Articles with examples of trading robots developed in MQL5

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An Expert Advisor is the 'pinnacle' of programming and the desired goal of every automated trading developer. Read the articles in this section to create your own trading robot. By following the described steps you will learn how to create, debug and test automated trading systems.

The articles not only teach MQL5 programming, but also show how to implement trading ideas and techniques. You will learn how to program a trailing stop, how to apply money management, how to get the indicator values, and much more.

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Creating an EA that works automatically (Part 06): Account types (I)

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. Our EA in its current state can work in any situation but it is not yet ready for automation. We still have to work on a few points.
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Automating Trading Strategies in MQL5 (Part 3): The Zone Recovery RSI System for Dynamic Trade Management

In this article, we create a Zone Recovery RSI EA System in MQL5, using RSI signals to trigger trades and a recovery strategy to manage losses. We implement a "ZoneRecovery" class to automate trade entries, recovery logic, and position management. The article concludes with backtesting insights to optimize performance and enhance the EA’s effectiveness.
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Neural networks made easy (Part 13): Batch Normalization

In the previous article, we started considering methods aimed at improving neural network training quality. In this article, we will continue this topic and will consider another approach — batch data normalization.
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Automating Trading Strategies in MQL5 (Part 7): Building a Grid Trading EA with Dynamic Lot Scaling

In this article, we build a grid trading expert advisor in MQL5 that uses dynamic lot scaling. We cover the strategy design, code implementation, and backtesting process. Finally, we share key insights and best practices for optimizing the automated trading system.
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Creating an Interactive Graphical User Interface in MQL5 (Part 1): Making the Panel

This article explores the fundamental steps in crafting and implementing a Graphical User Interface (GUI) panel using MetaQuotes Language 5 (MQL5). Custom utility panels enhance user interaction in trading by simplifying common tasks and visualizing essential trading information. By creating custom panels, traders can streamline their workflow and save time during trading operations.
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Automating Trading Strategies in MQL5 (Part 10): Developing the Trend Flat Momentum Strategy

In this article, we develop an Expert Advisor in MQL5 for the Trend Flat Momentum Strategy. We combine a two moving averages crossover with RSI and CCI momentum filters to generate trade signals. We also cover backtesting and potential enhancements for real-world performance.
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Cascade Order Trading Strategy Based on EMA Crossovers for MetaTrader 5

The article guides in demonstrating an automated algorithm based on EMA Crossovers for MetaTrader 5. Detailed information on all aspects of demonstrating an Expert Advisor in MQL5 and testing it in MetaTrader 5 - from analyzing price range behaviors to risk management.
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Experiments with neural networks (Part 6): Perceptron as a self-sufficient tool for price forecast

The article provides an example of using a perceptron as a self-sufficient price prediction tool by showcasing general concepts and the simplest ready-made Expert Advisor followed by the results of its optimization.
Prices in DoEasy library (part 60): Series list of symbol tick data

Prices in DoEasy library (part 60): Series list of symbol tick data

In this article, I will create the list for storing tick data of a single symbol and check its creation and retrieval of required data in an EA. Tick data lists that are individual for each used symbol will further constitute a collection of tick data.
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Neural networks made easy (Part 30): Genetic algorithms

Today I want to introduce you to a slightly different learning method. We can say that it is borrowed from Darwin's theory of evolution. It is probably less controllable than the previously discussed methods but it allows training non-differentiable models.
Building an Interactive Application to Display RSS Feeds in MetaTrader 5

Building an Interactive Application to Display RSS Feeds in MetaTrader 5

In this article we look at the possibility of creating an application for the display of RSS feeds. The article will show how aspects of the Standard Library can be used to create interactive programs for MetaTrader 5.
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Creating an EA that works automatically (Part 03): New functions

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. In the previous article, we started to develop an order system that we will use in our automated EA. However, we have created only one of the necessary functions.
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Neural networks made easy (Part 36): Relational Reinforcement Learning

In the reinforcement learning models we discussed in previous article, we used various variants of convolutional networks that are able to identify various objects in the original data. The main advantage of convolutional networks is the ability to identify objects regardless of their location. At the same time, convolutional networks do not always perform well when there are various deformations of objects and noise. These are the issues which the relational model can solve.
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Scalping Orderflow for MQL5

