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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Developing a Replay System (Part 75): New Chart Trade (II)

Developing a Replay System (Part 75): New Chart Trade (II)

In this article, we will talk about the C_ChartFloatingRAD class. This is what makes Chart Trade work. However, the explanation does not end there. We will complete it in the next article, as the content of this article is quite extensive and requires deep understanding. The content presented here is intended solely for educational purposes. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.
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MQL5 Wizard Techniques you should know (Part 67): Using Patterns of TRIX and the Williams Percent Range

MQL5 Wizard Techniques you should know (Part 67): Using Patterns of TRIX and the Williams Percent Range

The Triple Exponential Moving Average Oscillator (TRIX) and the Williams Percentage Range Oscillator are another pair of indicators that could be used in conjunction within an MQL5 Expert Advisor. This indicator pair, like those we’ve covered recently, is also complementary given that TRIX defines the trend while Williams Percent Range affirms support and Resistance levels. As always, we use the MQL5 wizard to prototype any potential these two may have.
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Data Science and ML (Part 39): News + Artificial Intelligence, Would You Bet on it?

Data Science and ML (Part 39): News + Artificial Intelligence, Would You Bet on it?

News drives the financial markets, especially major releases like Non-Farm Payrolls (NFPs). We've all witnessed how a single headline can trigger sharp price movements. In this article, we dive into the powerful intersection of news data and Artificial Intelligence.
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Artificial Ecosystem-based Optimization (AEO) algorithm

Artificial Ecosystem-based Optimization (AEO) algorithm

The article considers a metaheuristic Artificial Ecosystem-based Optimization (AEO) algorithm, which simulates interactions between ecosystem components by creating an initial population of solutions and applying adaptive update strategies, and describes in detail the stages of AEO operation, including the consumption and decomposition phases, as well as different agent behavior strategies. The article introduces the features and advantages of this algorithm.
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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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MQL5 Wizard Techniques you should know (Part 72): Using Patterns of MACD and the OBV with Supervised Learning

MQL5 Wizard Techniques you should know (Part 72): Using Patterns of MACD and the OBV with Supervised Learning

We follow up on our last article, where we introduced the indicator pair of the MACD and the OBV, by looking at how this pairing could be enhanced with Machine Learning. MACD and OBV are a trend and volume complimentary pairing. Our machine learning approach uses a convolution neural network that engages the Exponential kernel in sizing its kernels and channels, when fine-tuning the forecasts of this indicator pairing. As always, this is done in a custom signal class file that works with the MQL5 wizard to assemble an Expert Advisor.
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Developing a Replay System (Part 46): Chart Trade Project (V)

Developing a Replay System (Part 46): Chart Trade Project (V)

Tired of wasting time searching for that very file that you application needs in order to work? How about including everything in the executable? This way you won't have to search for the things. I know that many people use this form of distribution and storage, but there is a much more suitable way. At least as far as the distribution of executable files and their storage is concerned. The method that will be presented here can be very useful, since you can use MetaTrader 5 itself as an excellent assistant, as well as MQL5. Furthermore, it is not that difficult to understand.
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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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MQL5 Wizard Techniques you should know (Part 21): Testing with Economic Calendar Data

MQL5 Wizard Techniques you should know (Part 21): Testing with Economic Calendar Data

Economic Calendar Data is not available for testing with Expert Advisors within Strategy Tester, by default. We look at how Databases could help in providing a work around this limitation. So, for this article we explore how SQLite databases can be used to archive Economic Calendar news such that wizard assembled Expert Advisors can use this to generate trade signals.
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Developing a Replay System (Part 62): Playing the service (III)

Developing a Replay System (Part 62): Playing the service (III)

In this article, we will begin to address the issue of tick excess that can impact application performance when using real data. This excess often interferes with the correct timing required to construct a one-minute bar in the appropriate window.
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Websockets for MetaTrader 5: Asynchronous client connections with the Windows API

Websockets for MetaTrader 5: Asynchronous client connections with the Windows API

This article details the development of a custom dynamically linked library designed to facilitate asynchronous websocket client connections for MetaTrader programs.
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Developing a Replay System (Part 43): Chart Trade Project (II)

Developing a Replay System (Part 43): Chart Trade Project (II)

Most people who want or dream of learning to program don't actually have a clue what they're doing. Their activity consists of trying to create things in a certain way. However, programming is not about tailoring suitable solutions. Doing it this way can create more problems than solutions. Here we will be doing something more advanced and therefore different.
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Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (V): AnalyticsPanel Class

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (V): AnalyticsPanel Class

In this discussion, we explore how to retrieve real-time market data and trading account information, perform various calculations, and display the results on a custom panel. To achieve this, we will dive deeper into developing an AnalyticsPanel class that encapsulates all these features, including panel creation. This effort is part of our ongoing expansion of the New Admin Panel EA, introducing advanced functionalities using modular design principles and best practices for code organization.
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MQL5 Trading Toolkit (Part 4): Developing a History Management EX5 Library

