MQL5 Programming Articles
Study the MQL5 language for programming trading strategies in numerous published articles mostly written by you - the community members. The articles are grouped into categories to help you quicker find answers to any questions related to programming: Integration, Tester, Trading Strategies, etc.
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Automating Trading Strategies with Parabolic SAR Trend Strategy in MQL5: Crafting an Effective Expert Advisor
In this article, we will automate the trading strategies with Parabolic SAR Strategy in MQL5: Crafting an Effective Expert Advisor. The EA will make trades based on trends identified by the Parabolic SAR indicator.
Understanding functions in MQL5 with applications
Functions are critical things in any programming language, it helps developers apply the concept of (DRY) which means do not repeat yourself, and many other benefits. In this article, you will find much more information about functions and how we can create our own functions in MQL5 with simple applications that can be used or called in any system you have to enrich your trading system without complicating things.
Integrating AI model into already existing MQL5 trading strategy
This topic focuses on incorporating a trained AI model (such as a reinforcement learning model like LSTM or a machine learning-based predictive model) into an existing MQL5 trading strategy.
Interview with Juan Pablo Alonso Escobar (ATC 2012)
"Everyone who is struggling with programming and who were not able to participate in this year's competition, know that it becomes a lot easier in time", said Juan Pablo Alonso Escobar (JPAlonso), the hero of today's interview.
MQL5 Wizard techniques you should know (Part 06): Fourier Transform
The Fourier transform introduced by Joseph Fourier is a means of deconstructing complex data wave points into simple constituent waves. This feature could be resourceful to traders and this article takes a look at that.
Working with ONNX models in float16 and float8 formats
Data formats used to represent machine learning models play a crucial role in their effectiveness. In recent years, several new types of data have emerged, specifically designed for working with deep learning models. In this article, we will focus on two new data formats that have become widely adopted in modern models.
Creating a mean-reversion strategy based on machine learning
This article proposes another original approach to creating trading systems based on machine learning, using clustering and trade labeling for mean reversion strategies.
Library for easy and quick development of MetaTrader programs (part IX): Compatibility with MQL4 - Preparing data
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 eighth part, we implemented the class for tracking order and position modification events. Here, we will improve the library by making it fully compatible with MQL4.
The Kalman Filter for Forex Mean-Reversion Strategies
The Kalman filter is a recursive algorithm used in algorithmic trading to estimate the true state of a financial time series by filtering out noise from price movements. It dynamically updates predictions based on new market data, making it valuable for adaptive strategies like mean reversion. This article first introduces the Kalman filter, covering its calculation and implementation. Next, we apply the filter to a classic mean-reversion forex strategy as an example. Finally, we conduct various statistical analyses by comparing the filter with a moving average across different forex pairs.
Building an Interactive Application to Display RSS Feeds in MetaTrader 5
In this article we look at the possibility of creating an application for the display of RSS feeds. The article will show how aspects of the Standard Library can be used to create interactive programs for MetaTrader 5.
Monte Carlo Permutation Tests in MetaTrader 5
In this article we take a look at how we can conduct permutation tests based on shuffled tick data on any expert advisor using only Metatrader 5.
How to choose an Expert Advisor: Twenty strong criteria to reject a trading bot
This article tries to answer the question: how can we choose the right expert advisors? Which are the best for our portfolio, and how can we filter the large trading bots list available on the market? This article will present twenty clear and strong criteria to reject an expert advisor. Each criterion will be presented and well explained to help you make a more sustained decision and build a more profitable expert advisor collection for your profits.
Price Action Analysis Toolkit Development (Part 26): Pin Bar, Engulfing Patterns and RSI Divergence (Multi-Pattern) Tool
Aligned with our goal of developing practical price-action tools, this article explores the creation of an EA that detects pin bar and engulfing patterns, using RSI divergence as a confirmation trigger before generating any trading signals.
Neural networks made easy (Part 14): Data clustering
It has been more than a year since I published my last article. This is quite a lot time to revise ideas and to develop new approaches. In the new article, I would like to divert from the previously used supervised learning method. This time we will dip into unsupervised learning algorithms. In particular, we will consider one of the clustering algorithms—k-means.
Tips for Purchasing a Product on the Market. Step-By-Step Guide
This step-by-step guide provides tips and tricks for better understanding and searching for a required product. The article makes an attempt to puzzle out different methods of searching for an appropriate product, sorting out unwanted products, determining product efficiency and essentiality for you.
Learn how to design a trading system by Chaikin Oscillator
Welcome to our new article from our series about learning how to design a trading system by the most popular technical indicator. Through this new article, we will learn how to design a trading system by the Chaikin Oscillator indicator.
Gradient boosting in transductive and active machine learning
In this article, we will consider active machine learning methods utilizing real data, as well discuss their pros and cons. Perhaps you will find these methods useful and will include them in your arsenal of machine learning models. Transduction was introduced by Vladimir Vapnik, who is the co-inventor of the Support-Vector Machine (SVM).
Creating volatility forecast indicator using Python
In this article, we will forecast future extreme volatility using binary classification. Besides, we will develop an extreme volatility forecast indicator using machine learning.
Automated Parameter Optimization for Trading Strategies Using Python and MQL5
There are several types of algorithms for self-optimization of trading strategies and parameters. These algorithms are used to automatically improve trading strategies based on historical and current market data. In this article we will look at one of them with python and MQL5 examples.
A Library for Constructing a Chart via Google Chart API
The construction of various types of diagrams is an essential part of the analyses of the market situation and the testing of a trading system. Frequently, in order to construct a nice looking diagram, it is necessary to organize the data output into a file, after which it is used in applications such as MS Excel. This is not very convenient and deprives us of the ability to dynamically update the data. Google Charts API provided the means for creating charts in online modes, by sending a special request to the server. In this article we attempt to automate the process of creating such a request and obtaining a chart from the Google server.
