Articles with examples of trading robots developed in MQL5

The article discusses the methods for building and training ensembles of neural networks with bagging structure. It also determines the peculiarities of hyperparameter optimization for individual neural network classifiers that make up the ensemble. The quality of the optimized neural network obtained in the previous article of the series is compared with the quality of the created ensemble of neural networks. Possibilities of further improving the quality of the ensemble's classification are considered.

In this article, we will continue to modify the Expert Advisor we have been working on throughout the preceding articles of the MQL5 Cookbook series. This time, the Expert Advisor will be enhanced with indicators whose values will be used to check position opening conditions. To spice it up, we will create a drop-down list in the external parameters to be able to select one out of three trading indicators.

In the previous article, we started developing a form class for controls. In this article, we are going to continue doing that by filling this class with methods for moving a form over the chart area. We will then integrate this interface component into the core of the library. Also, we will ensure that the color of a form control changes when the mouse cursor is hovering over it.

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.

The main difference of the trading system proposed in the article is the use of mathematical tools for analyzing stock quotes. The system applies digital filtering and spectral estimation of discrete time series. The theoretical aspects of the strategy are described and a test Expert Advisor is created.

The article describes a method of modifying the code of a trading signal module for the implementation of the functionality allowing you to set pending orders at any distance from the current price: it may be the Close or Open price of the previous bar or the value of the moving average. There are plenty of options. Important is that you can set any opening price for a pending order. This article will be useful to traders who trade with pending orders.

In the article, we continue to develop the MQL application for working with optimization results. This time, we will show how to form the table of the best results after optimizing the parameters by specifying another criterion via the graphical interface.

In this article, we create a Breaker Block Trading System in MQL5 that identifies consolidation ranges, detects breakouts, and validates breaker blocks with swing points to trade retests with defined risk parameters. The system visualizes order and breaker blocks with dynamic labels and arrows, supporting automated trading and trailing stops.

This article explores how to build an Opening Range Breakout (ORB) Expert Advisor in MQL5. It explains how the EA identifies breakouts from the market’s initial range and opens trades accordingly. You’ll also learn how to control the number of positions opened and set a specific cutoff time to stop trading automatically.

In this article, we are going to continue developing the CWindow class by adding methods, which will allow managing the form by clicking on its controls. We will enable the program to be closed by a form button as well as implement a minimizing and maximizing feature for the form.

The first chapter of the series was about simple and multi-functional buttons. The second article will be dedicated to groups of interconnected buttons that will allow the creation of elements in an application when a user can select one of the option out of a set (group).

Since the publication of the previous article in the series, Easy And Fast library has received some new features. The library structure and code have been partially optimized slightly reducing CPU load. Some recurring methods in many control classes have been moved to the CElement base class.

The problem of calculation of the total position volume of the specified symbol and magic number is considered in this article. The proposed method requests only the minimum necessary part of the history of deals, finds the closest time when the total position was equal to zero, and performs the calculations with the recent deals. Working with global variables of the client terminal is also considered.

Different situations happen in trader’s life. Often, the history of successful trades allows us to restore a strategy, while looking at a loss history we try to develop and improve it. In both cases, we compare trades with known indicators. This article suggests methods of batch comparison of trades with a number of indicators.

This article presents a method of programming the equidistant channel system. Certain details of building such channels are being considered here. Channel typification is provided, and a universal type of moving channels' method is suggested. Object-oriented programming (OOP) is used for code implementation.

Many traders on Moscow Exchange would like to automate their trading algorithms, but they do not know where to start. The MQL5 language offers a huge range of trading functions, and it additionally provides ready classes that help users to make their first steps in algo trading.

In previous articles, we used stochastic gradient descent to train a neural network using the same learning rate for all neurons within the network. In this article, I propose to look towards adaptive learning methods which enable changing of the learning rate for each neuron. We will also consider the pros and cons of this approach.

This article will consider new controls: Text Edit box, Picture Slider, as well as additional simple controls: Text label and Picture. The library continues to grow, and in addition to introduction of new controls, the previously created ones are also being improved.

