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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An Analysis of Why Expert Advisors Fail

An Analysis of Why Expert Advisors Fail

This article presents an analysis of currency data to better understand why expert advisors can have good performance in some regions of time and poor performance in other regions of time.
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Modified Grid-Hedge EA in MQL5 (Part II): Making a Simple Grid EA

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

In this article, we explored the classic grid strategy, detailing its automation using an Expert Advisor in MQL5 and analyzing initial backtest results. We highlighted the strategy's need for high holding capacity and outlined plans for optimizing key parameters like distance, takeProfit, and lot sizes in future installments. The series aims to enhance trading strategy efficiency and adaptability to different market conditions.
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Decoding Opening Range Breakout Intraday Trading Strategies

Decoding Opening Range Breakout Intraday Trading Strategies

Opening Range Breakout (ORB) strategies are built on the idea that the initial trading range established shortly after the market opens reflects significant price levels where buyers and sellers agree on value. By identifying breakouts above or below a certain range, traders can capitalize on the momentum that often follows as the market direction becomes clearer. In this article, we will explore three ORB strategies adapted from the Concretum Group.
Naive Bayes classifier for signals of a set of indicators
Naive Bayes classifier for signals of a set of indicators

Naive Bayes classifier for signals of a set of indicators

The article analyzes the application of the Bayes' formula for increasing the reliability of trading systems by means of using signals from multiple independent indicators. Theoretical calculations are verified with a simple universal EA, configured to work with arbitrary indicators.
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Data Science and Machine Learning — Neural Network (Part 02): Feed forward NN Architectures Design

Data Science and Machine Learning — Neural Network (Part 02): Feed forward NN Architectures Design

There are minor things to cover on the feed-forward neural network before we are through, the design being one of them. Let's see how we can build and design a flexible neural network to our inputs, the number of hidden layers, and the nodes for each of the network.
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Learn how to design a trading system by Awesome Oscillator

Learn how to design a trading system by Awesome Oscillator

In this new article in our series, we will learn about a new technical tool that may be useful in our trading. It is the Awesome Oscillator (AO) indicator. We will learn how to design a trading system by this indicator.
Using the TesterWithdrawal() Function for Modeling the Withdrawals of Profit
Using the TesterWithdrawal() Function for Modeling the Withdrawals of Profit

Using the TesterWithdrawal() Function for Modeling the Withdrawals of Profit

This article describes the usage of the TesterWithDrawal() function for estimating risks in trade systems which imply the withdrawing of a certain part of assets during their operation. In addition, it describes the effect of this function on the algorithm of calculation of the drawdown of equity in the strategy tester. This function is useful when optimizing parameter of your Expert Advisors.
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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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Neural networks made easy (Part 11): A take on GPT

Neural networks made easy (Part 11): A take on GPT

Perhaps one of the most advanced models among currently existing language neural networks is GPT-3, the maximal variant of which contains 175 billion parameters. Of course, we are not going to create such a monster on our home PCs. However, we can view which architectural solutions can be used in our work and how we can benefit from them.
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How to build and optimize a cycle-based trading system (Detrended Price Oscillator - DPO)

How to build and optimize a cycle-based trading system (Detrended Price Oscillator - DPO)

This article explains how to design and optimise a trading system using the Detrended Price Oscillator (DPO) in MQL5. It outlines the indicator's core logic, demonstrating how it identifies short-term cycles by filtering out long-term trends. Through a series of step-by-step examples and simple strategies, readers will learn how to code it, define entry and exit signals, and conduct backtesting. Finally, the article presents practical optimization methods to enhance performance and adapt the system to changing market conditions.
The Player of Trading Based on Deal History
The Player of Trading Based on Deal History

The Player of Trading Based on Deal History

The player of trading. Only four words, no explanation is needed. Thoughts about a small box with buttons come to your mind. Press one button - it plays, move the lever - the playback speed changes. In reality, it is pretty similar. In this article, I want to show my development that plays trade history almost like it is in real time. The article covers some nuances of OOP, working with indicators and managing charts.
Graphics in DoEasy library (Part 76): Form object and predefined color themes
Graphics in DoEasy library (Part 76): Form object and predefined color themes

Graphics in DoEasy library (Part 76): Form object and predefined color themes

In this article, I will describe the concept of building various library GUI design themes, create the Form object, which is a descendant of the graphical element class object, and prepare data for creating shadows of the library graphical objects, as well as for further development of the functionality.
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Automating Trading Strategies in MQL5 (Part 7): Building a Grid Trading EA with Dynamic Lot Scaling