Other classes in DoEasy library (Part 67): Chart object class
In this article, I will create the chart object class (of a single trading instrument chart) and improve the collection class of MQL5 signal objects so that each signal object stored in the collection updates all its parameters when updating the list.
Jeremy Scott - Successful MQL5 Market Seller
Jeremy Scott who is better known under Johnnypasado nickname at MQL5.community became famous offering products in our MQL5 Market service. Jeremy has already made several thousands of dollars in the Market and that is not the limit. We decided to take a closer look at the future millionaire and receive some pieces of advice for MQL5 Market sellers.
The Most Active MQL5.community Members Have Been Awarded iPhones!
After we decided to reward the most outstanding MQL5.com participants, we have selected the key criteria to determine each participant's contribution to the Community development. As a result, we have the following champions who published the greatest amount of articles on the website - investeo (11 articles) and victorg (10 articles), and who submitted their programs to Code Base – GODZILLA (340 programs), Integer (61 programs) and abolk (21 programs).
Automating Trading Strategies in MQL5 (Part 18): Envelopes Trend Bounce Scalping - Core Infrastructure and Signal Generation (Part I)
In this article, we build the core infrastructure for the Envelopes Trend Bounce Scalping Expert Advisor in MQL5. We initialize envelopes and other indicators for signal generation. We set up backtesting to prepare for trade execution in the next part.
Graphical interfaces X: New features for the Rendered table (build 9)
Until today, the CTable was the most advanced type of tables among all presented in the library. This table is assembled from edit boxes of the OBJ_EDIT type, and its further development becomes problematic. Therefore, in terms of maximum capabilities, it is better to develop rendered tables of the CCanvasTable type even at the current development stage of the library. Its current version is completely lifeless, but starting from this article, we will try to fix the situation.
Prices in DoEasy library (part 60): Series list of symbol tick data
In this article, I will create the list for storing tick data of a single symbol and check its creation and retrieval of required data in an EA. Tick data lists that are individual for each used symbol will further constitute a collection of tick data.
Graphics in DoEasy library (Part 87): Graphical object collection - managing object property modification on all open charts
In this article, I will continue my work on tracking standard graphical object events and create the functionality allowing users to control changes in the properties of graphical objects placed on any charts opened in the terminal.
Neural networks made easy (Part 36): Relational Reinforcement Learning
In the reinforcement learning models we discussed in previous article, we used various variants of convolutional networks that are able to identify various objects in the original data. The main advantage of convolutional networks is the ability to identify objects regardless of their location. At the same time, convolutional networks do not always perform well when there are various deformations of objects and noise. These are the issues which the relational model can solve.
Prices in DoEasy library (part 62): Updating tick series in real time, preparation for working with Depth of Market
In this article, I will implement updating tick data in real time and prepare the symbol object class for working with Depth of Market (DOM itself is to be implemented in the next article).
DoEasy. Controls (Part 2): Working on the CPanel class
In the current article, I will get rid of some errors related to handling graphical elements and continue the development of the CPanel control. In particular, I will implement the methods for setting the parameters of the font used by default for all panel text objects.
Calculation of Integral Characteristics of Indicator Emissions
Indicator emissions are a little-studied area of market research. Primarily, this is due to the difficulty of analysis that is caused by the processing of very large arrays of time-varying data. Existing graphical analysis is too resource intensive and has therefore triggered the development of a parsimonious algorithm that uses time series of emissions. This article demonstrates how visual (intuitive image) analysis can be replaced with the study of integral characteristics of emissions. It can be of interest to both traders and developers of automated trading systems.
Engineering Trading Discipline into Code (Part 2): Building a Daily Trade Limit Enforcer for All Trades in MQL5
We have developed a system that enforces a daily trade limit to keep you aligned with your trading rules. It monitors all executed trades across the account and automatically intervenes once the defined limit is reached, preventing any further activity. By embedding control directly into the platform, the system ensures discipline is maintained even when market pressure rises.
Gain An Edge Over Any Market
Learn how you can get ahead of any market you wish to trade, regardless of your current level of skill.
Timeseries in DoEasy library (part 58): Timeseries of indicator buffer data
In conclusion of the topic of working with timeseries organise storage, search and sort of data stored in indicator buffers which will allow to further perform the analysis based on values of the indicators to be created on the library basis in programs. The general concept of all collection classes of the library allows to easily find necessary data in the corresponding collection. Respectively, the same will be possible in the class created today.
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.
Ready-made templates for including indicators to Expert Advisors (Part 3): Trend indicators
In this reference article, we will look at standard indicators from the Trend Indicators category. We will create ready-to-use templates for indicator use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.
Creating an EA that works automatically (Part 15): Automation (VII)
To complete this series of articles on automation, we will continue discussing the topic of the previous article. We will see how everything will fit together, making the EA run like clockwork.
Cycle analysis using the Goertzel algorithm
In this article we present code utilities that implement the goertzel algorithm in Mql5 and explore two ways in which the technique can be used in the analysis of price quotes for possible strategy development.
Graphics in DoEasy library (Part 79): "Animation frame" object class and its descendant objects
In this article, I will develop the class of a single animation frame and its descendants. The class is to allow drawing shapes while maintaining and then restoring the background under them.
How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 5): Bollinger Bands On Keltner Channel — Indicators Signal
The Multi-Currency Expert Advisor in this article is an Expert Advisor or Trading Robot that can trade (open orders, close orders and manage orders for example: Trailing Stop Loss and Trailing Profit) for more than one symbol pair from only one symbol chart. In this article we will use signals from two indicators, in this case Bollinger Bands® on Keltner Channel.