Articles on the MQL5 programming and use of trading robots

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Expert Advisors created for the MetaTrader platform perform a variety of functions implemented by their developers. Trading robots can track financial symbols 24 hours a day, copy deals, create and send reports, analyze news and even provide specific custom graphical interface.

The articles describe programming techniques, mathematical ideas for data processing, tips on creating and ordering of trading robots.

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Learn how to design a trading system by VIDYA

Learn how to design a trading system by VIDYA

Welcome to a new article from our series about learning how to design a trading system by the most popular technical indicators, in this article we will learn about a new technical tool and learn how to design a trading system by Variable Index Dynamic Average (VIDYA).
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Data Science and Machine Learning (Part 03): Matrix Regressions

Data Science and Machine Learning (Part 03): Matrix Regressions

This time our models are being made by matrices, which allows flexibility while it allows us to make powerful models that can handle not only five independent variables but also many variables as long as we stay within the calculations limits of a computer, this article is going to be an interesting read, that's for sure.
The Prototype of a Trading Robot
The Prototype of a Trading Robot

The Prototype of a Trading Robot

This article summarizes and systematizes the principles of creating algorithms and elements of trading systems. The article considers designing of expert algorithm. As an example the CExpertAdvisor class is considered, which can be used for quick and easy development of trading systems.
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Mastering Market Dynamics: Creating a Support and Resistance Strategy Expert Advisor (EA)

Mastering Market Dynamics: Creating a Support and Resistance Strategy Expert Advisor (EA)

A comprehensive guide to developing an automated trading algorithm based on the Support and Resistance strategy. Detailed information on all aspects of creating an expert advisor in MQL5 and testing it in MetaTrader 5 – from analyzing price range behaviors to risk management.
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Neural Networks in Trading: A Multi-Agent Self-Adaptive Model (MASA)

Neural Networks in Trading: A Multi-Agent Self-Adaptive Model (MASA)

I invite you to get acquainted with the Multi-Agent Self-Adaptive (MASA) framework, which combines reinforcement learning and adaptive strategies, providing a harmonious balance between profitability and risk management in turbulent market conditions.
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Automating Trading Strategies in MQL5 (Part 8): Building an Expert Advisor with Butterfly Harmonic Patterns

Automating Trading Strategies in MQL5 (Part 8): Building an Expert Advisor with Butterfly Harmonic Patterns

In this article, we build an MQL5 Expert Advisor to detect Butterfly harmonic patterns. We identify pivot points and validate Fibonacci levels to confirm the pattern. We then visualize the pattern on the chart and automatically execute trades when confirmed.
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Learn how to design a trading system by Parabolic SAR

Learn how to design a trading system by Parabolic SAR

In this article, we will continue our series about how to design a trading system using the most popular indicators. In this article, we will learn about the Parabolic SAR indicator in detail and how we can design a trading system to be used in MetaTrader 5 using some simple strategies.
Freelance Jobs on MQL5.com - Developer's Favorite Place
Freelance Jobs on MQL5.com - Developer's Favorite Place

Freelance Jobs on MQL5.com - Developer's Favorite Place

Developers of trading robots no longer need to market their services to traders that require Expert Advisors - as now they will find you. Already, thousands of traders place orders to MQL5 freelance developers, and pay for work in on MQL5.com. For 4 years, this service facilitated three thousand traders to pay for more than 10 000 jobs performed. And the activity of traders and developers is constantly growing!
Separate optimization of a strategy on trend and flat conditions
Separate optimization of a strategy on trend and flat conditions

Separate optimization of a strategy on trend and flat conditions

The article considers applying the separate optimization method during various market conditions. Separate optimization means defining trading system's optimal parameters by optimizing for an uptrend and downtrend separately. To reduce the effect of false signals and improve profitability, the systems are made flexible, meaning they have some specific set of settings or input data, which is justified because the market behavior is constantly changing.
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Neural networks made easy (Part 3): Convolutional networks

Neural networks made easy (Part 3): Convolutional networks

As a continuation of the neural network topic, I propose considering convolutional neural networks. This type of neural network are usually applied to analyzing visual imagery. In this article, we will consider the application of these networks in the financial markets.
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How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 1): Indicator Signals based on ADX in combination with Parabolic SAR

How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 1): Indicator Signals based on ADX in combination with Parabolic SAR

The Multi-Currency Expert Advisor in this article is Expert Advisor or trading robot that can trade (open orders, close orders and manage orders an more) for more than 1 symbol pair only from one symbol chart.
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MQL5 Integration: Python

MQL5 Integration: Python

Python is a well-known and popular programming language with many features, especially in the fields of finance, data science, Artificial Intelligence, and Machine Learning. Python is a powerful tool that can be useful in trading as well. MQL5 allows us to use this powerful language as an integration to get our objectives done effectively. In this article, we will share how we can use Python as an integration in MQL5 after learning some basic information about Python.
Other classes in DoEasy library (Part 66): MQL5.com Signals collection class
Other classes in DoEasy library (Part 66): MQL5.com Signals collection class