MQL5 Trading Toolkit (Part 4): Developing a History Management EX5 Library

Learn how to retrieve, process, classify, sort, analyze, and manage closed positions, orders, and deal histories using MQL5 by creating an expansive History Management EX5 Library in a detailed step-by-step approach.
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Population optimization algorithms: Bird Swarm Algorithm (BSA)

Population optimization algorithms: Bird Swarm Algorithm (BSA)

The article explores the bird swarm-based algorithm (BSA) inspired by the collective flocking interactions of birds in nature. The different search strategies of individuals in BSA, including switching between flight, vigilance and foraging behavior, make this algorithm multifaceted. It uses the principles of bird flocking, communication, adaptability, leading and following to efficiently find optimal solutions.
All about Automated Trading Championship: Interviews with the Participants'07
All about Automated Trading Championship: Interviews with the Participants'07

All about Automated Trading Championship: Interviews with the Participants'07

The published interviews of Championship 2007 bear the stamp of the results obtained during the preceding contest. The first Championship evoked a wide response on the internet and in printings. The leading developer of the MetaQuotes Software Corp. tells about changes made to the forthcoming Automated Trading Championship 2007. We put our questions to the developer of a well-known indicating complex ZUP, Eugeni Neumoin (nen) and spoke to an equity trader, Alexander Pozdnishev (AlexSilver).
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Price Action Analysis Toolkit Development (Part 18): Introducing Quarters Theory (III) — Quarters Board

Price Action Analysis Toolkit Development (Part 18): Introducing Quarters Theory (III) — Quarters Board

In this article, we enhance the original Quarters Script by introducing the Quarters Board, a tool that lets you toggle quarter levels directly on the chart without needing to revisit the code. You can easily activate or deactivate specific levels, and the EA also provides trend direction commentary to help you better understand market movements.
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Neural Networks in Trading: Mask-Attention-Free Approach to Price Movement Forecasting

Neural Networks in Trading: Mask-Attention-Free Approach to Price Movement Forecasting

In this article, we will discuss the Mask-Attention-Free Transformer (MAFT) method and its application in the field of trading. Unlike traditional Transformers that require data masking when processing sequences, MAFT optimizes the attention process by eliminating the need for masking, significantly improving computational efficiency.
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Building MQL5-Like Trade Classes in Python for MetaTrader 5

Building MQL5-Like Trade Classes in Python for MetaTrader 5

MetaTrader 5 python package provides an easy way to build trading applications for the MetaTrader 5 platform in the Python language, while being a powerful and useful tool, this module isn't as easy as MQL5 programming language when it comes to making an algorithmic trading solution. In this article, we are going to build trade classes similar to the one offered in MQL5 to create a similar syntax and make it easier to make trading robots in Python as in MQL5.
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Reimagining Classic Strategies (Part IV): SP500 and US Treasury Notes

Reimagining Classic Strategies (Part IV): SP500 and US Treasury Notes

In this series of articles, we analyze classical trading strategies using modern algorithms to determine whether we can improve the strategy using AI. In today's article, we revisit a classical approach for trading the SP500 using the relationship it has with US Treasury Notes.
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MQL5 Wizard Techniques you should know (Part 32): Regularization

MQL5 Wizard Techniques you should know (Part 32): Regularization

Regularization is a form of penalizing the loss function in proportion to the discrete weighting applied throughout the various layers of a neural network. We look at the significance, for some of the various regularization forms, this can have in test runs with a wizard assembled Expert Advisor.
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Neural Network in Practice: Pseudoinverse (II)

Neural Network in Practice: Pseudoinverse (II)

Since these articles are educational in nature and are not intended to show the implementation of specific functionality, we will do things a little differently in this article. Instead of showing how to apply factorization to obtain the inverse of a matrix, we will focus on factorization of the pseudoinverse. The reason is that there is no point in showing how to get the general coefficient if we can do it in a special way. Even better, the reader can gain a deeper understanding of why things happen the way they do. So, let's now figure out why hardware is replacing software over time.
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Data Science and ML (Part 35): NumPy in MQL5 – The Art of Making Complex Algorithms with Less Code

Data Science and ML (Part 35): NumPy in MQL5 – The Art of Making Complex Algorithms with Less Code

NumPy library is powering almost all the machine learning algorithms to the core in Python programming language, In this article we are going to implement a similar module which has a collection of all the complex code to aid us in building sophisticated models and algorithms of any kind.
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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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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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Developing a Replay System (Part 40): Starting the second phase (I)

Developing a Replay System (Part 40): Starting the second phase (I)

Today we'll talk about the new phase of the replay/simulator system. At this stage, the conversation will become truly interesting and quite rich in content. I strongly recommend that you read the article carefully and use the links provided in it. This will help you understand the content better.
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Artificial Bee Hive Algorithm (ABHA): Theory and methods

