Articles on MetaTrader 5 integration using MQL5

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Traders meet interesting challenges which often require an innovative approach. This category features articles that offer the most unexpected solutions for evaluating, analyzing and processing price data and trading results. The articles describe various integration solutions, including connection of databases and ICQ, use of OpenCL and social networks, use of Delphi and C#.

Read on to learn how to use specialized mathematical and neural packages, and much more. Become an author and share unique ideas with the MQL5.community members.

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CatBoost machine learning algorithm from Yandex with no Python or R knowledge required

CatBoost machine learning algorithm from Yandex with no Python or R knowledge required

The article provides the code and the description of the main stages of the machine learning process using a specific example. To obtain the model, you do not need Python or R knowledge. Furthermore, basic MQL5 knowledge is enough — this is exactly my level. Therefore, I hope that the article will serve as a good tutorial for a broad audience, assisting those interested in evaluating machine learning capabilities and in implementing them in their programs.
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Websockets for MetaTrader 5

Websockets for MetaTrader 5

Before the introduction of the network functionality provided with the updated MQL5 API, MetaTrader programs have been limited in their ability to connect and interface with websocket based services. But of course this has all changed, in this article we will explore the implementation of a websocket library in pure MQL5. A brief description of the websocket protocol will be given along with a step by step guide on how to use the resulting library.
Using cryptography with external applications
Using cryptography with external applications

Using cryptography with external applications

In this article, we consider encryption/decryption of objects in MetaTrader and in external applications. Our purpose is to determine the conditions under which the same results will be obtained with the same initial data.
Calculating mathematical expressions (Part 2). Pratt and shunting yard parsers
Calculating mathematical expressions (Part 2). Pratt and shunting yard parsers

Calculating mathematical expressions (Part 2). Pratt and shunting yard parsers

In this article, we consider the principles of mathematical expression parsing and evaluation using parsers based on operator precedence. We will implement Pratt and shunting-yard parser, byte-code generation and calculations by this code, as well as view how to use indicators as functions in expressions and how to set up trading signals in Expert Advisors based on these indicators.
MQL as a Markup Tool for the Graphical Interface of MQL Programs (Part 3). Form Designer
MQL as a Markup Tool for the Graphical Interface of MQL Programs (Part 3). Form Designer

MQL as a Markup Tool for the Graphical Interface of MQL Programs (Part 3). Form Designer

In this paper, we are completing the description of our concept of building the window interface of MQL programs, using the structures of MQL. Specialized graphical editor will allow to interactively set up the layout that consists of the basic classes of the GUI elements and then export it into the MQL description to use it in your MQL project. The paper presents the internal design of the editor and a user guide. Source codes are attached.
Native Twitter Client: Part 2
Native Twitter Client: Part 2

Native Twitter Client: Part 2

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.
Native Twitter Client for MT4 and MT5 without DLL
Native Twitter Client for MT4 and MT5 without DLL

Native Twitter Client for MT4 and MT5 without DLL

Ever wanted to access tweets and/or post your trade signals on Twitter ? Search no more, these on-going article series will show you how to do it without using any DLL. Enjoy the journey of implementing Twitter API using MQL. In this first part, we will follow the glory path of authentication and authorization in accessing Twitter API.
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Continuous Walk-Forward Optimization (Part 6): Auto optimizer's logical part and structure

Continuous Walk-Forward Optimization (Part 6): Auto optimizer's logical part and structure

We have previously considered the creation of automatic walk-forward optimization. This time, we will proceed to the internal structure of the auto optimizer tool. The article will be useful for all those who wish to further work with the created project and to modify it, as well as for those who wish to understand the program logic. The current article contains UML diagrams which present the internal structure of the project and the relationships between objects. It also describes the process of optimization start, but it does not contain the description of the optimizer implementation process.
MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 2
MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 2

MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 2

This paper continues checking the new conception to describe the window interface of MQL programs, using the structures of MQL. Automatically creating GUI based on the MQL markup provides additional functionality for caching and dynamically generating the elements and controlling the styles and new schemes for processing the events. Attached is an enhanced version of the standard library of controls.
MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 1
MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 1

MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 1

This paper proposes a new conception to describe the window interface of MQL programs, using the structures of MQL. Special classes transform the viewable MQL markup into the GUI elements and allow manage them, set up their properties, and process the events in a unified manner. It also provides some examples of using the markup for the dialogs and elements of a standard library.
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Continuous Walk-Forward Optimization (Part 5): Auto Optimizer project overview and creation of a GUI

Continuous Walk-Forward Optimization (Part 5): Auto Optimizer project overview and creation of a GUI

This article provides further description of the walk-forward optimization in the MetaTrader 5 terminal. In previous articles, we considered methods for generating and filtering the optimization report and started analyzing the internal structure of the application responsible for the optimization process. The Auto Optimizer is implemented as a C# application and it has its own graphical interface. The fifth article is devoted to the creation of this graphical interface.
Applying network functions, or MySQL without DLL: Part I - Connector
Applying network functions, or MySQL without DLL: Part I - Connector

Applying network functions, or MySQL without DLL: Part I - Connector

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.
How to create 3D graphics using DirectX in MetaTrader 5
How to create 3D graphics using DirectX in MetaTrader 5

How to create 3D graphics using DirectX in MetaTrader 5

3D graphics provide excellent means for analyzing huge amounts of data as they enable the visualization of hidden patterns. These tasks can be solved directly in MQL5, while DireсtX functions allow creating three-dimensional object. Thus, it is even possible to create programs of any complexity, even 3D games for MetaTrader 5. Start learning 3D graphics by drawing simple three-dimensional shapes.
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Continuous Walk-Forward Optimization (Part 3): Adapting a Robot to Auto Optimizer

