 5: a TDD approach — Part 2

Developing an MQTT client for MetaTrader 5: a TDD approach — Part 2

This article is part of a series describing our development steps of a native MQL5 client for the MQTT protocol. In this part we describe our code organization, the first header files and classes, and how we are writing our tests. This article also includes brief notes about the Test-Driven-Development practice and how we are applying it to this project.
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The Group Method of Data Handling: Implementing the Combinatorial Algorithm in MQL5

The Group Method of Data Handling: Implementing the Combinatorial Algorithm in MQL5

In this article we continue our exploration of the Group Method of Data Handling family of algorithms, with the implementation of the Combinatorial Algorithm along with its refined incarnation, the Combinatorial Selective Algorithm in MQL5.
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Color buffers in multi-symbol multi-period indicators

Color buffers in multi-symbol multi-period indicators

In this article, we will review the structure of the indicator buffer in multi-symbol, multi-period indicators and organize the display of colored buffers of these indicators on the chart.
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Developing a Replay System (Part 33): Order System (II)

Developing a Replay System (Part 33): Order System (II)

Today we will continue to develop the order system. As you will see, we will be massively reusing what has already been shown in other articles. Nevertheless, you will receive a small reward in this article. First, we will develop a system that can be used with a real trading server, both from a demo account or from a real one. We will make extensive use of the MetaTrader 5 platform, which will provide us with all the necessary support from the beginning.
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Triangular arbitrage with predictions

Triangular arbitrage with predictions

This article simplifies triangular arbitrage, showing you how to use predictions and specialized software to trade currencies smarter, even if you're new to the market. Ready to trade with expertise?
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Category Theory in MQL5 (Part 11): Graphs

Category Theory in MQL5 (Part 11): Graphs

This article is a continuation in a series that look at Category Theory implementation in MQL5. In here we examine how Graph-Theory could be integrated with monoids and other data structures when developing a close-out strategy to a trading system.
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Trailing stop in trading

Trailing stop in trading

In this article, we will look at the use of a trailing stop in trading. We will assess how useful and effective it is, and how it can be used. The efficiency of a trailing stop largely depends on price volatility and the selection of the stop loss level. A variety of approaches can be used to set a stop loss.
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Combinatorially Symmetric Cross Validation In MQL5

Combinatorially Symmetric Cross Validation In MQL5

In this article we present the implementation of Combinatorially Symmetric Cross Validation in pure MQL5, to measure the degree to which a overfitting may occure after optimizing a strategy using the slow complete algorithm of the Strategy Tester.
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Population optimization algorithms: Spiral Dynamics Optimization (SDO) algorithm

Population optimization algorithms: Spiral Dynamics Optimization (SDO) algorithm

The article presents an optimization algorithm based on the patterns of constructing spiral trajectories in nature, such as mollusk shells - the spiral dynamics optimization (SDO) algorithm. I have thoroughly revised and modified the algorithm proposed by the authors. The article will consider the necessity of these changes.
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Data label for time series mining (Part 6):Apply and Test in EA Using ONNX

Data label for time series mining (Part 6):Apply and Test in EA Using ONNX

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!
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Population optimization algorithms: Binary Genetic Algorithm (BGA). Part II

Population optimization algorithms: Binary Genetic Algorithm (BGA). Part II

In this article, we will look at the binary genetic algorithm (BGA), which models the natural processes that occur in the genetic material of living things in nature.
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MQL5 Wizard Techniques you should know (14): Multi Objective Timeseries Forecasting with STF

MQL5 Wizard Techniques you should know (14): Multi Objective Timeseries Forecasting with STF

Spatial Temporal Fusion which is using both ‘space’ and time metrics in modelling data is primarily useful in remote-sensing, and a host of other visual based activities in gaining a better understanding of our surroundings. Thanks to a published paper, we take a novel approach in using it by examining its potential to traders.
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Population optimization algorithms: Charged System Search (CSS) algorithm

Population optimization algorithms: Charged System Search (CSS) algorithm

In this article, we will consider another optimization algorithm inspired by inanimate nature - Charged System Search (CSS) algorithm. The purpose of this article is to present a new optimization algorithm based on the principles of physics and mechanics.
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Developing a Replay System (Part 30): Expert Advisor project — C_Mouse class (IV)

Developing a Replay System (Part 30): Expert Advisor project — C_Mouse class (IV)

Today we will learn a technique that can help us a lot in different stages of our professional life as a programmer. Often it is not the platform itself that is limited, but the knowledge of the person who talks about the limitations. This article will tell you that with common sense and creativity you can make the MetaTrader 5 platform much more interesting and versatile without resorting to creating crazy programs or anything like that, and create simple yet safe and reliable code. We will use our creativity to modify existing code without deleting or adding a single line to the source code.
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Introduction to MQL5 (Part 5): A Beginner's Guide to Array Functions in MQL5