Artificial Bee Hive Algorithm (ABHA): Theory and methods

In this article, we will consider the Artificial Bee Hive Algorithm (ABHA) developed in 2009. The algorithm is aimed at solving continuous optimization problems. We will look at how ABHA draws inspiration from the behavior of a bee colony, where each bee has a unique role that helps them find resources more efficiently.
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Neural Networks in Trading: Exploring the Local Structure of Data

Neural Networks in Trading: Exploring the Local Structure of Data

Effective identification and preservation of the local structure of market data in noisy conditions is a critical task in trading. The use of the Self-Attention mechanism has shown promising results in processing such data; however, the classical approach does not account for the local characteristics of the underlying structure. In this article, I introduce an algorithm capable of incorporating these structural dependencies.
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MQL5 Wizard Techniques you should know (Part 62): Using Patterns of ADX and CCI with Reinforcement-Learning TRPO

MQL5 Wizard Techniques you should know (Part 62): Using Patterns of ADX and CCI with Reinforcement-Learning TRPO

The ADX Oscillator and CCI oscillator are trend following and momentum indicators that can be paired when developing an Expert Advisor. We continue where we left off in the last article by examining how in-use training, and updating of our developed model, can be made thanks to reinforcement-learning. We are using an algorithm we are yet to cover in these series, known as Trusted Region Policy Optimization. And, as always, Expert Advisor assembly by the MQL5 Wizard allows us to set up our model(s) for testing much quicker and also in a way where it can be distributed and tested with different signal types.
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Price Action Analysis Toolkit Development (Part 35): Training and Deploying Predictive Models

Price Action Analysis Toolkit Development (Part 35): Training and Deploying Predictive Models

Historical data is far from “trash”—it’s the foundation of any robust market analysis. In this article, we’ll take you step‑by‑step from collecting that history to using it to train a predictive model, and finally deploying that model for live price forecasts. Read on to learn how!
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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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Mastering Log Records (Part 7): How to Show Logs on Chart

Mastering Log Records (Part 7): How to Show Logs on Chart

Learn how to display logs directly on the MetaTrader chart in an organized way, with frames, titles and automatic scrolling. In this article, we show you how to create a visual log system using MQL5, ideal for monitoring what your robot is doing in real time.
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Feature Engineering With Python And MQL5 (Part II): Angle Of Price

Feature Engineering With Python And MQL5 (Part II): Angle Of Price

There are many posts in the MQL5 Forum asking for help calculating the slope of price changes. This article will demonstrate one possible way of calculating the angle formed by the changes in price in any market you wish to trade. Additionally, we will answer if engineering this new feature is worth the extra effort and time invested. We will explore if the slope of the price can improve any of our AI model's accuracy when forecasting the USDZAR pair on the M1.
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Mastering JSON: Create Your Own JSON Reader from Scratch in MQL5

Mastering JSON: Create Your Own JSON Reader from Scratch in MQL5

Experience a step-by-step guide on creating a custom JSON parser in MQL5, complete with object and array handling, error checking, and serialization. Gain practical insights into bridging your trading logic and structured data with this flexible solution for handling JSON in MetaTrader 5.
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Neural Networks in Trading: Injection of Global Information into Independent Channels (InjectTST)

Neural Networks in Trading: Injection of Global Information into Independent Channels (InjectTST)

Most modern multimodal time series forecasting methods use the independent channels approach. This ignores the natural dependence of different channels of the same time series. Smart use of two approaches (independent and mixed channels) is the key to improving the performance of the models.
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Developing a Replay System (Part 72): An Unusual Communication (I)

Developing a Replay System (Part 72): An Unusual Communication (I)

What we create today will be difficult to understand. Therefore, in this article I will only talk about the initial stage. Please read this article carefully, it is an important prerequisite before we proceed to the next step. The purpose of this material is purely didactic as we will only study and master the presented concepts, without practical application.
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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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MQL5 Trading Tools (Part 5): Creating a Rolling Ticker Tape for Real-Time Symbol Monitoring

MQL5 Trading Tools (Part 5): Creating a Rolling Ticker Tape for Real-Time Symbol Monitoring

In this article, we develop a rolling ticker tape in MQL5 for real-time monitoring of multiple symbols, displaying bid prices, spreads, and daily percentage changes with scrolling effects. We implement customizable fonts, colors, and scroll speeds to highlight price movements and trends effectively.
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MQL5 Wizard Techniques you should know (Part 66): Using Patterns of FrAMA and the Force Index with the Dot Product Kernel

MQL5 Wizard Techniques you should know (Part 66): Using Patterns of FrAMA and the Force Index with the Dot Product Kernel

The FrAMA Indicator and the Force Index Oscillator are trend and volume tools that could be paired when developing an Expert Advisor. We continue from our last article that introduced this pair by considering machine learning applicability to the pair. We are using a convolution neural network that uses the dot-product kernel in making forecasts with these indicators’ inputs. This is done in a custom signal class file that works with the MQL5 wizard to assemble an Expert Advisor.
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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.