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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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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Developing a trading Expert Advisor from scratch (Part 7): Adding Volume at Price (I)

Developing a trading Expert Advisor from scratch (Part 7): Adding Volume at Price (I)

This is one of the most powerful indicators currently existing. Anyone who trades trying to have a certain degree of confidence must have this indicator on their chart. Most often the indicator is used by those who prefer “tape reading” while trading. Also, this indicator can be utilized by those who use only Price Action while trading.
Developing a cross-platform grider EA (part III): Correction-based grid with martingale
Developing a cross-platform grider EA (part III): Correction-based grid with martingale

Developing a cross-platform grider EA (part III): Correction-based grid with martingale

In this article, we will make an attempt to develop the best possible grid-based EA. As usual, this will be a cross-platform EA capable of working both with MetaTrader 4 and MetaTrader 5. The first EA was good enough, except that it could not make a profit over a long period of time. The second EA could work at intervals of more than several years. Unfortunately, it was unable to yield more than 50% of profit per year with a maximum drawdown of less than 50%.
Statistical Carry Trade Strategy
Statistical Carry Trade Strategy

Statistical Carry Trade Strategy

An algorithm of statistical protection of open positive swap positions from unwanted price movements. This article features a variant of the carry trade protection strategy that allows to compensate for potential risk of the price movement in the direction opposite to that of the open position.
Applying OLAP in trading (part 2): Visualizing the interactive multidimensional data analysis results
Applying OLAP in trading (part 2): Visualizing the interactive multidimensional data analysis results

Applying OLAP in trading (part 2): Visualizing the interactive multidimensional data analysis results

In this article, we consider the creation of an interactive graphical interface for an MQL program, which is designed for the processing of account history and trading reports using OLAP techniques. To obtain a visual result, we will use maximizable and scalable windows, an adaptive layout of rubber controls and a new control for displaying diagrams. To provide the visualization functionality, we will implement a GUI with the selection of variables along coordinate axes, as well as with the selection of aggregate functions, diagram types and sorting options.
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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.
Visualizing trading strategy optimization in MetaTrader 5
Visualizing trading strategy optimization in MetaTrader 5

Visualizing trading strategy optimization in MetaTrader 5

The article implements an MQL application with a graphical interface for extended visualization of the optimization process. The graphical interface applies the last version of EasyAndFast library. Many users may ask why they need graphical interfaces in MQL applications. This article demonstrates one of multiple cases where they can be useful for traders.
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From Novice to Expert: Higher Probability Signals

From Novice to Expert: Higher Probability Signals

In high-probability support and resistance zones, valid entry confirmation signals are always present once the zone has been correctly identified. In this discussion, we build an intelligent MQL5 program that automatically detects entry conditions within these zones. We leverage well-known candlestick patterns alongside native confirmation indicators to validate trade decisions. Click to read further.
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Neural networks made easy (Part 12): Dropout

Neural networks made easy (Part 12): Dropout

As the next step in studying neural networks, I suggest considering the methods of increasing convergence during neural network training. There are several such methods. In this article we will consider one of them entitled Dropout.
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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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Automating Trading Strategies in MQL5 (Part 5): Developing the Adaptive Crossover RSI Trading Suite Strategy

Automating Trading Strategies in MQL5 (Part 5): Developing the Adaptive Crossover RSI Trading Suite Strategy

In this article, we develop the Adaptive Crossover RSI Trading Suite System, which uses 14- and 50-period moving average crossovers for signals, confirmed by a 14-period RSI filter. The system includes a trading day filter, signal arrows with annotations, and a real-time dashboard for monitoring. This approach ensures precision and adaptability in automated trading.
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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).
Video: Simple automated trading – How to create a simple Expert Advisor with MQL5
Video: Simple automated trading – How to create a simple Expert Advisor with MQL5

Video: Simple automated trading – How to create a simple Expert Advisor with MQL5

The majority of students in my courses felt that MQL5 was really difficult to understand. In addition to this, they were searching for a straightforward method to automate a few processes. Find out how to begin working with MQL5 right now by reading the information contained in this article. Even if you have never done any form of programming before. And even in the event that you are unable to comprehend the previous illustrations that you have observed.
Cross-Platform Expert Advisor: Stops
Cross-Platform Expert Advisor: Stops

