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.
Follow our new publications and discuss them on the Forum!
Add a new article
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
Multiple indicators on one chart (Part 05): Turning MetaTrader 5 into a RAD system (I)
There are a lot of people who do not know how to program but they are quite creative and have great ideas. However, the lack of programming knowledge prevents them from implementing these ideas. Let's see together how to create a Chart Trade using the MetaTrader 5 platform itself, as if it were an IDE.
How to create a custom True Strength Index indicator using MQL5
Here is a new article about how to create a custom indicator. This time we will work with the True Strength Index (TSI) and will create an Expert Advisor based on it.
MQL5 Wizard Techniques you should know (Part 48): Bill Williams Alligator
The Alligator Indicator, which was the brain child of Bill Williams, is a versatile trend identification indicator that yields clear signals and is often combined with other indicators. The MQL5 wizard classes and assembly allow us to test a variety of signals on a pattern basis, and so we consider this indicator as well.
Building a Trading System (Part 1): A Quantitative Approach
Many traders evaluate strategies based on short-term performance, often abandoning profitable systems too early. Long-term profitability, however, depends on positive expectancy through optimized win rate and risk-reward ratio, along with disciplined position sizing. These principles can be validated using Monte Carlo simulation in Python with back-tested metrics to assess whether a strategy is robust or likely to fail over time.
Selection and navigation utility in MQL5 and MQL4: Adding "homework" tabs and saving graphical objects
In this article, we are going to expand the capabilities of the previously created utility by adding tabs for selecting the symbols we need. We will also learn how to save graphical objects we have created on the specific symbol chart, so that we do not have to constantly create them again. Besides, we will find out how to work only with symbols that have been preliminarily selected using a specific website.
Prices in DoEasy library (part 61): Collection of symbol tick series
Since a program may use different symbols in its work, a separate list should be created for each of them. In this article, I will combine such lists into a tick data collection. In fact, this will be a regular list based on the class of dynamic array of pointers to instances of CObject class and its descendants of the Standard library.
Technical Analysis: How Do We Analyze?
This article briefly describes the author's opinion on redrawing indicators, multi-timeframe indicators and displaying of quotes with Japanese candlesticks. The article contain no programming specifics and is of a general character.
Reimagining Classic Strategies (Part 13): Minimizing The Lag in Moving Average Cross-Overs
Moving average cross-overs are widely known by traders in our community, and yet the core of the strategy has changed very little since its inception. In this discussion, we will present you with a slight adjustment to the original strategy, that aims to minimize the lag present in the trading strategy. All fans of the original strategy, could consider revising the strategy in accordance with the insights we will discuss today. By using 2 moving averages with the same period, we reduce the lag in the trading strategy considerably, without violating the foundational principles of the strategy.
Implementing the Deus EA: Automated Trading with RSI and Moving Averages in MQL5
This article outlines the steps to implement the Deus EA based on the RSI and Moving Average indicators for guiding automated trading.
Graphics in DoEasy library (Part 90): Standard graphical object events. Basic functionality
In this article, I will implement the basic functionality for tracking standard graphical object events. I will start from a double click event on a graphical object.
CCI indicator. Three transformation steps
In this article, I will make additional changes to the CCI affecting the very logic of this indicator. Moreover, we will be able to see it in the main chart window.
Price Action Analysis Toolkit Development (Part 13): RSI Sentinel Tool
Price action can be effectively analyzed by identifying divergences, with technical indicators such as the RSI providing crucial confirmation signals. In the article below, we explain how automated RSI divergence analysis can identify trend continuations and reversals, thereby offering valuable insights into market sentiment.
Developing a trading Expert Advisor from scratch (Part 22): New order system (V)
Today we will continue to develop the new order system. It is not that easy to implement a new system as we often encounter problems which greatly complicate the process. When these problems appear, we have to stop and re-analyze the direction in which we are moving.
Category Theory in MQL5 (Part 1)
Category Theory is a diverse and expanding branch of Mathematics which as of yet is relatively uncovered in the MQL community. These series of articles look to introduce and examine some of its concepts with the overall goal of establishing an open library that attracts comments and discussion while hopefully furthering the use of this remarkable field in Traders' strategy development.