Other classes in DoEasy library (Part 66): MQL5.com Signals collection class

In this article, I will create the signal collection class of the MQL5.com Signals service with the functions for managing signals. Besides, I will improve the Depth of Market snapshot object class for displaying the total DOM buy and sell volumes.
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Learn how to design a trading system by Standard Deviation

Learn how to design a trading system by Standard Deviation

Here is a new article in our series about how to design a trading system by the most popular technical indicators in MetaTrader 5 trading platform. In this new article, we will learn how to design a trading system by Standard Deviation indicator.
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Brute force approach to pattern search

Brute force approach to pattern search

In this article, we will search for market patterns, create Expert Advisors based on the identified patterns, and check how long these patterns remain valid, if they ever retain their validity.
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Developing a trading Expert Advisor from scratch (Part 19): New order system (II)

Developing a trading Expert Advisor from scratch (Part 19): New order system (II)

In this article, we will develop a graphical order system of the "look what happens" type. Please note that we are not starting from scratch this time, but we will modify the existing system by adding more objects and events on the chart of the asset we are trading.
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Introduction to MQL5 (Part 1): A Beginner's Guide into Algorithmic Trading

Introduction to MQL5 (Part 1): A Beginner's Guide into Algorithmic Trading

Dive into the fascinating realm of algorithmic trading with our beginner-friendly guide to MQL5 programming. Discover the essentials of MQL5, the language powering MetaTrader 5, as we demystify the world of automated trading. From understanding the basics to taking your first steps in coding, this article is your key to unlocking the potential of algorithmic trading even without a programming background. Join us on a journey where simplicity meets sophistication in the exciting universe of MQL5.
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Pair trading

Pair trading

In this article, we will consider pair trading, namely what its principles are and if there are any prospects for its practical application. We will also try to create a pair trading strategy.
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Experiments with neural networks (Part 1): Revisiting geometry

Experiments with neural networks (Part 1): Revisiting geometry

In this article, I will use experimentation and non-standard approaches to develop a profitable trading system and check whether neural networks can be of any help for traders.
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Modified Grid-Hedge EA in MQL5 (Part I): Making a Simple Hedge EA

Modified Grid-Hedge EA in MQL5 (Part I): Making a Simple Hedge EA

We will be creating a simple hedge EA as a base for our more advanced Grid-Hedge EA, which will be a mixture of classic grid and classic hedge strategies. By the end of this article, you will know how to create a simple hedge strategy, and you will also get to know what people say about whether this strategy is truly 100% profitable.
Controlling the Slope of Balance Curve During Work of an Expert Advisor
Controlling the Slope of Balance Curve During Work of an Expert Advisor

Controlling the Slope of Balance Curve During Work of an Expert Advisor

Finding rules for a trade system and programming them in an Expert Advisor is a half of the job. Somehow, you need to correct the operation of the Expert Advisor as it accumulates the results of trading. This article describes one of approaches, which allows improving performance of an Expert Advisor through creation of a feedback that measures slope of the balance curve.
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Learn how to design a trading system by Williams PR

Learn how to design a trading system by Williams PR

A new article in our series about learning how to design a trading system by the most popular technical indicators by MQL5 to be used in the MetaTrader 5. In this article, we will learn how to design a trading system by the Williams' %R indicator.
Graphics in DoEasy library (Part 73): Form object of a graphical element
Graphics in DoEasy library (Part 73): Form object of a graphical element

Graphics in DoEasy library (Part 73): Form object of a graphical element

The article opens up a new large section of the library for working with graphics. In the current article, I will create the mouse status object, the base object of all graphical elements and the class of the form object of the library graphical elements.
Practical Use of Kohonen Neural Networks in Algorithmic Trading. Part II. Optimizing and forecasting
Practical Use of Kohonen Neural Networks in Algorithmic Trading. Part II. Optimizing and forecasting

Practical Use of Kohonen Neural Networks in Algorithmic Trading. Part II. Optimizing and forecasting

Based on universal tools designed for working with Kohonen networks, we construct the system of analyzing and selecting the optimal EA parameters and consider forecasting time series. In Part I, we corrected and improved the publicly available neural network classes, having added necessary algorithms. Now, it is time to apply them to practice.
Swaps (Part I): Locking and Synthetic Positions
Swaps (Part I): Locking and Synthetic Positions

Swaps (Part I): Locking and Synthetic Positions

In this article I will try to expand the classic concept of swap trading methods. I will explain why I have come to the conclusion that this concept deserves special attention and is absolutely recommended for study.
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Learn how to design a trading system by OBV

Learn how to design a trading system by OBV

This is a new article to continue our series for beginners about how to design a trading system based on some of the popular indicators. We will learn a new indicator that is On Balance Volume (OBV), and we will learn how we can use it and design a trading system based on it.
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Trader-friendly stop loss and take profit

Trader-friendly stop loss and take profit

Stop loss and take profit can have a significant impact on trading results. In this article, we will look at several ways to find optimal stop order values.
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Using JSON Data API in your MQL projects

