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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Archery Algorithm (AA)

Archery Algorithm (AA)

The article takes a detailed look at the archery-inspired optimization algorithm, with an emphasis on using the roulette method as a mechanism for selecting promising areas for "arrows". The method allows evaluating the quality of solutions and selecting the most promising positions for further study.
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Category Theory in MQL5 (Part 5): Equalizers

Category Theory in MQL5 (Part 5): Equalizers

Category Theory is a diverse and expanding branch of Mathematics which is only recently getting some coverage in the MQL5 community. These series of articles look to explore and examine some of its concepts & axioms with the overall goal of establishing an open library that provides insight while also hopefully furthering the use of this remarkable field in Traders' strategy development.
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From Novice to Expert: Animated News Headline Using MQL5 (IX) — Multiple Symbol Management on a single chart for News Trading

From Novice to Expert: Animated News Headline Using MQL5 (IX) — Multiple Symbol Management on a single chart for News Trading

News trading often requires managing multiple positions and symbols within a very short time due to heightened volatility. In today’s discussion, we address the challenges of multi-symbol trading by integrating this feature into our News Headline EA. Join us as we explore how algorithmic trading with MQL5 makes multi-symbol trading more efficient and powerful.
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Functions for activating neurons during training: The key to fast convergence?

Functions for activating neurons during training: The key to fast convergence?

This article presents a study of the interaction of different activation functions with optimization algorithms in the context of neural network training. Particular attention is paid to the comparison of the classical ADAM and its population version when working with a wide range of activation functions, including the oscillating ACON and Snake functions. Using a minimalistic MLP (1-1-1) architecture and a single training example, the influence of activation functions on the optimization is isolated from other factors. The article proposes an approach to manage network weights through the boundaries of activation functions and a weight reflection mechanism, which allows avoiding problems with saturation and stagnation in training.
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Neural Networks in Trading: Multi-Task Learning Based on the ResNeXt Model

Neural Networks in Trading: Multi-Task Learning Based on the ResNeXt Model

A multi-task learning framework based on ResNeXt optimizes the analysis of financial data, taking into account its high dimensionality, nonlinearity, and time dependencies. The use of group convolution and specialized heads allows the model to effectively extract key features from the input data.
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Billiards Optimization Algorithm (BOA)

Billiards Optimization Algorithm (BOA)

The BOA method is inspired by the classic game of billiards and simulates the search for optimal solutions as a game with balls trying to fall into pockets representing the best results. In this article, we will consider the basics of BOA, its mathematical model, and its efficiency in solving various optimization problems.
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Trading with the MQL5 Economic Calendar (Part 4): Implementing Real-Time News Updates in the Dashboard

Trading with the MQL5 Economic Calendar (Part 4): Implementing Real-Time News Updates in the Dashboard

This article enhances our Economic Calendar dashboard by implementing real-time news updates to keep market information current and actionable. We integrate live data fetching techniques in MQL5 to update events on the dashboard continuously, improving the responsiveness of the interface. This update ensures that we can access the latest economic news directly from the dashboard, optimizing trading decisions based on the freshest data.
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Developing a Replay System — Market simulation (Part 14): Birth of the SIMULATOR (IV)

Developing a Replay System — Market simulation (Part 14): Birth of the SIMULATOR (IV)

In this article we will continue the simulator development stage. this time we will see how to effectively create a RANDOM WALK type movement. This type of movement is very intriguing because it forms the basis of everything that happens in the capital market. In addition, we will begin to understand some concepts that are fundamental to those conducting market analysis.
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Developing a Replay System — Market simulation (Part 11): Birth of the SIMULATOR (I)

Developing a Replay System — Market simulation (Part 11): Birth of the SIMULATOR (I)

In order to use the data that forms the bars, we must abandon replay and start developing a simulator. We will use 1 minute bars because they offer the least amount of difficulty.
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Category Theory in MQL5 (Part 22): A different look at Moving Averages

