Articles with MQL5 programming examples

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Access a huge collection of articles with code examples showing how to create indicators and trading robots for the MetaTrader platform in the MQL5 language. Source codes are attached to the articles, so you can open them in MetaEditor and run them to see how the applications work.

These articles will be useful both for those who have just started exploring automated trading and for professional traders with programming experience. They feature not only examples, but also contain new ideas.

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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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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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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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News Trading Made Easy (Part 1): Creating a Database

News Trading Made Easy (Part 1): Creating a Database

News trading can be complicated and overwhelming, in this article we will go through steps to obtain news data. Additionally we will learn about the MQL5 Economic Calendar and what it has to offer.
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Population optimization algorithms: Changing shape, shifting probability distributions and testing on Smart Cephalopod (SC)

Population optimization algorithms: Changing shape, shifting probability distributions and testing on Smart Cephalopod (SC)

The article examines the impact of changing the shape of probability distributions on the performance of optimization algorithms. We will conduct experiments using the Smart Cephalopod (SC) test algorithm to evaluate the efficiency of various probability distributions in the context of optimization problems.
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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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Population optimization algorithms: Simulated Annealing (SA) algorithm. Part I

Population optimization algorithms: Simulated Annealing (SA) algorithm. Part I

The Simulated Annealing algorithm is a metaheuristic inspired by the metal annealing process. In the article, we will conduct a thorough analysis of the algorithm and debunk a number of common beliefs and myths surrounding this widely known optimization method. The second part of the article will consider the custom Simulated Isotropic Annealing (SIA) algorithm.
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Build Self Optmising Expert Advisors in MQL5

Build Self Optmising Expert Advisors in MQL5

Build expert advisors that look forward and adjust themselves to any market.
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The Group Method of Data Handling: Implementing the Multilayered Iterative Algorithm in MQL5

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

In this article we describe the implementation of the Multilayered Iterative Algorithm of the Group Method of Data Handling in MQL5.
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Gain An Edge Over Any Market

Gain An Edge Over Any Market

Learn how you can get ahead of any market you wish to trade, regardless of your current level of skill.
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Population optimization algorithms: Nelder–Mead, or simplex search (NM) method

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.
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Population optimization algorithms: Differential Evolution (DE)

Population optimization algorithms: Differential Evolution (DE)

In this article, we will consider the algorithm that demonstrates the most controversial results of all those discussed previously - the differential evolution (DE) algorithm.
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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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Master MQL5 from beginner to pro (Part I): Getting started with programming

Master MQL5 from beginner to pro (Part I): Getting started with programming

This article is an introduction to a series of articles about programming. It is assumed here that the reader has never dealt with programming before. So, this series starts from the very basics. Programming knowledge level: Absolute Beginner.
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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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How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 7): ZigZag with Awesome Oscillator Indicators Signal

How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 7): ZigZag with Awesome Oscillator Indicators Signal

The multi-currency expert advisor in this article is an expert advisor or automated trading that uses ZigZag indicator which are filtered with the Awesome Oscillator or filter each other's signals.
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Developing a Replay System (Part 32): Order System (I)

Developing a Replay System (Part 32): Order System (I)

Of all the things that we have developed so far, this system, as you will probably notice and eventually agree, is the most complex. Now we need to do something very simple: make our system simulate the operation of a trading server. This need to accurately implement the way the trading server operates seems like a no-brainer. At least in words. But we need to do this so that the everything is seamless and transparent for the user of the replay/simulation system.
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Understanding Programming Paradigms (Part 2): An Object-Oriented Approach to Developing a Price Action Expert Advisor

Understanding Programming Paradigms (Part 2): An Object-Oriented Approach to Developing a Price Action Expert Advisor

Learn about the object-oriented programming paradigm and its application in MQL5 code. This second article goes deeper into the specifics of object-oriented programming, offering hands-on experience through a practical example. You'll learn how to convert our earlier developed procedural price action expert advisor using the EMA indicator and candlestick price data to object-oriented code.
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Integrating ML models with the Strategy Tester (Conclusion): Implementing a regression model for price prediction

Integrating ML models with the Strategy Tester (Conclusion): Implementing a regression model for price prediction

This article describes the implementation of a regression model based on a decision tree. The model should predict prices of financial assets. We have already prepared the data, trained and evaluated the model, as well as adjusted and optimized it. However, it is important to note that this model is intended for study purposes only and should not be used in real trading.
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Population optimization algorithms: Stochastic Diffusion Search (SDS)

Population optimization algorithms: Stochastic Diffusion Search (SDS)

The article discusses Stochastic Diffusion Search (SDS), which is a very powerful and efficient optimization algorithm based on the principles of random walk. The algorithm allows finding optimal solutions in complex multidimensional spaces, while featuring a high speed of convergence and the ability to avoid local extrema.
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Population optimization algorithms: Mind Evolutionary Computation (MEC) algorithm

Population optimization algorithms: Mind Evolutionary Computation (MEC) algorithm

The article considers the algorithm of the MEC family called the simple mind evolutionary computation algorithm (Simple MEC, SMEC). The algorithm is distinguished by the beauty of its idea and ease of implementation.
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Ready-made templates for including indicators to Expert Advisors (Part 3): Trend indicators

Ready-made templates for including indicators to Expert Advisors (Part 3): Trend indicators

In this reference article, we will look at standard indicators from the Trend Indicators category. We will create ready-to-use templates for indicator use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.
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Population optimization algorithms: Shuffled Frog-Leaping algorithm (SFL)