This MetaTrader 5 Expert Advisor implements a Scalping OrderFlow strategy with advanced risk management. It uses multiple technical indicators to identify trading opportunities based on order flow imbalances. Backtesting shows potential profitability but highlights the need for further optimization, especially in risk management and trade outcome ratios. Suitable for experienced traders, it requires thorough testing and understanding before live deployment.
Graphical interfaces X: New features for the Rendered table (build 9)

Graphical interfaces X: New features for the Rendered table (build 9)

Until today, the CTable was the most advanced type of tables among all presented in the library. This table is assembled from edit boxes of the OBJ_EDIT type, and its further development becomes problematic. Therefore, in terms of maximum capabilities, it is better to develop rendered tables of the CCanvasTable type even at the current development stage of the library. Its current version is completely lifeless, but starting from this article, we will try to fix the situation.
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Neural networks made easy (Part 14): Data clustering

It has been more than a year since I published my last article. This is quite a lot time to revise ideas and to develop new approaches. In the new article, I would like to divert from the previously used supervised learning method. This time we will dip into unsupervised learning algorithms. In particular, we will consider one of the clustering algorithms—k-means.
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How to Integrate Smart Money Concepts (BOS) Coupled with the RSI Indicator into an EA

How to Integrate Smart Money Concepts (BOS) Coupled with the RSI Indicator into an EA

Smart Money Concept (Break Of Structure) coupled with the RSI Indicator to make informed automated trading decisions based on the market structure.
Other classes in DoEasy library (Part 67): Chart object class

Other classes in DoEasy library (Part 67): Chart object class

In this article, I will create the chart object class (of a single trading instrument chart) and improve the collection class of MQL5 signal objects so that each signal object stored in the collection updates all its parameters when updating the list.
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Automating Trading Strategies in MQL5 (Part 1): The Profitunity System (Trading Chaos by Bill Williams)

Automating Trading Strategies in MQL5 (Part 1): The Profitunity System (Trading Chaos by Bill Williams)

In this article, we examine the Profitunity System by Bill Williams, breaking down its core components and unique approach to trading within market chaos. We guide readers through implementing the system in MQL5, focusing on automating key indicators and entry/exit signals. Finally, we test and optimize the strategy, providing insights into its performance across various market scenarios.
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Developing a trading Expert Advisor from scratch (Part 12): Times and Trade (I)

Developing a trading Expert Advisor from scratch (Part 12): Times and Trade (I)

Today we will create Times & Trade with fast interpretation to read the order flow. It is the first part in which we will build the system. In the next article, we will complete the system with the missing information. To implement this new functionality, we will need to add several new things to the code of our Expert Advisor.
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MQL5 Wizard techniques you should know (Part 06): Fourier Transform

MQL5 Wizard techniques you should know (Part 06): Fourier Transform

The Fourier transform introduced by Joseph Fourier is a means of deconstructing complex data wave points into simple constituent waves. This feature could be resourceful to traders and this article takes a look at that.
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Creating an MQL5 Expert Advisor Based on the Daily Range Breakout Strategy

Creating an MQL5 Expert Advisor Based on the Daily Range Breakout Strategy

In this article, we create an MQL5 Expert Advisor based on the Daily Range Breakout strategy. We cover the strategy’s key concepts, design the EA blueprint, and implement the breakout logic in MQL5. In the end, we explore techniques for backtesting and optimizing the EA to maximize its effectiveness.
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Automating Trading Strategies in MQL5 (Part 4): Building a Multi-Level Zone Recovery System

Automating Trading Strategies in MQL5 (Part 4): Building a Multi-Level Zone Recovery System

In this article, we develop a Multi-Level Zone Recovery System in MQL5 that utilizes RSI to generate trading signals. Each signal instance is dynamically added to an array structure, allowing the system to manage multiple signals simultaneously within the Zone Recovery logic. Through this approach, we demonstrate how to handle complex trade management scenarios effectively while maintaining a scalable and robust code design.
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Automating Trading Strategies in MQL5 (Part 13): Building a Head and Shoulders Trading Algorithm

Automating Trading Strategies in MQL5 (Part 13): Building a Head and Shoulders Trading Algorithm

In this article, we automate the Head and Shoulders pattern in MQL5. We analyze its architecture, implement an EA to detect and trade it, and backtest the results. The process reveals a practical trading algorithm with room for refinement.
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Creating an EA that works automatically (Part 04): Manual triggers (I)

Creating an EA that works automatically (Part 04): Manual triggers (I)

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode.
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Timeseries in DoEasy library (part 56): Custom indicator object, get data from indicator objects in the collection

