MQL5 Programming Articles

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

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

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.

In this article, we develop a Nick Rypock Trailing Reverse (NRTR) trading system in MQL5 that uses channel indicators for reversal signals, enabling trend-following entries with hedging support for buys and sells. We incorporate risk management features like auto lot sizing based on equity or balance, fixed or dynamic stop-loss and take-profit levels using ATR multipliers, and position limits.

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

Do you need more than awkward graphics of moving averages? Do you want to draw something more beautiful than a simple filled rectangle in your terminal? Attractive graphics can be drawn in the terminal. This can be implemented through the CСanvas class, which is used for creating custom graphics. With this class you can implement transparency, blend colors and produce the illusion of transparency by means of overlapping and blending colors.

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.

The article deals with the approaches enabling accurate simulation of walk forward optimization using the built-in tester and auxiliary libraries implemented in MQL.

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.

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.

In this article, we will analyze the concept of correlation between variables, as well as methods for the calculation of correlation coefficients and their practical use in trading. Correlation is a statistical relationship between two or more random variables (or quantities which can be considered random with some acceptable degree of accuracy). Changes in one ore more variables lead to systematic changes of other related variables.

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.

In this article, we will consider such issues as including sound files in the file of the Expert Advisor, and thus adding sound notifications to trade events. The fact that the files will be included means that the sound files will be located inside the Expert Advisor. So when giving the compiled version of the Expert Advisor (*.ex5) to another user, you will not have to also provide the sound files and explain where they need to be saved.

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 consider yet another custom trading strategy optimization criterion based on the balance graph analysis. The linear regression is calculated using the function from the ALGLIB library.

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.

The article describes the process of developing and implementing a class for sending signals based on the moving channels. Each of the signal version is followed by a trading strategy with testing results. Classes of the Standard Library are used for creating derived classes.

This article will describe an implementation of a simple approach suitable for a multi-currency Expert Advisor. This means that you will be able to set up the Expert Advisor for testing/trading under identical conditions but with different parameters for each symbol. As an example, we will create a pattern for two symbols but in such a way so as to be able to add additional symbols, if necessary, by making small changes to the code.

The article describes the basic principles and methods that allow you to analyze any strategy using spreadsheets (Excel, Calc, Google). The obtained results are compared with MetaTrader 5 tester.

This article is an introduction to a series of articles about programming. It is assumed here that the reader has never dealt with programming before. So, this series starts from the very basics. Programming knowledge level: Absolute Beginner.

Functions and code snippets that simplify and clarify the handling of time, broker offset, and the changes to summer or winter time. Accurate timing may be a crucial element in trading. At the current hour, is the stock exchange in London or New York already open or not yet open, when does the trading time for Forex trading start and end? For a trader who trades manually and live, this is not a big problem.

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.