This is the next article within the series, in which I show how I created a convenient library for manual application of chart graphics by utilizing keyboard shortcuts. The tools used include straight lines and their combinations. In this part, we will view how the drawing tools are applied using the functions described in the first part. The library can be connected to any Expert Advisor or indicator which will greatly simplify the charting tasks. This solution DOES NOT use external dlls, while all the commands are implemented using built-in MQL tools.

This article discusses how custom stop levels can be set up in a cross-platform expert advisor. It also discusses a closely-related method by which the evolution of a stop level over time can be defined.

We continue studying the world of neural networks. In this article, we will consider another type of neural networks, recurrent networks. This type is proposed for use with time series, which are represented in the MetaTrader 5 trading platform by price charts.

In this article, we build an MQL5 Expert Advisor for Fibonacci retracement trading, using either daily candle ranges or lookback arrays to calculate custom levels like 50% and 61.8% for entries, determining bullish or bearish setups based on close vs. open. The system triggers buys or sells on price crossings of levels with max trades per level, optional closure on new Fib calcs, points-based trailing stops after a min profit threshold, and SL/TP buffers as percentages of the range.

In continuation of our work on the Expert Advisor from the previous article of the series called "MQL5 Cookbook: Analyzing Position Properties in the MetaTrader 5 Strategy Tester", we will enhance it with a whole lot of useful functions, as well as improve and optimize the existing ones. The Expert Advisor will this time have external parameters that can be optimized in the MetaTrader 5 Strategy Tester and will in some ways resemble a simple trading system.

Some traders execute all their trades automatically, and some mix automatic and manual trades based on the output of several indicators. Being a member of the latter group I needed an interactive tool to asses dynamically risk and reward price levels directly from the chart. This article will present a way to implement an interactive semi-automatic Expert Advisor with predefined equity risk and R/R ratio. The Expert Advisor risk, R/R and lot size parameters can be changed during runtime on the EA panel.

In the first two chapters of the fifth part of the series, we developed classes for creating a scrollbar and a view list. In this chapter, we will speak about creating a class for the combobox control. This is also a compound control containing, among others, elements considered in the previous chapters of the fifth part.

The seventh part of the series on MetaTrader graphical interfaces deals with three table types: text label, edit box and rendered one. Another important and frequently used controls are tabs allowing you to show/hide groups of other controls and develop space effective interfaces in your MQL applications.

The project involves using Python for deep learning-based forecasting in financial markets. We will explore the intricacies of testing the model's performance using key metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R2) and we will learn how to wrap everything into an executable. We will also make a ONNX model file with its EA.

This article deals primarily with the classes CExpertAdvisor and CExpertAdvisors, which serve as the container for all the other components described in this article-series regarding cross-platform expert advisors.

This article continues the series of publications on a universal Expert Advisor model. This part describes in detail the original event model based on centralized data processing, and considers the structure of the CStrategy base class of the engine.

This article shows you how to build an Object-Oriented Expert Advisor from scratch, from conceiving a theoretical trading idea to programming a MQL5 EA that makes that idea real in the empirical world. Learning by doing is IMHO a solid approach to succeed, so I am showing a practical example in order for you to see how you can order your ideas to finally code your Forex robots. My goal is also to invite you to adhere the OO principles.

It is time to briefly summarize the information provided in the previous articles on position properties. In this article, we will create a few additional functions to get the properties that can only be obtained after accessing the history of deals. We will also get familiar with data structures that will allow us to access position and symbol properties in a more convenient way.

I am not a professional programmer. And thus, the principle of "going from the simple to the complex" is of primary importance to me when I am working on trading system development. What exactly is simple for me? First of all, it is the visualization of the process of creating the system, and the logic of its work. Also, it is a minimum of handwritten code. In this article, I will attempt to create and test the trading system, based on a Matlab package, and then write an Expert Advisor for MetaTrader 5. The historical data from MetaTrader 5 will be used for the testing process.