Continuous Walk-Forward Optimization (Part 3): Adapting a Robot to Auto Optimizer

The third part serves as a bridge between the previous two parts: it describes the mechanism of interaction with the DLL considered in the first article and the objects for report downloading, which were described in the second article. We will analyze the process of wrapper creation for a class which is imported from DLL and which forms an XML file with the trading history. We will also consider a method for interacting with this wrapper.
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SQLite: Native handling of SQL databases in MQL5

SQLite: Native handling of SQL databases in MQL5

The development of trading strategies is associated with handling large amounts of data. Now, you are able to work with databases using SQL queries based on SQLite directly in MQL5. An important feature of this engine is that the entire database is placed in a single file located on a user's PC.
Optimization management (Part II): Creating key objects and add-on logic
Optimization management (Part II): Creating key objects and add-on logic

Optimization management (Part II): Creating key objects and add-on logic

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.
Optimization management (Part I): Creating a GUI
Optimization management (Part I): Creating a GUI

Optimization management (Part I): Creating a GUI

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.
Evaluating the ability of Fractal index and Hurst exponent to predict financial time series
Evaluating the ability of Fractal index and Hurst exponent to predict financial time series

Evaluating the ability of Fractal index and Hurst exponent to predict financial time series

Studies related to search for the fractal behavior of financial data suggest that behind the seemingly chaotic behavior of economic time series there are hidden stable mechanisms of participants' collective behavior. These mechanisms can lead to the emergence of price dynamics on the exchange, which can define and describe specific properties of price series. When applied to trading, one could benefit from the indicators which can efficiently and reliably estimate the fractal parameters in the scale and time frame, which are relevant in practice.
A DLL for MQL5 in 10 Minutes (Part II): Creating with Visual Studio 2017
A DLL for MQL5 in 10 Minutes (Part II): Creating with Visual Studio 2017

A DLL for MQL5 in 10 Minutes (Part II): Creating with Visual Studio 2017

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.
Using MATLAB 2018 computational capabilities in MetaTrader 5
Using MATLAB 2018 computational capabilities in MetaTrader 5

Using MATLAB 2018 computational capabilities in MetaTrader 5

After the upgrade of the MATLAB package in 2015, it is necessary to consider a modern way of creating DLL libraries. The article uses a sample predictive indicator to illustrate the peculiarities of linking MetaTrader 5 and MATLAB using modern 64-bit versions of the platforms, which are utilized nowadays. With the entire sequence of connecting MATLAB considered, MQL5 developers will be able to create applications with advanced computational capabilities much faster, avoiding «pitfalls».
Extracting structured data from HTML pages using CSS selectors
Extracting structured data from HTML pages using CSS selectors

Extracting structured data from HTML pages using CSS selectors

The article provides a description of a universal method for analyzing and converting data from HTML documents based on CSS selectors. Trading reports, tester reports, your favorite economic calendars, public signals, account monitoring and additional online quote sources will become available straight from MQL.
MetaTrader 5 and Python integration: receiving and sending data
MetaTrader 5 and Python integration: receiving and sending data

MetaTrader 5 and Python integration: receiving and sending data

Comprehensive data processing requires extensive tools and is often beyond the sandbox of one single application. Specialized programming languages are used for processing and analyzing data, statistics and machine learning. One of the leading programming languages for data processing is Python. The article provides a description of how to connect MetaTrader 5 and Python using sockets, as well as how to receive quotes via the terminal API.
MQL Parsing by Means of MQL
MQL Parsing by Means of MQL

MQL Parsing by Means of MQL

The article describes a preprocessor, a scanner, and a parser to be used in parsing the MQL-based source codes. MQL implementation is attached.
How to create and test custom MOEX symbols in MetaTrader 5
How to create and test custom MOEX symbols in MetaTrader 5

How to create and test custom MOEX symbols in MetaTrader 5

The article describes the creation of a custom exchange symbol using the MQL5 language. In particular, it considers the use of exchange quotes from the popular Finam website. Another option considered in this article is the possibility to work with an arbitrary format of text files used in the creation of the custom symbol. This allows working with any financial symbols and data sources. After creating a custom symbol, we can use all the capabilities of the MetaTrader 5 Strategy Tester to test trading algorithms for exchange instruments.
Using OpenCL to test candlestick patterns
Using OpenCL to test candlestick patterns

Using OpenCL to test candlestick patterns

The article describes the algorithm for implementing the OpenCL candlestick patterns tester in the "1 minute OHLC" mode. We will also compare its speed with the built-in strategy tester launched in the fast and slow optimization modes.
950 websites broadcast the Economic Calendar from MetaQuotes
950 websites broadcast the Economic Calendar from MetaQuotes

950 websites broadcast the Economic Calendar from MetaQuotes

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.
Integrating MQL-based Expert Advisors and databases (SQL Server, .NET and C#)
Integrating MQL-based Expert Advisors and databases (SQL Server, .NET and C#)

Integrating MQL-based Expert Advisors and databases (SQL Server, .NET and C#)

The article describes how to add the ability to work with Microsoft SQL Server database server to MQL5-based Expert Advisors. Import of functions from a DLL is used. The DLL is created using the Microsoft .NET platform and the C# language. The methods used in the article are also suitable for experts written in MQL4, with minor adjustments.
Deep Neural Networks (Part VII). Ensemble of neural networks: stacking
Deep Neural Networks (Part VII). Ensemble of neural networks: stacking

Deep Neural Networks (Part VII). Ensemble of neural networks: stacking

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.