Articles on MetaTrader 5 integration using MQL5

This article demonstrates how to utilize Depth of Market (DOM) programmatically and describes the operation principle of CMarketBook class, that can expand the Standard Library of MQL5 classes and offer convenient methods of using DOM.

The article considers three methods which can be used to increase the classification quality of bagging ensembles, and their efficiency is estimated. The effects of optimization of the ELM neural network hyperparameters and postprocessing parameters are evaluated.

This series of articles continues exploring deep neural networks (DNN), which are used in many application areas including trading. Here new dimensions of this theme will be explored along with testing of new methods and ideas using practical experiments. The first article of the series is dedicated to preparing data for DNN.

Using the object-oriented approach in MQL5 greatly simplifies the creation of multi-currency/multi-system /multi-time-frame Expert Advisors. Just imagine, your single EA trades on several dozens of trading strategies, on all of the available instruments, and on all of the possible time frames! In addition, the EA is easily tested in the tester, and for all of the strategies, included in its composition, it has one or several working systems of money management.

This article describes the principles of working with the Internet via the use of HTTP requests, and data exchange between terminals, using an intermediate server. An MqlNet library class is presented for working with Internet resources in the MQL5 environment. Monitoring prices from different brokers, exchanging messages with other traders without exiting the terminal, searching for information on the Internet – these are just some examples, reviewed in this article.

The article describes how to implement Interprocess Communication between MetaTrader 5 client terminals using named pipes. For the use of the named pipes, the CNamedPipes class is developed. For the test of its use and to measure the connection throughput, the tick indicator, the server and client scripts are presented. The use of named pipes is sufficient for real-time quotes.

MetaTrader 5 has received network functions recently. This opened up great opportunities for programmers developing products for the Market. Now they can implement things that required dynamic libraries before. In this article, we will consider them using the implementation of the MySQL as an example.

This article considers new capabilities of the darch package (v.0.12.0). It contains a description of training of a deep neural networks with different data types, different structure and training sequence. Training results are included.

The widget provides websites with a detailed release schedule of 500 indicators and indices, of the world's largest economies. Thus, traders quickly receive up-to-date information on all important events with explanations and graphs in addition to the main website content.

In this article we are going to show how to explore the Standard Library of Trading Strategy Classes and how to add Custom Strategies and Filters/Signals using the Patterns-and-Models logic of the MQL5 Wizard. In the end you will be able easily add your own strategies using MetaTrader 5 standard indicators, and MQL5 Wizard will create a clean and powerful code and fully functional Expert Advisor.

The article is devoted to the analysis of trading signals for the MetaTrader 5 platform, which enable the automated execution of trading operations on subscribers' accounts. Also, the article considers the development of tools, which help search for potentially promising trading signals straight from the terminal.

We continue to build ensembles. This time, the bagging ensemble created earlier will be supplemented with a trainable combiner — a deep neural network. One neural network combines the 7 best ensemble outputs after pruning. The second one takes all 500 outputs of the ensemble as input, prunes and combines them. The neural networks will be built using the keras/TensorFlow package for Python. The features of the package will be briefly considered. Testing will be performed and the classification quality of bagging and stacking ensembles will be compared.

This article is a continuation of the previous publication related to the creation of a graphical interface for optimization management. The article considers the logic of the add-on. A wrapper for the MetaTrader 5 terminal will be created: it will enable the running of the add-on as a managed process via C#. In addition, operation with configuration files and setup files is considered in this article. The application logic is divided into two parts: the first one describes the methods called after pressing a particular key, while the second part covers optimization launch and management.

This article discusses the implementation of money management method for a cross-platform expert advisor. The money management classes are responsible for the calculation of the lot size to be used for the next trade to be entered by the expert advisor.

A Twitter client implemented as MQL class to allow you to send tweets with photos. All you need is to include a single self contained include file and off you go to tweet all your wonderful charts and signals.

The article compares the classic MQL5 access to indicators with alternative MQL4-style methods. Several varieties of MQL4-style access to indicators are considered: with and without the indicator handles caching. Considering the indicator handles inside the MQL5 core is analyzed as well.