Population optimization algorithms: Shuffled Frog-Leaping algorithm (SFL)

The article presents a detailed description of the shuffled frog-leaping (SFL) algorithm and its capabilities in solving optimization problems. The SFL algorithm is inspired by the behavior of frogs in their natural environment and offers a new approach to function optimization. The SFL algorithm is an efficient and flexible tool capable of processing a variety of data types and achieving optimal solutions.
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DRAKON visual programming language — communication tool for MQL developers and customers

DRAKON visual programming language — communication tool for MQL developers and customers

DRAKON is a visual programming language designed to simplify interaction between specialists from different fields (biologists, physicists, engineers...) with programmers in Russian space projects (for example, in the Buran reusable spacecraft project). In this article, I will talk about how DRAKON makes the creation of algorithms accessible and intuitive, even if you have never encountered code, and also how it is easier for customers to explain their thoughts when ordering trading robots, and for programmers to make fewer mistakes in complex functions.
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Ready-made templates for including indicators to Expert Advisors (Part 2): Volume and Bill Williams indicators

Ready-made templates for including indicators to Expert Advisors (Part 2): Volume and Bill Williams indicators

In this article, we will look at standard indicators of the Volume and Bill Williams' indicators category. We will create ready-to-use templates for indicator use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.
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ALGLIB numerical analysis library in MQL5

ALGLIB numerical analysis library in MQL5

The article takes a quick look at the ALGLIB 3.19 numerical analysis library, its applications and new algorithms that can improve the efficiency of financial data analysis.
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How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 6): Two RSI indicators cross each other's lines

How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 6): Two RSI indicators cross each other's lines

The multi-currency expert advisor in this article is an expert advisor or trading robot that uses two RSI indicators with crossing lines, the Fast RSI which crosses with the Slow RSI.
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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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Ready-made templates for including indicators to Expert Advisors (Part 1): Oscillators

Ready-made templates for including indicators to Expert Advisors (Part 1): Oscillators

The article considers standard indicators from the oscillator category. We will create ready-to-use templates for their use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.
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Introduction to MQL5 (Part 2): Navigating Predefined Variables, Common Functions, and  Control Flow Statements

Introduction to MQL5 (Part 2): Navigating Predefined Variables, Common Functions, and Control Flow Statements

Embark on an illuminating journey with Part Two of our MQL5 series. These articles are not just tutorials, they're doorways to an enchanted realm where programming novices and wizards alike unite. What makes this journey truly magical? Part Two of our MQL5 series stands out with its refreshing simplicity, making complex concepts accessible to all. Engage with us interactively as we answer your questions, ensuring an enriching and personalized learning experience. Let's build a community where understanding MQL5 is an adventure for everyone. Welcome to the enchantment!
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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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Making a dashboard to display data in indicators and EAs

Making a dashboard to display data in indicators and EAs

In this article, we will create a dashboard class to be used in indicators and EAs. This is an introductory article in a small series of articles with templates for including and using standard indicators in Expert Advisors. I will start by creating a panel similar to the MetaTrader 5 data window.
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Understanding Programming Paradigms (Part 1): A Procedural Approach to Developing a Price Action Expert Advisor

Understanding Programming Paradigms (Part 1): A Procedural Approach to Developing a Price Action Expert Advisor

Learn about programming paradigms and their application in MQL5 code. This article explores the specifics of procedural programming, offering hands-on experience through a practical example. You'll learn how to develop a price action expert advisor using the EMA indicator and candlestick price data. Additionally, the article introduces you to the functional programming paradigm.
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Brute force approach to patterns search (Part VI): Cyclic optimization

Brute force approach to patterns search (Part VI): Cyclic optimization

In this article I will show the first part of the improvements that allowed me not only to close the entire automation chain for MetaTrader 4 and 5 trading, but also to do something much more interesting. From now on, this solution allows me to fully automate both creating EAs and optimization, as well as to minimize labor costs for finding effective trading configurations.
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Filtering and feature extraction in the frequency domain

Filtering and feature extraction in the frequency domain

In this article we explore the application of digital filters on time series represented in the frequency domain so as to extract unique features that may be useful to prediction models.
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Data label for time series mining (Part 4):Interpretability Decomposition Using Label Data

Data label for time series mining (Part 4):Interpretability Decomposition Using Label Data

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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Developing a Replay System — Market simulation (Part 17): Ticks and more ticks (I)

Developing a Replay System — Market simulation (Part 17): Ticks and more ticks (I)

Here we will see how to implement something really interesting, but at the same time very difficult due to certain points that can be very confusing. The worst thing that can happen is that some traders who consider themselves professionals do not know anything about the importance of these concepts in the capital market. Well, although we focus here on programming, understanding some of the issues involved in market trading is paramount to what we are going to implement.
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Trade transactions. Request and response structures, description and logging

Trade transactions. Request and response structures, description and logging

The article considers handling trade request structures, namely creating a request, its preliminary verification before sending it to the server, the server's response to a trade request and the structure of trade transactions. We will create simple and convenient functions for sending trading orders to the server and, based on everything discussed, create an EA informing of trade transactions.
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Developing a quality factor for Expert Advisors

Developing a quality factor for Expert Advisors

In this article, we will see how to develop a quality score that your Expert Advisor can display in the strategy tester. We will look at two well-known calculation methods – Van Tharp and Sunny Harris.
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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.