Category Theory in MQL5 (Part 22): A different look at Moving Averages

In this article we attempt to simplify our illustration of concepts covered in these series by dwelling on just one indicator, the most common and probably the easiest to understand. The moving average. In doing so we consider significance and possible applications of vertical natural transformations.
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Design Patterns in software development and MQL5 (Part 2): Structural Patterns

Design Patterns in software development and MQL5 (Part 2): Structural Patterns

In this article, we will continue our articles about Design Patterns after learning how much this topic is more important for us as developers to develop extendable, reliable applications not only by the MQL5 programming language but others as well. We will learn about another type of Design Patterns which is the structural one to learn how to design systems by using what we have as classes to form larger structures.
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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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Artificial Electric Field Algorithm (AEFA)

Artificial Electric Field Algorithm (AEFA)

The article presents an artificial electric field algorithm (AEFA) inspired by Coulomb's law of electrostatic force. The algorithm simulates electrical phenomena to solve complex optimization problems using charged particles and their interactions. AEFA exhibits unique properties in the context of other algorithms related to laws of nature.
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Neural Network in Practice: The First Neuron

Neural Network in Practice: The First Neuron

In this article, we'll start building something simple and humble: a neuron. We will program it with a very small amount of MQL5 code. The neuron worked great in my tests. Let's go back a bit in this series of articles about neural networks to understand what I'm talking about.
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Integrate Your Own LLM into EA (Part 3): Training Your Own LLM with CPU

Integrate Your Own LLM into EA (Part 3): Training Your Own LLM with CPU

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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Neural networks made easy (Part 45): Training state exploration skills

Neural networks made easy (Part 45): Training state exploration skills

Training useful skills without an explicit reward function is one of the main challenges in hierarchical reinforcement learning. Previously, we already got acquainted with two algorithms for solving this problem. But the question of the completeness of environmental research remains open. This article demonstrates a different approach to skill training, the use of which directly depends on the current state of the system.
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Developing a multi-currency Expert Advisor (Part 6): Automating the selection of an instance group

Developing a multi-currency Expert Advisor (Part 6): Automating the selection of an instance group

After optimizing the trading strategy, we receive sets of parameters. We can use them to create several instances of trading strategies combined in one EA. Previously, we did this manually. Here we will try to automate this process.
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Self Optimizing Expert Advisors in MQL5 (Part 10): Matrix Factorization

Self Optimizing Expert Advisors in MQL5 (Part 10): Matrix Factorization

Factorization is a mathematical process used to gain insights into the attributes of data. When we apply factorization to large sets of market data — organized in rows and columns — we can uncover patterns and characteristics of the market. Factorization is a powerful tool, and this article will show how you can use it within the MetaTrader 5 terminal, through the MQL5 API, to gain more profound insights into your market data.
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Neural networks made easy (Part 51): Behavior-Guided Actor-Critic (BAC)

Neural networks made easy (Part 51): Behavior-Guided Actor-Critic (BAC)

The last two articles considered the Soft Actor-Critic algorithm, which incorporates entropy regularization into the reward function. This approach balances environmental exploration and model exploitation, but it is only applicable to stochastic models. The current article proposes an alternative approach that is applicable to both stochastic and deterministic models.
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Combine Fundamental And Technical Analysis Strategies in MQL5 For Beginners

Combine Fundamental And Technical Analysis Strategies in MQL5 For Beginners

In this article, we will discuss how to integrate trend following and fundamental principles seamlessly into one Expert Advisors to build a strategy that is more robust. This article will demonstrate how easy it is for anyone to get up and running building customized trading algorithms using MQL5.
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MQL5 Wizard Techniques you should know (Part 16): Principal Component Analysis with Eigen Vectors

MQL5 Wizard Techniques you should know (Part 16): Principal Component Analysis with Eigen Vectors

Principal Component Analysis, a dimensionality reducing technique in data analysis, is looked at in this article, with how it could be implemented with Eigen values and vectors. As always, we aim to develop a prototype expert-signal-class usable in the MQL5 wizard.
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Black Hole Algorithm (BHA)