Electronic Tables in MQL5
The article describes a class of dynamic two-dimensional array that contains data of different types in its first dimension. Storing data in the form of a table is convenient for solving a wide range of problems of arrangement, storing and operation with bound information of different types. The source code of the class that implements the functionality of working with tables is attached to the article.
Deep Learning GRU model with Python to ONNX with EA, and GRU vs LSTM models
We will guide you through the entire process of DL with python to make a GRU ONNX model, culminating in the creation of an Expert Advisor (EA) designed for trading, and subsequently comparing GRU model with LSTM model.
DoEasy. Controls (Part 13): Optimizing interaction of WinForms objects with the mouse, starting the development of the TabControl WinForms object
In this article, I will fix and optimize handling the appearance of WinForms objects after moving the mouse cursor away from the object, as well as start the development of the TabControl WinForms object.
How to add Trailing Stop using Parabolic SAR
When creating a trading strategy, we need to test a variety of protective stop options. Here is where a dynamic pulling up of the Stop Loss level following the price comes to mind. The best candidate for this is the Parabolic SAR indicator. It is difficult to think of anything simpler and visually clearer.
Automating Trading Strategies in MQL5 (Part 30): Creating a Price Action AB-CD Harmonic Pattern with Visual Feedback
In this article, we develop an AB=CD Pattern EA in MQL5 that identifies bullish and bearish AB=CD harmonic patterns using pivot points and Fibonacci ratios, executing trades with precise entry, stop loss, and take-profit levels. We enhance trader insight with visual feedback through chart objects.
Creating an MQL5-Telegram Integrated Expert Advisor (Part 5): Sending Commands from Telegram to MQL5 and Receiving Real-Time Responses
In this article, we create several classes to facilitate real-time communication between MQL5 and Telegram. We focus on retrieving commands from Telegram, decoding and interpreting them, and sending appropriate responses back. By the end, we ensure that these interactions are effectively tested and operational within the trading environment
Build Self Optimizing Expert Advisors With MQL5 And Python
In this article, we will discuss how we can build Expert Advisors capable of autonomously selecting and changing trading strategies based on prevailing market conditions. We will learn about Markov Chains and how they can be helpful to us as algorithmic traders.
Data Science and Machine Learning (Part 12): Can Self-Training Neural Networks Help You Outsmart the Stock Market?
Are you tired of constantly trying to predict the stock market? Do you wish you had a crystal ball to help you make more informed investment decisions? Self-trained neural networks might be the solution you've been looking for. In this article, we explore whether these powerful algorithms can help you "ride the wave" and outsmart the stock market. By analyzing vast amounts of data and identifying patterns, self-trained neural networks can make predictions that are often more accurate than human traders. Discover how you can use this cutting-edge technology to maximize your profits and make smarter investment decisions.
Building AI-Powered Trading Systems in MQL5 (Part 2): Developing a ChatGPT-Integrated Program with User Interface
In this article, we develop a ChatGPT-integrated program in MQL5 with a user interface, leveraging the JSON parsing framework from Part 1 to send prompts to OpenAI’s API and display responses on a MetaTrader 5 chart. We implement a dashboard with an input field, submit button, and response display, handling API communication and text wrapping for user interaction.
Marvel Your MQL5 Customers with a Usable Cocktail of Technologies!
MQL5 provides programmers with a very complete set of functions and object-oriented API thanks to which they can do everything they want within the MetaTrader environment. However, Web Technology is an extremely versatile tool nowadays that may come to the rescue in some situations when you need to do something very specific, want to marvel your customers with something different or simply you do not have enough time to master a specific part of MT5 Standard Library. Today's exercise walks you through a practical example about how you can manage your development time at the same time as you also create an amazing tech cocktail.
Experiments with neural networks (Part 5): Normalizing inputs for passing to a neural network
Neural networks are an ultimate tool in traders' toolkit. Let's check if this assumption is true. MetaTrader 5 is approached as a self-sufficient medium for using neural networks in trading. A simple explanation is provided.