Introduction to MQL5 (Part 5): A Beginner's Guide to Array Functions in MQL5

Explore the world of MQL5 arrays in Part 5, designed for absolute beginners. Simplifying complex coding concepts, this article focuses on clarity and inclusivity. Join our community of learners, where questions are embraced, and knowledge is shared!
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Mastering Model Interpretation: Gaining Deeper Insight From Your Machine Learning Models

Mastering Model Interpretation: Gaining Deeper Insight From Your Machine Learning Models

Machine Learning is a complex and rewarding field for anyone of any experience. In this article we dive deep into the inner mechanisms powering the models you build, we explore the intricate world of features,predictions and impactful decisions unravelling the complexities and gaining a firm grasp of model interpretation. Learn the art of navigating tradeoffs , enhancing predictions, ranking feature importance all while ensuring robust decision making. This essential read helps you clock more performance from your machine learning models and extract more value for employing machine learning methodologies.
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Developing an MQL5 RL agent with RestAPI integration (Part 3): Creating automatic moves and test scripts in MQL5

Developing an MQL5 RL agent with RestAPI integration (Part 3): Creating automatic moves and test scripts in MQL5

This article discusses the implementation of automatic moves in the tic-tac-toe game in Python, integrated with MQL5 functions and unit tests. The goal is to improve the interactivity of the game and ensure the reliability of the system through testing in MQL5. The presentation covers game logic development, integration, and hands-on testing, and concludes with the creation of a dynamic game environment and a robust integrated system.
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Neural networks made easy (Part 63): Unsupervised Pretraining for Decision Transformer (PDT)

Neural networks made easy (Part 63): Unsupervised Pretraining for Decision Transformer (PDT)

We continue to discuss the family of Decision Transformer methods. From previous article, we have already noticed that training the transformer underlying the architecture of these methods is a rather complex task and requires a large labeled dataset for training. In this article we will look at an algorithm for using unlabeled trajectories for preliminary model training.
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The case for using Hospital-Performance Data with Perceptrons, this Q4, in weighing SPDR XLV's next Performance

The case for using Hospital-Performance Data with Perceptrons, this Q4, in weighing SPDR XLV's next Performance

XLV is SPDR healthcare ETF and in an age where it is common to be bombarded by a wide array of traditional news items plus social media feeds, it can be pressing to select a data set for use with a model. We try to tackle this problem for this ETF by sizing up some of its critical data sets in MQL5.
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MQL5 Wizard Techniques you should know (Part 10). The Unconventional RBM

MQL5 Wizard Techniques you should know (Part 10). The Unconventional RBM

Restrictive Boltzmann Machines are at the basic level, a two-layer neural network that is proficient at unsupervised classification through dimensionality reduction. We take its basic principles and examine if we were to re-design and train it unorthodoxly, we could get a useful signal filter.
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Overcoming ONNX Integration Challenges

Overcoming ONNX Integration Challenges

ONNX is a great tool for integrating complex AI code between different platforms, it is a great tool that comes with some challenges that one must address to get the most out of it, In this article we discuss the common issues you might face and how to mitigate them.
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MQL5 Wizard Techniques You Should Know (Part 15): Support Vector Machines with Newton's Polynomial

MQL5 Wizard Techniques You Should Know (Part 15): Support Vector Machines with Newton's Polynomial

Support Vector Machines classify data based on predefined classes by exploring the effects of increasing its dimensionality. It is a supervised learning method that is fairly complex given its potential to deal with multi-dimensioned data. For this article we consider how it’s very basic implementation of 2-dimensioned data can be done more efficiently with Newton’s Polynomial when classifying price-action.
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Population optimization algorithms: Micro Artificial immune system (Micro-AIS)

Population optimization algorithms: Micro Artificial immune system (Micro-AIS)

The article considers an optimization method based on the principles of the body's immune system - Micro Artificial Immune System (Micro-AIS) - a modification of AIS. Micro-AIS uses a simpler model of the immune system and simple immune information processing operations. The article also discusses the advantages and disadvantages of Micro-AIS compared to conventional AIS.
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Implementation of the Augmented Dickey Fuller test in MQL5

Implementation of the Augmented Dickey Fuller test in MQL5

In this article we demonstrate the implementation of the Augmented Dickey-Fuller test, and apply it to conduct cointegration tests using the Engle-Granger method.
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Quantization in machine learning (Part 2): Data preprocessing, table selection, training CatBoost models

Quantization in machine learning (Part 2): Data preprocessing, table selection, training CatBoost models

The article considers the practical application of quantization in the construction of tree models. The methods for selecting quantum tables and data preprocessing are considered. No complex mathematical equations are used.