In late January 2012, the software development company that stands behind the development of MetaTrader 5 announced native support for OpenCL in MQL5. Using an illustrative example, the article sets forth the programming basics in OpenCL in the MQL5 environment and provides a few examples of the naive optimization of the program for the increase of operating speed.

Want to organize export of quotes from MetaTrader 5 to your own application? The MQL5-DLL junction allows to create such solutions! This article will show you one of the ways to export quotes from MetaTrader 5 to applications written in .NET. For me it was more interesting, rational and easy to implement export of quotes using this very platform. Unfortunately, version 5 still does not support .NET, so like in old days we will use win32 dll with .NET support as an interlayer.

The Strategy Tester in the MetaTrader 5 trading platform provides only two optimization options: complete search of parameters and genetic algorithm. This article proposes a new method for optimizing trading strategies — Simulated annealing. The method's algorithm, its implementation and integration into any Expert Advisor are considered. The developed algorithm is tested on the Moving Average EA.

The original basic article has not lost its relevance and thus if you are interested in this topic, be sure to read the first article. However much time has passed since then, so the current Visual Studio 2017 features an updated interface. The MetaTrader 5 platform has also acquired new features. The article provides a description of dll project development stages, as well as DLL setup and interaction with MetaTrader 5 tools.

Any Expert Advisor developer, regardless of programming skills, is daily confronted with the same trading tasks and algorithmic problems, which should be solved to organize a reliable trading process. The article describes the possibilities of the CStrategy trading engine that can undertake the solution of these tasks and provide a user with convenient mechanism for describing a custom trading idea.

This article discusses the CSignal and CSignals classes which will be used in cross-platform expert advisors. It examines the differences between MQL4 and MQL5 on how particular data needed for evaluation of trade signals are accessed to ensure that the code written will be compatible with both compilers.

This article discusses creation of Expert Advisors using the UML graphical language, which is used for visual modeling of object-oriented software systems. The main advantage of this approach is the visualization of the modeling process. The article contains an example that shows modeling of the structure and properties of an Expert Advisor using the Software Ideas Modeler.

This article describes a new approach to hedging of positions and draws the line in the debates between users of MetaTrader 4 and MetaTrader 5 about this matter. The algorithms making such hedging reliable are described in layman's terms and illustrated with simple charts and diagrams. This article is dedicated to the new panel HedgeTerminal, which is essentially a fully featured trading terminal within MetaTrader 5. Using HedgeTerminal and the virtualization of the trade it offers, positions can be managed in the way similar to MetaTrader 4.

In this article, we will continue analyzing the algorithms of the CStrategy trading engine. The third part of the series contains the detailed analysis of examples of how to develop specific trading strategies using this approach. Special attention is paid to auxiliary algorithms — Expert Advisor logging system and data access using a conventional indexer (Close[1], Open[0] etc.)

This article discusses the implementation of various methods of time filtering a cross-platform expert advisor. The time filter classes are responsible for checking whether or not a given time falls under a certain time configuration setting.

This article describes the MQL5 Standard Library extension, which allows to create Expert Advisors, place orders, Stop Losses and Take Profits using the MQL5 Wizard by the prices received from included modules. This approach does not apply any additional restrictions on the number of modules and does not cause conflicts in their joint work.

The eighth part of the article features the description of the CSymbol class, which is a special object that provides access to any trading instrument. When used inside an Expert Advisor, the class provides a wide set of symbol properties, while allowing to simplify Expert Advisor programming and to expand its functionality.

In this article, we will consider the main aspects of integration of neural networks and the trading terminal, with the purpose of creating a fully featured trading robot.

This article is intended for developers who would be interested in using SQL in their projects. It explains the functionality and advantages of SQLite. The article does not require special knowledge of SQLite functions, yet minimum understanding of SQL would be beneficial.

This article describes the process of creating an extension for the MetaTrader terminal. The solution discussed helps to automate the optimization process by running optimizations in other terminals. A few more articles will be written concerning this topic. The extension has been developed using the C# language and design patterns, which additionally demonstrates the ability to expand the terminal capabilities by developing custom modules, as well as the ability to create custom graphical user interfaces using the functionality of a preferred programming language.