Cross-Platform Expert Advisor: Stops

This article discusses an implementation of stop levels in an expert advisor in order to make it compatible with the two platforms MetaTrader 4 and MetaTrader 5.
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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.
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The Inverse Fair Value Gap Trading Strategy

The Inverse Fair Value Gap Trading Strategy

An inverse fair value gap(IFVG) occurs when price returns to a previously identified fair value gap and, instead of showing the expected supportive or resistive reaction, fails to respect it. This failure can signal a potential shift in market direction and offer a contrarian trading edge. In this article, I'm going to introduce my self-developed approach to quantifying and utilizing inverse fair value gap as a strategy for MetaTrader 5 expert advisors.
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Neural networks made easy (Part 8): Attention mechanisms

Neural networks made easy (Part 8): Attention mechanisms

In previous articles, we have already tested various options for organizing neural networks. We also considered convolutional networks borrowed from image processing algorithms. In this article, I suggest considering Attention Mechanisms, the appearance of which gave impetus to the development of language models.
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Improve Your Trading Charts With Interactive GUI's in MQL5 (Part III): Simple Movable Trading GUI

Improve Your Trading Charts With Interactive GUI's in MQL5 (Part III): Simple Movable Trading GUI

Join us in Part III of the "Improve Your Trading Charts With Interactive GUIs in MQL5" series as we explore the integration of interactive GUIs into movable trading dashboards in MQL5. This article builds on the foundations set in Parts I and II, guiding readers to transform static trading dashboards into dynamic, movable ones.
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Learn how to design a trading system by Relative Vigor Index

Learn how to design a trading system by Relative Vigor Index

A new article in our series about how to design a trading system by the most popular technical indicator. In this article, we will learn how to do that by the Relative Vigor Index indicator.
Building a Social Technology Startup, Part II: Programming an MQL5 REST Client
Building a Social Technology Startup, Part II: Programming an MQL5 REST Client

Building a Social Technology Startup, Part II: Programming an MQL5 REST Client

Let's now shape the PHP-based Twitter idea which was introduced in the first part of this article. We are assembling the different parts of the SDSS. Regarding the client side of the system architecture, we are relying on the new MQL5 WebRequest() function for sending trading signals via HTTP.
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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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Automating Trading Strategies in MQL5 (Part 25): Trendline Trader with Least Squares Fit and Dynamic Signal Generation

Automating Trading Strategies in MQL5 (Part 25): Trendline Trader with Least Squares Fit and Dynamic Signal Generation

In this article, we develop a trendline trader program that uses least squares fit to detect support and resistance trendlines, generating dynamic buy and sell signals based on price touches and open positions based on generated signals.
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Automating Trading Strategies in MQL5 (Part 43): Adaptive Linear Regression Channel Strategy

Automating Trading Strategies in MQL5 (Part 43): Adaptive Linear Regression Channel Strategy

In this article, we implement an adaptive Linear Regression Channel system in MQL5 that automatically calculates the regression line and standard deviation channel over a user-defined period, only activates when the slope exceeds a minimum threshold to confirm a clear trend, and dynamically recreates or extends the channel when the price breaks out by a configurable percentage of channel width.
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Price Action Analysis Toolkit Development (Part 53): Pattern Density Heatmap for Support and Resistance Zone Discovery

Price Action Analysis Toolkit Development (Part 53): Pattern Density Heatmap for Support and Resistance Zone Discovery

This article introduces the Pattern Density Heatmap, a price‑action mapping tool that transforms repeated candlestick pattern detections into statistically significant support and resistance zones. Rather than treating each signal in isolation, the EA aggregates detections into fixed price bins, scores their density with optional recency weighting, and confirms levels against higher‑timeframe data. The resulting heatmap reveals where the market has historically reacted—levels that can be used proactively for trade timing, risk management, and strategy confidence across any trading style.
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!
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Automating Trading Strategies in MQL5 (Part 24): London Session Breakout System with Risk Management and Trailing Stops

Automating Trading Strategies in MQL5 (Part 24): London Session Breakout System with Risk Management and Trailing Stops

In this article, we develop a London Session Breakout System that identifies pre-London range breakouts and places pending orders with customizable trade types and risk settings. We incorporate features like trailing stops, risk-to-reward ratios, maximum drawdown limits, and a control panel for real-time monitoring and management.
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.