Black Hole Algorithm (BHA)

The Black Hole Algorithm (BHA) uses the principles of black hole gravity to optimize solutions. In this article, we will look at how BHA attracts the best solutions while avoiding local extremes, and why this algorithm has become a powerful tool for solving complex problems. Learn how simple ideas can lead to impressive results in the world of optimization.
Interview with Sergey Nikitin (ATC 2011)
Interview with Sergey Nikitin (ATC 2011)

Interview with Sergey Nikitin (ATC 2011)

In the second week of the competition, the Expert Advisor of Sergey Nikitin (VNIK) trading on two currency pairs EURUSD and EURJPY got featured on the very top drawing away from the rest. Multicurrency Expert Advisors always attract attention in the Championship, especially those that show good results. We talked with Sergey about the role of luck in a trader's life and his way of trading.
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Reimagining Classic Strategies (Part V): Multiple Symbol Analysis on USDZAR

Reimagining Classic Strategies (Part V): Multiple Symbol Analysis on USDZAR

In this series of articles, we revisit classical strategies to see if we can improve the strategy using AI. In today's article, we will examine a popular strategy of multiple symbol analysis using a basket of correlated securities, we will focus on the exotic USDZAR currency pair.
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Statistical Arbitrage Through Cointegrated Stocks (Part 1): Engle-Granger and Johansen Cointegration Tests

Statistical Arbitrage Through Cointegrated Stocks (Part 1): Engle-Granger and Johansen Cointegration Tests

This article aims to provide a trader-friendly, gentle introduction to the most common cointegration tests, along with a simple guide to understanding their results. The Engle-Granger and Johansen cointegration tests can reveal statistically significant pairs or groups of assets that share long-term dynamics. The Johansen test is especially useful for portfolios with three or more assets, as it calculates the strength of cointegrating vectors all at once.
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MQL5 Wizard Techniques you should know (Part 56): Bill Williams Fractals

MQL5 Wizard Techniques you should know (Part 56): Bill Williams Fractals

The Fractals by Bill Williams is a potent indicator that is easy to overlook when one initially spots it on a price chart. It appears too busy and probably not incisive enough. We aim to draw away this curtain on this indicator by examining what its various patterns could accomplish when examined with forward walk tests on all, with wizard assembled Expert Advisor.
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MQL5 Trading Tools (Part 4): Improving the Multi-Timeframe Scanner Dashboard with Dynamic Positioning and Toggle Features

MQL5 Trading Tools (Part 4): Improving the Multi-Timeframe Scanner Dashboard with Dynamic Positioning and Toggle Features

In this article, we upgrade the MQL5 Multi-Timeframe Scanner Dashboard with movable and toggle features. We enable dragging the dashboard and a minimize/maximize option for better screen use. We implement and test these enhancements for improved trading flexibility.
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Moving to MQL5 Algo Forge (Part 3): Using External Repositories in Your Own Projects

Moving to MQL5 Algo Forge (Part 3): Using External Repositories in Your Own Projects

Let's explore how you can start integrating external code from any repository in the MQL5 Algo Forge storage into your own project. In this article, we finally turn to this promising, yet more complex, task: how to practically connect and use libraries from third-party repositories within MQL5 Algo Forge.
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DoEasy. Service functions (Part 1): Price patterns

DoEasy. Service functions (Part 1): Price patterns

In this article, we will start developing methods for searching for price patterns using timeseries data. A pattern has a certain set of parameters, common to any type of patterns. All data of this kind will be concentrated in the object class of the base abstract pattern. In the current article, we will create an abstract pattern class and a Pin Bar pattern class.
Interview with Matúš German (ATC 2011)
Interview with Matúš German (ATC 2011)

Interview with Matúš German (ATC 2011)

On the second day of the Championship the Expert Advisor created by Matúš German (gery18) increased its capital by 2.5 times and took the lead being ahead of all competitors. Matúš himself doubts his Expert Advisor will win, he thinks that luck and high risk were the reasons of such unexpected rise.
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Price Action Analysis Toolkit Development (Part 8): Metrics Board

