Articles with MQL5 programming examples

The author familiarizes the readers with a simple library of matrix algebra and provides descriptions and peculiarities of the main functions.

The article shows an example of how to develop an MQL5-program implementing the adaptive algorithm of clustering called Growing neural gas (GNG). The article is intended for the users who have studied the language documentation and have certain programming skills and basic knowledge in the area of neuroinformatics.

This article provides a method to create complex indicators while also avoiding the problems that arise when dealing with multiple plots, buffers and/or combining data from multiple sources.

Every price action trader manually uses trendlines to confirm trends and spot potential turning or continuation levels. In this series on developing a price action analysis toolkit, we introduce a tool focused on drawing slanted trendlines for easy market analysis. This tool simplifies the process for traders by clearly outlining key trends and levels essential for effective price action evaluation.

In this article, I will consider the algorithms allowing you to create your own technical indicator. You will learn how to obtain pretty complex and interesting results with very simple initial assumptions.

In the previous articles, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. In the fifth part of the article series, we created trading event classes and the event collection, from which the events are sent to the base object of the Engine library and the control program chart. In this part, we will let the library to work on netting accounts.

In this article, I will expand the functionality of chart objects and arrange navigation through charts, creation of screenshots, as well as saving and applying templates to charts. Also, I will implement auto update of the collection of chart objects, their windows and indicators within them.

This is the second article from the series "MQL4 Language for Newbies". Now we will examine more complex and advanced constructions of the language, learn new options and see, how they can be applied in everyday practice. You will get acquainted with a new cycle type 'while', new condition type 'switch', operators 'break' and 'continue'. Besides you will learn to write your own functions and work with multidimensional arrays. And for a dessert I have prepared an explanation about a preprocessor.

We will begin the journey to explore the steps and workflow on how to base development for MetaTrader 5 platform solely on Linux system in which the final product works seamlessly on both Windows and Linux system. We will get to know Wine, and Mingw; both are the essential tools to make cross-platform development works. Especially Mingw for its threading implementations (POSIX, and Win32) that we need to consider in choosing which one to go with. We then build a proof-of-concept DLL and consume it in MQL5 code, finally compare the performance of both threading implementations. All for your foundation to expand further on your own. You should be comfortable building MT related tools on Linux after reading this article.

In the previous articles, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. In the eighth part, we implemented the class for tracking order and position modification events. Here, we will improve the library by making it fully compatible with MQL4.

The article describes creation of an indicator that would display the support/resistance levels using up/down fractals.

The construction of various types of diagrams is an essential part of the analyses of the market situation and the testing of a trading system. Frequently, in order to construct a nice looking diagram, it is necessary to organize the data output into a file, after which it is used in applications such as MS Excel. This is not very convenient and deprives us of the ability to dynamically update the data. Google Charts API provided the means for creating charts in online modes, by sending a special request to the server. In this article we attempt to automate the process of creating such a request and obtaining a chart from the Google server.

Description of a step-by-step Linux-desktop setup using a non-emulator wine for running MetaTrader 4 Client Terminal on it.

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.

Indicator emissions are a little-studied area of market research. Primarily, this is due to the difficulty of analysis that is caused by the processing of very large arrays of time-varying data. Existing graphical analysis is too resource intensive and has therefore triggered the development of a parsimonious algorithm that uses time series of emissions. This article demonstrates how visual (intuitive image) analysis can be replaced with the study of integral characteristics of emissions. It can be of interest to both traders and developers of automated trading systems.

Create a trading journal using MetaTrader and Google Sheets! You will learn how to sync your trading data via HTTP POST and retrieve it using HTTP requests. In the end, You have a trading journal that will help you keep track of your trades effectively and efficiently.

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.

In this article, I will optimize the code of classes from the previous articles and create the geometric animation frame object class allowing us to draw regular polygons with a given number of vertices.

In the current article, I will get rid of some errors related to handling graphical elements and continue the development of the CPanel control. In particular, I will implement the methods for setting the parameters of the font used by default for all panel text objects.

In this article, I will implement updating tick data in real time and prepare the symbol object class for working with Depth of Market (DOM itself is to be implemented in the next article).

In conclusion of the topic of working with timeseries organise storage, search and sort of data stored in indicator buffers which will allow to further perform the analysis based on values of the indicators to be created on the library basis in programs. The general concept of all collection classes of the library allows to easily find necessary data in the corresponding collection. Respectively, the same will be possible in the class created today.

In this article, I will continue my work on tracking standard graphical object events and create the functionality allowing users to control changes in the properties of graphical objects placed on any charts opened in the terminal.

Every developer wants to be able to write code faster, and being able to code faster and effective is not some kind of special ability that only a few people are born with. It's a skill that can be learned by every coder, regardless of years of experience on the keyboard.

To complete this series of articles on automation, we will continue discussing the topic of the previous article. We will see how everything will fit together, making the EA run like clockwork.

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.

The article continues developing indicator object classes and their collections. For each indicator object create its description and correct collection class for error-free storage and getting indicator objects from the collection list.