MQL5 Wizard techniques you should know (Part 03): Shannon's Entropy
Todays trader is a philomath who is almost always looking up new ideas, trying them out, choosing to modify them or discard them; an exploratory process that should cost a fair amount of diligence. These series of articles will proposition that the MQL5 wizard should be a mainstay for traders.
Automating The Market Sentiment Indicator
In this article, we automate a custom market sentiment indicator that classifies market conditions into bullish, bearish, risk-on, risk-off, and neutral. The Expert Advisor delivers real-time insights into prevailing sentiment while streamlining the analysis process for current market trends or direction.
Using Assertions in MQL5 Programs
This article covers the use of assertions in MQL5 language. It provides two examples of the assertion mechanism and some general guidance for implementing assertions.
Multiple indicators on one chart (Part 03): Developing definitions for users
Today we will update the functionality of the indicator system for the first time. In the previous article within the "Multiple indicators on one chart" we considered the basic code which allows using more than one indicator in a chart subwindow. But what was presented was just the starting base of a much larger system.
Introduction to MQL5 (Part 15): A Beginner's Guide to Building Custom Indicators (IV)
In this article, you'll learn how to build a price action indicator in MQL5, focusing on key points like low (L), high (H), higher low (HL), higher high (HH), lower low (LL), and lower high (LH) for analyzing trends. You'll also explore how to identify the premium and discount zones, mark the 50% retracement level, and use the risk-reward ratio to calculate profit targets. The article also covers determining entry points, stop loss (SL), and take profit (TP) levels based on the trend structure.
Moving Average in MQL5 from scratch: Plain and simple
Using simple examples, we will examine the principles of calculating moving averages, as well as learn about the ways to optimize indicator calculations, including moving averages.
Developing a Replay System — Market simulation (Part 02): First experiments (II)
This time, let's try a different approach to achieve the 1 minute goal. However, this task is not as simple as one might think.
Improve Your Trading Charts With Interactive GUI's in MQL5 (Part I): Movable GUI (I)
Unleash the power of dynamic data representation in your trading strategies or utilities with our comprehensive guide on creating movable GUI in MQL5. Dive into the core concept of chart events and learn how to design and implement simple and multiple movable GUI on the same chart. This article also explores the process of adding elements to your GUI, enhancing their functionality and aesthetic appeal.
Trend strength and direction indicator on 3D bars
We will consider a new approach to market trend analysis based on three-dimensional visualization and tensor analysis of the market microstructure.
Data Science and Machine Learning (Part 07): Polynomial Regression
Unlike linear regression, polynomial regression is a flexible model aimed to perform better at tasks the linear regression model could not handle, Let's find out how to make polynomial models in MQL5 and make something positive out of it.
Better Programmer (Part 03): Give Up doing these 5 things to become a successful MQL5 Programmer
This is the must-read article for anyone wanting to improve their programming career. This article series is aimed at making you the best programmer you can possibly be, no matter how experienced you are. The discussed ideas work for MQL5 programming newbies as well as professionals.
Classification models in the Scikit-Learn library and their export to ONNX
In this article, we will explore the application of all classification models available in the Scikit-Learn library to solve the classification task of Fisher's Iris dataset. We will attempt to convert these models into ONNX format and utilize the resulting models in MQL5 programs. Additionally, we will compare the accuracy of the original models with their ONNX versions on the full Iris dataset.
Parallel Particle Swarm Optimization
The article describes a method of fast optimization using the particle swarm algorithm. It also presents the method implementation in MQL, which is ready for use both in single-threaded mode inside an Expert Advisor and in a parallel multi-threaded mode as an add-on that runs on local tester agents.
How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 7): ZigZag with Awesome Oscillator Indicators Signal
The multi-currency expert advisor in this article is an expert advisor or automated trading that uses ZigZag indicator which are filtered with the Awesome Oscillator or filter each other's signals.
Statistical Arbitrage with predictions
We will walk around statistical arbitrage, we will search with python for correlation and cointegration symbols, we will make an indicator for Pearson's coefficient and we will make an EA for trading statistical arbitrage with predictions done with python and ONNX models.