Price Action Analysis Toolkit Development (Part 8): Metrics Board

As one of the most powerful Price Action analysis toolkits, the Metrics Board is designed to streamline market analysis by instantly providing essential market metrics with just a click of a button. Each button serves a specific function, whether it’s analyzing high/low trends, volume, or other key indicators. This tool delivers accurate, real-time data when you need it most. Let’s dive deeper into its features in this article.
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Neural Networks in Trading: Lightweight Models for Time Series Forecasting

Neural Networks in Trading: Lightweight Models for Time Series Forecasting

Lightweight time series forecasting models achieve high performance using a minimum number of parameters. This, in turn, reduces the consumption of computing resources and speeds up decision-making. Despite being lightweight, such models achieve forecast quality comparable to more complex ones.
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Formulating Dynamic Multi-Pair EA (Part 2): Portfolio Diversification and Optimization

Formulating Dynamic Multi-Pair EA (Part 2): Portfolio Diversification and Optimization

Portfolio Diversification and Optimization strategically spreads investments across multiple assets to minimize risk while selecting the ideal asset mix to maximize returns based on risk-adjusted performance metrics.
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Neural Networks in Trading: Memory Augmented Context-Aware Learning (MacroHFT) for Cryptocurrency Markets

Neural Networks in Trading: Memory Augmented Context-Aware Learning (MacroHFT) for Cryptocurrency Markets

I invite you to explore the MacroHFT framework, which applies context-aware reinforcement learning and memory to improve high-frequency cryptocurrency trading decisions using macroeconomic data and adaptive agents.
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Developing Trading Strategy: Pseudo Pearson Correlation Approach

Developing Trading Strategy: Pseudo Pearson Correlation Approach

Generating new indicators from existing ones offers a powerful way to enhance trading analysis. By defining a mathematical function that integrates the outputs of existing indicators, traders can create hybrid indicators that consolidate multiple signals into a single, efficient tool. This article introduces a new indicator built from three oscillators using a modified version of the Pearson correlation function, which we call the Pseudo Pearson Correlation (PPC). The PPC indicator aims to quantify the dynamic relationship between oscillators and apply it within a practical trading strategy.
Interview with Ilnur Khasanov (ATC 2011)
Interview with Ilnur Khasanov (ATC 2011)

Interview with Ilnur Khasanov (ATC 2011)

The Expert Advisor of Ilnur Khasanov (aharata) is holding its place in our TOP-10 chart of the Automated Trading Championship 2011 participants from the third week already, though Ilnur's acquaintance with Forex has started only a year ago. The idea that forms the basis of the Expert Advisor is simple but the trading robot contains self-optimization elements. Perhaps, that is the key to its survival? Besides, the author had to change the Expert Advisor planned to be submitted for the Championship...
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Developing a Replay System — Market simulation (Part 09): Custom events

Developing a Replay System — Market simulation (Part 09): Custom events

Here we'll see how custom events are triggered and how the indicator reports the state of the replay/simulation service.
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Building A Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (II)

Building A Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (II)

The number of strategies that can be integrated into an Expert Advisor is virtually limitless. However, each additional strategy increases the complexity of the algorithm. By incorporating multiple strategies, an Expert Advisor can better adapt to varying market conditions, potentially enhancing its profitability. Today, we will explore how to implement MQL5 for one of the prominent strategies developed by Richard Donchian, as we continue to enhance the functionality of our Trend Constraint Expert.
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From Basic to Intermediate: SWITCH Statement

From Basic to Intermediate: SWITCH Statement

In this article, we will learn how to use the SWITCH statement in its simplest and most basic form. 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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Creating a Trading Administrator Panel in MQL5 (Part II): Enhancing Responsiveness and Quick Messaging

Creating a Trading Administrator Panel in MQL5 (Part II): Enhancing Responsiveness and Quick Messaging

In this article, we will enhance the responsiveness of the Admin Panel that we previously created. Additionally, we will explore the significance of quick messaging in the context of trading signals.