MQL4 and MQL5 Programming Articles

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.

In this article, we start the development of the indicator buffer classes for the DoEasy library. We will create the base class of the abstract buffer which is to be used as a foundation for the development of different class types of indicator buffers.

The aim of this article is to investigate the possibilities of trade automation and the analysis, on the basis of some ideas from a book by James Hyerczyk "Pattern, Price & Time: Using Gann Theory in Trading Systems" in the form of indicators and Expert Advisor. Without claiming to be exhaustive, here we investigate only the Model - the first part of the Gann theory.

Let me offer you an overview and the program code of the mechanical trading system based on ideas of Stanislav Chuvashov. Triangle's construction is based on the intersection of two trend lines built by the upper and lower fractals.

EA Tree is the first drag and drop MetaTrader MQL5 Expert Advisor builder. You can create complex MQL5 using a very easy to use graphical user interface. In EA Tree, Expert Advisors are created by connecting boxes together. Boxes may contain MQL5 functions, technical indicators, custom indicators, or values. Using the "tree of boxes", EA Tree generates the MQL5 code of the Expert Advisor.

The article demonstrates the development of the ZigZag indicator in accordance with one of the sample specifications described in the article "How to prepare Requirements Specification when ordering an indicator". The indicator is built by extreme values defined using an oscillator. There is an ability to use one of five oscillators: WPR, CCI, Chaikin, RSI or Stochastic Oscillator.

In MQL5 you can write an indicator both from a scratch and on the basis of another already existing indicator, in-built in the client terminal or a custom one. And here you also have two ways - to improve an indicator by adding new calculations and graphical styles to it , or to use an indicator in-built in the client terminal or a custom one via the iCustom() or IndicatorCreate() functions.

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.

With the introduction of hedging, MetaTrader 5 provides an excellent opportunity to trade several Expert Advisors on a single trading account simultaneously. When one strategy is profitable, while the second one is loss-making, the profit graph may hang around zero. In this case, it is useful to build the Balance and Equity graphs for each trading strategy separately.

When developing trading algorithms, we often encounter a problem: how to determine where a trend/flat begins and ends? In this article, we try to create a universal indicator, in which we try to combine signals for different types of strategies. We will try to simplify the process of obtaining trade signals in an expert as much as possible. An example of combining several indicators in one will be given.

There are lots of chart types that provide information on the current market situation. Many of them, such as Point and Figure chart, are the legacy of the remote past. The article describes an example of Point and Figure charting using a real time indicator.

When writing an indicator that uses the short form of the OnCalculate() function call, you might miss the fact that an indicator can be calculated not only by price data, but also by data of some other indicator (no matter whether it is a built-in or custom one). Do you want to improve an indicator for its correct application to the other indicator's data? In this article we'll review all the steps required for such modification.

We continue the development of the functionality allowing users to trade using pending requests. In this article, we are going to implement the ability to place pending orders under certain conditions.

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.

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.

In this article, I offer my set of trading functions in the form of a ready-made EA. This method allows getting multiple trading strategies by simply adding indicators and changing inputs.

This article contains the description of writing a simple and convenient indicator displaying in a working area the main economic events from external Internet resources.

This is the continuation of Another MQL5 OOP class article which showed you how to build a simple OO EA from scratch and gave you some tips on object-oriented programming. Today I am showing you the technical basics needed to develop an EA able to trade the news. My goal is to keep on giving you ideas about OOP and also cover a new topic in this series of articles, working with the file system.

In the following article I am describing a process of implementing Moving Mini-Max indicator based on a paper by Z.G.Silagadze 'Moving Mini-max: a new indicator for technical analysis'. The idea of the indicator is based on simulation of quantum tunneling phenomena, proposed by G. Gamov in the theory of alpha decay.

Examined are the most frequent mistakes that lead the first-time programmers to creation of a "super-moneymaking" (when tested) trading systems. Exemplary experts that show fantastic results in tester, but result in losses during real trading are presented.

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.

Overbought/oversold zones characterize a certain state of the market, differentiating through weaker changes in the prices of securities. This adverse change in the synamics is pronounced most at the final stage in the development of trends of any scales. Since the profit value in trading depends directly on the capability of covering as large trend amplitude as possible, the accuracy of detecting such zones is a key task in trading with any securities whatsoever.

This article suggests the ways of improving manual trading strategy by applying fuzzy set theory. As an example we have provided a step-by-step description of the strategy search and the selection of its parameters, followed by fuzzy logic application to blur overly formal criteria for the market entry. This way, after strategy modification we obtain flexible conditions for opening a position that has a reasonable reaction to a market situation.

In the upcoming series of articles, I will demonstrate the development of self-adapting algorithms considering most market factors, as well as show how to systematize these situations, describe them in logic and take them into account in your trading activity. I will start with a very simple algorithm that will gradually acquire theory and evolve into a very complex project.

A simple, universal and reliable solution of information exchange between МetaТrader 4 Expert Advisor and the outside world. Suppliers and consumers of the information can be located on different computers, the connection is performed through the global IP addresses.

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.

The article describes the development and implementation of a class for sending signals based on pivots — reversal levels. This class is used to form a strategy applying the Standard Library. Improving the pivot strategy by adding filters is considered.

Creation of Custom Indicators in the MetaTrader trading system has a number of features.

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 fourth part, we tested tracking trading events on the account. In this article, we will develop trading event classes and place them to the event collections. From there, they will be sent to the base object of the Engine library and the control program chart.

The article offers basic tools for the OLAP analysis of tester reports relating to single passes and optimization results. The tool can work with standard format files (tst and opt), and it also provides a graphical interface. MQL source codes are attached below.

In this article, we will discuss how to develop a trading robot with minimum programming. Of course, MetaTrader 5 provides a high level of control over trading positions. However, using only the manual ability to place orders can be quite difficult and risky for less experienced users.

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.

Automate the collection of interest rate data to improve the performance of an Expert Advisor.

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 centers around strategies that actively use pending orders, a metalanguage that can be created to formally describe such strategies and the use of a multi-purpose Expert Advisor whose operation is based on those descriptions