MQL4 and MQL5 Programming Articles

Testing manual strategies on history. Check how your trading algorithm works turning a deaf ear to programming niceties!

The main difference of the trading system proposed in the article is the use of mathematical tools for analyzing stock quotes. The system applies digital filtering and spectral estimation of discrete time series. The theoretical aspects of the strategy are described and a test Expert Advisor is created.

In this article, we will consider an example of developing a user interface with button controls. To convey the idea of interactivity to the user, buttons will change their colors when the cursor hovers over them. With the cursor being over a button, the button color will be slightly darkened, getting significantly darker when the button is clicked. Furthermore, we will add tooltips to each button, thus creating an intuitive interface.

The article proposes Kagi chart indicator with various charting options and additional functions. Also, indicator charting principle and its MQL5 implementation features are considered. The most popular cases of its implementation in trading are displayed - Yin/Yang exchange strategy, pushing away from the trend line and consistently increasing "shoulders"/decreasing "waists".

In the previous part, we considered the implementation of the MySQL connector. In this article, we will consider its application by implementing the service for collecting signal properties and the program for viewing their changes over time. The implemented example has practical sense if users need to observe changes in properties that are not displayed on the signal's web page.

The article presents a new version of the Pattern Analyzer application. This version provides bug fixes and new features, as well as the revised user interface. Comments and suggestions from previous article were taken into account when developing the new version. The resulting application is described in this article.

In this article, we will fiddle around ChatGPT from OpenAI in order to understand its capabilities in terms of reducing the time and labor intensity of developing Expert Advisors, indicators and scripts. I will quickly navigate you through this technology and try to show you how to use it correctly for programming in MQL4 and MQL5.

In this article, we will expand the capabilities of the toolkit: we will add the ability to close trade positions upon specific conditions and will create tables for controlling market and pending orders, with the ability to edit these orders.

This article discusses the creation of an order manager for a cross-platform expert advisor. The order manager is responsible for the entry and exit of orders or positions entered by the expert, as well as for keeping an independent record of such trades that is usable for both versions.

The article describes a method of modifying the code of a trading signal module for the implementation of the functionality allowing you to set pending orders at any distance from the current price: it may be the Close or Open price of the previous bar or the value of the moving average. There are plenty of options. Important is that you can set any opening price for a pending order. This article will be useful to traders who trade with pending orders.

All channel indicators are displayed as three lines, including central, top and bottom lines. The drawing principle of the central line is similar to a moving average, while the moving average indicator is mostly used for drawing channels. The top and bottom lines are located at equal distances from the central line. This distance can be determined in points, as percent of price (the Envelopes indicator), using a standard deviation value (Bollinger Bands), or an ATR value (Keltner channel).

Surfing the Internet, it is easy to find many strategies, which will give you a number of various recommendations. Let’s take an insider’s approach and look into the process of strategy creation, based on the differences in timezones on different continents.

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 continue our learning series — this time we will learn how to design a trading system using one of the most popular and useful indicators, which is the Stochastic Oscillator indicator, to build a new block in our knowledge of basics.

MetaTrader 4 and MetaTrader 5 uses different conventions in processing trade requests. This article discusses the possibility of using a class object that can be used to represent the trades processed by the server, in order for a cross-platform expert advisor to further work on them, regardless of the version of the trading platform and mode being used.

The article describes how to create a framework for the online analysis of multidimensional data (OLAP), as well as how to implement this in MQL and to apply such analysis in the MetaTrader environment using the example of trading account history processing.

This article seeks to upgrade the indicator created earlier on and briefly deals with a method for estimating forecast confidence intervals using bootstrapping and quantiles. As a result, we will get the forecast indicator and scripts to be used for estimation of the forecast accuracy.

Genetic (evolutionary) algorithms are used for optimization purposes. An example of such purpose can be neuronet learning, i.e., selection of such weight values that allow reaching the minimum error. At this, the genetic algorithm is based on the random search method.

The article is devoted to the practical application of the fuzzy logic concept for financial markets analysis. We propose the example of the indicator generating signals based on two fuzzy rules based on Envelopes indicator. The developed indicator uses several indicator buffers: 7 buffers for calculations, 5 buffers for the charts display and 2 color buffers.