Timeseries in DoEasy library (part 56): Custom indicator object, get data from indicator objects in the collection

The article considers creation of the custom indicator object for the use in EAs. Let’s slightly improve library classes and add methods to get data from indicator objects in EAs.
Creating a "Snake" Game in MQL5

Creating a "Snake" Game in MQL5

This article describes an example of "Snake" game programming. In MQL5, the game programming became possible primarily due to event handling features. The object-oriented programming greatly simplifies this process. In this article, you will learn the event processing features, the examples of use of the Standard MQL5 Library classes and details of periodic function calls.
MQL5 Cookbook: Reducing the Effect of Overfitting and Handling the Lack of Quotes

MQL5 Cookbook: Reducing the Effect of Overfitting and Handling the Lack of Quotes

Whatever trading strategy you use, there will always be a question of what parameters to choose to ensure future profits. This article gives an example of an Expert Advisor with a possibility to optimize multiple symbol parameters at the same time. This method is intended to reduce the effect of overfitting parameters and handle situations where data from a single symbol are not enough for the study.
Other classes in DoEasy library (Part 68): Chart window object class and indicator object classes in the chart window

Other classes in DoEasy library (Part 68): Chart window object class and indicator object classes in the chart window

In this article, I will continue the development of the chart object class. I will add the list of chart window objects featuring the lists of available indicators.
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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.
Other classes in DoEasy library (Part 71): Chart object collection events

Other classes in DoEasy library (Part 71): Chart object collection events

In this article, I will create the functionality for tracking some chart object events — adding/removing symbol charts and chart subwindows, as well as adding/removing/changing indicators in chart windows.
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How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 5):  Bollinger Bands On Keltner Channel — Indicators Signal

How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 5): Bollinger Bands On Keltner Channel — Indicators Signal

The Multi-Currency Expert Advisor in this article is an 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 one symbol pair from only one symbol chart. In this article we will use signals from two indicators, in this case Bollinger Bands® on Keltner Channel.
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Non-linear indicators

Non-linear indicators

In this article, I will make an attempt to consider some ways of building non-linear indicators and their use in trading. There are quite a few indicators in the MetaTrader trading platform that use non-linear approaches.
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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.
Working with GSM Modem from an MQL5 Expert Advisor

Working with GSM Modem from an MQL5 Expert Advisor

There is currently a fair number of means for a comfortable remote monitoring of a trading account: mobile terminals, push notifications, working with ICQ. But it all requires Internet connection. This article describes the process of creating an Expert Advisor that will allow you to stay in touch with your trading terminal even when mobile Internet is not available, through calls and text messaging.
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Implementing a Bollinger Bands Trading Strategy with MQL5: A Step-by-Step Guide

Implementing a Bollinger Bands Trading Strategy with MQL5: A Step-by-Step Guide

A step-by-step guide to implementing an automated trading algorithm in MQL5 based on the Bollinger Bands trading strategy. A detailed tutorial based on creating an Expert Advisor that can be useful for traders.
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Multibot in MetaTrader (Part II): Improved dynamic template

Multibot in MetaTrader (Part II): Improved dynamic template

Developing the theme of the previous article, I decided to create a more flexible and functional template that has greater capabilities and can be effectively used both in freelancing and as a base for developing multi-currency and multi-period EAs with the ability to integrate with external solutions.
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Creating an EA that works automatically (Part 14): Automation (VI)

Creating an EA that works automatically (Part 14): Automation (VI)

In this article, we will put into practice all the knowledge from this series. We will finally build a 100% automated and functional system. But before that, we still have to learn one last detail.
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How to develop any type of Trailing Stop and connect it to an EA

How to develop any type of Trailing Stop and connect it to an EA

In this article, we will look at classes for convenient creation of various trailings, as well as learn how to connect a trailing stop to any EA.
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Neural networks made easy (Part 28): Policy gradient algorithm

Neural networks made easy (Part 28): Policy gradient algorithm

We continue to study reinforcement learning methods. In the previous article, we got acquainted with the Deep Q-Learning method. In this method, the model is trained to predict the upcoming reward depending on the action taken in a particular situation. Then, an action is performed in accordance with the policy and the expected reward. But it is not always possible to approximate the Q-function. Sometimes its approximation does not generate the desired result. In such cases, approximation methods are applied not to utility functions, but to a direct policy (strategy) of actions. One of such methods is Policy Gradient.