MQL4 and MQL5 Programming Articles

The article presents an extended study of seasonal characteristics: autocorrelation heat maps and scatter plots. The purpose of the article is to show that "market memory" is of seasonal nature, which is expressed through maximized correlation of increments of arbitrary order.

In the previous article, we have created the classes of pending request objects corresponding to the general concept of library objects. This time, we are going to deal with the class allowing the management of pending request objects.

In the previous articles, we checked the concept of pending trading requests. A pending request is, in fact, a common trading order executed by a certain condition. In this article, we are going to create full-fledged classes of pending request objects — a base request object and its descendants.

This is the third article about the concept of pending requests. We are going to complete the tests of pending trading requests by creating the methods for closing positions, removing pending orders and modifying position and pending order parameters.

In this article, we will continue the development of trading requests, implement placing pending orders and eliminate detected shortcomings of the trading class operation.

In this article, we are going to store some data in the value of the orders and positions magic number and start the implementation of pending requests. To check the concept, let's create the first test pending request for opening market positions when receiving a server error requiring waiting and sending a repeated request.

In this article we will view seasonal characteristics of financial time series using Boxplot diagrams. Each separate boxplot (or box-and-whiskey diagram) provides a good visualization of how values are distributed along the dataset. Boxplots should not be confused with the candlestick charts, although they can be visually similar.

After we send a trading order to the server, we need to check the error codes or the absence of errors. In this article, we will consider handling errors returned by the trade server and prepare for creating pending trading requests.

In the previous two articles, we discussed the application of Merrill patterns to various data types. An application was developed to test the presented ideas. In this article, we will continue working with the Strategy Builder, to improve its efficiency and to implement new features and capabilities.

In this article, we will have a look at the handler of invalid trading order parameters and improve the trading event class. Now all trading events (both single ones and the ones occurred simultaneously within one tick) will be defined in programs correctly.

In the article, we continue the development of the trading class by implementing the control over incorrect trading order parameter values and voicing trading events.

In this article, we will start the development of the library base trading class and add the initial verification of permissions to conduct trading operations to its first version. Besides, we will slightly expand the features and content of the base trading class.

In this article, we will start the development of the new library section - trading classes. Besides, we will consider the development of a unified base trading object for MetaTrader 5 and MetaTrader 4 platforms. When sending a request to the server, such a trading object implies that verified and correct trading request parameters are passed to it.

The article deals with storing data in the program's source code and creating audio and graphical files out of them. When developing an application, we often need audio and images. The MQL language features several methods of using such data.

When developing indicators, Expert Advisors and scripts, developers often need to create various pieces of code, which are not directly related to the trading strategy. In this article, we consider a way to create Expert Advisors using earlier created blocks, such as trailing, filtering and scheduling code, among others. We will see the benefits of this programming approach.

In this article, we will consider the class of displaying text messages. Currently, we have a sufficient number of different text messages. It is time to re-arrange the methods of their storage, display and translation of Russian or English messages to other languages. Besides, it would be good to introduce convenient ways of adding new languages to the library and quickly switching between them.

The article arranges the work of an account object on a new base object of all library objects, improves the CBaseObj base object and tests setting tracked parameters, as well as receiving events for any library objects.

In this article, we are going to finish the development of the base object of all library objects, so that any library object based on it is able to interact with a user. For example, users will be able to set the maximum acceptable size of a spread for opening a position and a price level, upon reaching which an event from a symbol object is sent to the program with the spread or price level-based signal.

In the previous article, we considered application of Merrill patterns to various data, such as to a price value on a currency symbol chart and values of standard MetaTrader 5 indicators: ATR, WPR, CCI, RSI, among others. Now, let us try to create a strategy construction set based on Merrill patterns.

In this article, we will create a new base class of all library objects adding the event functionality to all its descendants and develop the class for tracking symbol collection events based on the new base class. We will also change account and account event classes for developing the new base object functionality.

In previous articles within this series, we tried various methods for creating a more or less profitable grid Expert Advisor. Now we will try to increase the EA profitability through diversification. Our ultimate goal is to reach 100% profit per year with the maximum balance drawdown no more than 20%.

The article considers an approach to stress testing of a trading strategy using custom symbols. A custom symbol class is created for this purpose. This class is used to receive tick data from third-party sources, as well as to change symbol properties. Based on the results of the work done, we will consider several options for changing trading conditions, under which a trading strategy is being tested.

This article presents Pivot Mean Oscillator (PMO), an implementation of the cumulative moving average (CMA) as a trading indicator for the MetaTrader platforms. In particular, we first introduce Pivot Mean (PM) as a normalization index for timeseries that computes the fraction between any data point and the CMA. We then build PMO as the difference between the moving averages applied to two PM signals. Some preliminary experiments carried out on the EURUSD symbol to test the efficacy of the proposed indicator are also reported, leaving ample space for further considerations and improvements.

The article provides the description of a simple HTML code parsing library using third-party components. In particular, it covers the possibilities of accessing data which cannot be retrieved using GET and POST requests. We will select a website with not too large pages and will try to obtain interesting data from this site.

In this article, we will consider creation of a symbol collection based on the abstract symbol object developed in the previous article. The abstract symbol descendants are to clarify a symbol data and define the availability of the basic symbol object properties in a program. Such symbol objects are to be distinguished by their affiliation with groups.

The article provides a critical examination of regular divergence and efficiency of various indicators. In addition, it contains filtering options for an increased analysis accuracy and features description of non-standard solutions. As a result, we will create a new tool for solving the technical task.

In this article, we will have a look at Merrill patterns' model and try to evaluate their current relevance. To do this, we will develop a tool to test the patterns and apply the model to various data types such as Close, High and Low prices, as well as oscillators.

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.

In this article, we will create the class of a symbol object that is to be the basic object for creating the symbol collection. The class will allow us to obtain data on the necessary symbols for their further analysis and comparison.

The article considers working with account events for tracking important changes in account properties affecting the automated trading. We have already implemented some functionality for tracking account events in the previous article when developing the account object collection.

In the previous article, we defined position closure events for MQL4 in the library and got rid of the unused order properties. Here we will consider the creation of the Account object, develop the collection of account objects and prepare the functionality for tracking account events.

We continue the development of a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. In the tenth part, we resumed our work on the library compatibility with MQL4 and defined the events of opening positions and activating pending orders. In this article, we will define the events of closing positions and get rid of the unused order properties.

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.

In this article, we will make an attempt to develop the best possible grid-based EA. As usual, this will be a cross-platform EA capable of working both with MetaTrader 4 and MetaTrader 5. The first EA was good enough, except that it could not make a profit over a long period of time. The second EA could work at intervals of more than several years. Unfortunately, it was unable to yield more than 50% of profit per year with a maximum drawdown of less than 50%.

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 ninth part, we started improving the library classes for working with MQL4. Here we will continue improving the library to ensure its full compatibility with MQL4.