In the article, we continue to develop the MQL application for working with optimization results. This time, we will show how to form the table of the best results after optimizing the parameters by specifying another criterion via the graphical interface.

In the previous articles, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. We already have collections of historical orders and deals, market orders and positions, as well as the class for convenient selection and sorting of orders. In this part, we will continue the development of the base object and teach the Engine Library to track trading events on the account.

The article suggests a technology helping everyone to create custom trading strategies by assembling an individual indicator set, as well as to develop custom market entry signals.

The article considers the development of a simple multi-period indicator based on the DoEasy library. Let's improve the timeseries classes to receive data from any timeframes to display it on the current chart period.

The article gives formulas and the calculation order for data shown in the Tester report.

In this article, we will apply the probability theory and mathematical statistics methods to creating and testing trading strategies. We will also look for optimal trading risk using the differences between the price and the random walk. It is proved that if prices behave like a zero-drift random walk (with no directional trend), then profitable trading is impossible.

This article describes a special algorithm allowing to gain access to elements by their unique keys. Any base data type can be used as a key. For example it may be represented as a string or an integer variable. Such data container is commonly referred to as a dictionary or an associative array. It provides easier and more efficient way of problem solving.

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.

This article introduces the “Multi-Timeframe Harmony Index”—an advanced Expert Advisor for MetaTrader 5 that calculates a weighted bias from multiple timeframes, smooths the readings using EMA, and displays the results in a clean chart panel dashboard. It includes customizable alerts and automatic buy/sell signal plotting when strong bias thresholds are crossed. Suitable for traders who use multi-timeframe analysis to align entries with overall market structure.

Environment MQL4 is based on the conception of safe "sandbox": reading and saving files using the language are allowed in some predefined folders only. This protects the user of MetaTrader 4 from the potential danger of damaging important data on the HDD. However, it is sometimes necessary to leave that safe area. This article is devoted to the problem of how to do it easily and correctly.

In this article, we continue to dwell on reversing techniques. We will try to reduce the maximum balance drawdown till an acceptable level for the instruments considered earlier. We will see if the measures will reduce the profit. We will also check how the reversing method performs on other markets, including stock, commodity, index, ETF and agricultural markets. Attention, the article contains a lot of images!

This article suggests a variant of an adaptive system that consists of many strategies, each of which performs its own "virtual" trade operations. Real trading is performed in accordance with the signals of a most profitable strategy at the moment. Thanks to using of the object-oriented approach, classes for working with data and trade classes of the Standard library, the architecture of the system appeared to be simple and scalable; now you can easily create and analyze the adaptive systems that include hundreds of trade strategies.

The article deals with conflict-free trading of several experts on one МТ 4 Client Terminal. It will be useful for those who have basic command of working with the terminal and programming in MQL 4.

In the article, we will consider a sample multi-symbol multi-period indicator using the timeseries classes of the DoEasy library displaying the chart of a selected currency pair on a selected timeframe as candles in a subwindow. I am going to modify the library classes a bit and create a separate file for storing enumerations for program inputs and selecting a compilation language.

This article has been made to show you how to use neural networks, via FANN2MQL, using an easy example: teaching a simple pattern to the neuralnetwork, and testing it to see if it can recognize patterns it has never seen.

The article deals with the methods of indicators computational algorithms optimization. Everyone will find a method that suits his/her needs best. Three methods are described here.One of them is quite simple, the next one requires solid knowledge of Math and the last one requires some wit. Indicators or MetaTrader5 terminal design features are used to realize most of the described methods. The methods are quite universal and can be used not only for acceleration of the linear regression calculation, but also for many other indicators.

This is a continuation of the idea of processing and analysis of optimization results. This time, our purpose is to select the 100 best optimization results and display them in a GUI table. The user will be able to select a row in the optimization results table and receive a multi-symbol balance and drawdown graph on separate charts.

It is impossible to get a truly stable algorithm if we use optimization based on historical data to select parameters. A stable algorithm should be aware of what parameters are needed when working on any trading instrument at any time. It should not forecast or guess, it should know for sure.

The article deals with the simultaneous launch of Expert Advisor testing on four different trading instruments. The final comparison of four testing reports is provided in a table similar to how goods are represented in online stores. An additional bonus is that distribution charts will be automatically created for each symbol.