Using JSON Data API in your MQL projects

Imagine that you can use data that is not found in MetaTrader, you only get data from indicators by price analysis and technical analysis. Now imagine that you can access data that will take your trading power steps higher. You can multiply the power of the MetaTrader software if you mix the output of other software, macro analysis methods, and ultra-advanced tools through the ​​API data. In this article, we will teach you how to use APIs and introduce useful and valuable API data services.
Prices in DoEasy library (Part 64): Depth of Market, classes of DOM snapshot and snapshot series objects
Prices in DoEasy library (Part 64): Depth of Market, classes of DOM snapshot and snapshot series objects

Prices in DoEasy library (Part 64): Depth of Market, classes of DOM snapshot and snapshot series objects

In this article, I will create two classes (the class of DOM snapshot object and the class of DOM snapshot series object) and test creation of the DOM data series.
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Learn how to design a trading system by Accelerator Oscillator

Learn how to design a trading system by Accelerator Oscillator

A new article from our series about how to create simple trading systems by the most popular technical indicators. We will learn about a new one which is the Accelerator Oscillator indicator and we will learn how to design a trading system using it.
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Creating an MQL5-Telegram Integrated Expert Advisor (Part 1): Sending Messages from MQL5 to Telegram

Creating an MQL5-Telegram Integrated Expert Advisor (Part 1): Sending Messages from MQL5 to Telegram

In this article, we create an Expert Advisor (EA) in MQL5 to send messages to Telegram using a bot. We set up the necessary parameters, including the bot's API token and chat ID, and then perform an HTTP POST request to deliver the messages. Later, we handle the response to ensure successful delivery and troubleshoot any issues that arise in case of failure. This ensures we send messages from MQL5 to Telegram via the created bot.
Movement continuation model - searching on the chart and execution statistics
Movement continuation model - searching on the chart and execution statistics

Movement continuation model - searching on the chart and execution statistics

This article provides programmatic definition of one of the movement continuation models. The main idea is defining two waves — the main and the correction one. For extreme points, I apply fractals as well as "potential" fractals - extreme points that have not yet formed as fractals.
Deep Neural Networks (Part III). Sample selection and dimensionality reduction
Deep Neural Networks (Part III). Sample selection and dimensionality reduction

Deep Neural Networks (Part III). Sample selection and dimensionality reduction

This article is a continuation of the series of articles about deep neural networks. Here we will consider selecting samples (removing noise), reducing the dimensionality of input data and dividing the data set into the train/val/test sets during data preparation for training the neural network.
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Neural networks made easy (Part 29): Advantage Actor-Critic algorithm

Neural networks made easy (Part 29): Advantage Actor-Critic algorithm

In the previous articles of this series, we have seen two reinforced learning algorithms. Each of them has its own advantages and disadvantages. As often happens in such cases, next comes the idea to combine both methods into an algorithm, using the best of the two. This would compensate for the shortcomings of each of them. One of such methods will be discussed in this article.
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Brute force approach to pattern search (Part III): New horizons

Brute force approach to pattern search (Part III): New horizons

This article provides a continuation to the brute force topic, and it introduces new opportunities for market analysis into the program algorithm, thereby accelerating the speed of analysis and improving the quality of results. New additions enable the highest-quality view of global patterns within this approach.
A scientific approach to the development of trading algorithms
A scientific approach to the development of trading algorithms

A scientific approach to the development of trading algorithms

The article considers the methodology for developing trading algorithms, in which a consistent scientific approach is used to analyze possible price patterns and to build trading algorithms based on these patterns. Development ideals are demonstrated using examples.
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How to deal with lines using MQL5

How to deal with lines using MQL5

In this article, you will find your way to deal with the most important lines like trendlines, support, and resistance by MQL5.
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Python-MetaTrader 5 Strategy Tester (Part 01): Trade Simulator

Python-MetaTrader 5 Strategy Tester (Part 01): Trade Simulator

The MetaTrader 5 module offered in Python provides a convenient way of opening trades in the MetaTrader 5 app using Python, but it has a huge problem, it doesn't have the strategy tester capability present in the MetaTrader 5 app, In this article series, we will build a framework for back testing your trading strategies in Python environments.
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Neural Networks Made Easy (Part 96): Multi-Scale Feature Extraction (MSFformer)

Neural Networks Made Easy (Part 96): Multi-Scale Feature Extraction (MSFformer)

Efficient extraction and integration of long-term dependencies and short-term features remain an important task in time series analysis. Their proper understanding and integration are necessary to create accurate and reliable predictive models.
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How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 2): Indicator Signals: Multi Timeframe Parabolic SAR Indicator

How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 2): Indicator Signals: Multi Timeframe Parabolic SAR Indicator

The Multi-Currency Expert Advisor in this article is Expert Advisor or trading robot that can trade (open orders, close orders and manage orders for example: Trailing Stop Loss and Trailing Profit) for more than 1 symbol pair only from one symbol chart. This time we will use only 1 indicator, namely Parabolic SAR or iSAR in multi-timeframes starting from PERIOD_M15 to PERIOD_D1.