MQL5 Programming Articles

With this article we begin chapter nine of series of articles dedicated to creating graphical interfaces in MetaTrader trading terminals. It consists of two chapters where new elements of controls and interface, such as color picker, color button, progress bar and line chart are presented.

Hiding of the implementation details of classes/functions in an .ex5 file will enable you to share your know-how algorithms with other developers, set up common projects and promote them in the Web. And while the MetaQuotes team spares no effort to bring about the possibility of direct inheritance of ex5 library classes, we are going to implement it right now.

In this article, we will consider combining the lists of bar objects for each used symbol period into a single symbol timeseries object. Thus, each symbol will have an object storing the lists of all used symbol timeseries periods.

If an indicator uses values of many other indicators for its calculations, it consumes a lot of memory. The article describes several methods of decreasing the memory consumption when using auxiliary indicators. Saved memory allows increasing the number of simultaneously used currency pairs, indicators and strategies in the client terminal. It increases the reliability of trade portfolio. Such a simple care about technical resources of your computer can turn into money resources at your deposit.

We continue to add new features to the rendered table: data sorting, managing the number of columns and rows, setting the table cell types to place controls into them.

We will present a modified version of the Expert Advisor from the previous article "MQL5 Cookbook: Position Properties on the Custom Info Panel". Some of the issues we will address include getting data from bars, checking for new bar events on the current symbol, including a trade class of the Standard Library to a file, creating a function to search for trading signals and a function for executing trading operations, as well as determining trade events in the OnTrade() function.

Understanding the subtle dynamics behind price movements can give you a critical edge. One such phenomenon is the liquidity sweep, a deliberate strategy that large traders, especially institutions, use to push prices through key support or resistance levels. These levels often coincide with clusters of retail stop-loss orders, creating pockets of liquidity that big players can exploit to enter or exit sizeable positions with minimal slippage.

In this article we will implement an algorithm that applies the Box and Jenkins Autoregressive Integrated Moving Average model by using Powells method of function minimization. Box and Jenkins stated that most time series could be modeled by one or both of two frameworks.

A new version of the graphics library for creating scientific charts (the CGraphic class) has been presented recently. This update of the developed library for creating graphical interfaces will introduce a version with a new control for creating charts. Now it is even easier to visualize data of different types.

In this article, I will create the class of the abstract graphical object. This object is to serve as a basis for creating the class of standard graphical objects. Graphical objects feature multiple properties. Therefore, I will need to do a lot of preparatory work before actually creating the abstract graphical object class. This work includes setting the properties in the library enumerations.

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.

We continue to study machine learning methods. With this article, we begin another big topic, Reinforcement Learning. This approach allows the models to set up certain strategies for solving the problems. We can expect that this property of reinforcement learning will open up new horizons for building trading strategies.

In this article, I will consider tracking property value modification, as well as removing and renaming graphical objects in the library.

Matrices and vectors have been introduced in MQL5 for efficient operations with mathematical solutions. The new types offer built-in methods for creating concise and understandable code that is close to mathematical notation. Arrays provide extensive capabilities, but there are many cases in which matrices are much more efficient.

After I wrote a previous article on semi-automatic Expert Advisor with GUI interface it turned out that it would be desirable to enhance interface with some new functionalities for more complex indicators and Expert Advisors. After getting acquainted with MQL5 standard library classes I implemented new widgets. This article describes a process of designing and implementing new MQL5 GUI widgets that can be used in indicators and Expert Advisors. The widgets presented in the article are CChartObjectSpinner, CChartObjectProgressBar and CChartObjectEditTable.

In the previous chapter, we wrote classes for creating vertical and horizontal scrollbars. In this chapter, we will implement them. We will write a class for creating the list view element, a compound part of which will be a vertical scrollbar.

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.

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.

In this update of the library, the Table control (the CTable class) will be supplemented with new options. The lineup of controls in the table cells is expanded, this time adding text edit boxes and combo boxes. As an addition, this update also introduces the ability to resize the window of an MQL application during its runtime.

Calls to user and technical indicators takes up very little space in the program code of automated trading systems. Often it’s simply a few code lines. But it often happens that it is these few lines of code which use up the largest portion of time, which needs to be spent on testing the Expert Advisor. Therefore, everything that is related to data calculations within an indicator, needs to be considered much more thoroughly than would seem at first glance. This article will talk precisely about this.

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.

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.

This article starts an extensive topic of creating controls in Windows Forms style using MQL5. My first object of interest is creating the panel class. It is already becoming difficult to manage things without controls. Therefore, I will create all possible controls in Windows Forms style.

We have earlier discussed some types of neural network implementations. In the considered networks, the same operations are repeated for each neuron. A logical further step is to utilize multithreaded computing capabilities provided by modern technology in an effort to speed up the neural network learning process. One of the possible implementations is described in this article.

Trading Signals service recently introduced in MetaTrader 5 allows traders to copy trading operations of any signals provider. Users can select any signal, subscribe to it and all deals will be copied at their accounts. Signals providers can set their subscription prices and receive a fixed monthly fee from their subscribers.

This article presents an alternative method of GUI creation based on layouts and containers, using one layout manager — the CGrid class. The CGrid class is an auxiliary control that acts as a container for other containers and controls using a grid layout.

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.

The article considers the basic principles of mathematical expression parsing and calculation. We will implement recursive descent parsers operating in the interpreter and fast calculation modes, based on a pre-built syntax tree.

Volatility based breakout system identifies market ranges, then trades when price breaks above or below those levels, filtered by volatility measures such as ATR. This approach helps capture strong directional moves.