MQL4 and 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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News Trading Made Easy (Part 1): Creating a Database
News trading can be complicated and overwhelming, in this article we will go through steps to obtain news data. Additionally we will learn about the MQL5 Economic Calendar and what it has to offer.
Build Self Optimizing Expert Advisors in MQL5 (Part 5): Self Adapting Trading Rules
The best practices, defining how to safely us an indicator, are not always easy to follow. Quiet market conditions may surprisingly produce readings on the indicator that do not qualify as a trading signal, leading to missed opportunities for algorithmic traders. This article will suggest a potential solution to this problem, as we discuss how to build trading applications capable of adapting their trading rules to the available market data.
MQL5 Market Results for Q1 2013
Since its founding, the store of trading robots and technical indicators MQL5 Market has already attracted more than 250 developers who have published 580 products. The first quarter of 2013 has turned out to be quite successful for some MQL5 Market sellers who have managed to make handsome profit by selling their products.
Ready-made templates for including indicators to Expert Advisors (Part 1): Oscillators
The article considers standard indicators from the oscillator category. We will create ready-to-use templates for their use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.
Reimagining Classic Strategies (Part 12): EURUSD Breakout Strategy
Join us today as we challenge ourselves to build a profitable break-out trading strategy in MQL5. We selected the EURUSD pair and attempted to trade price breakouts on the hourly timeframe. Our system had difficulty distinguishing between false breakouts and the beginning of true trends. We layered our system with filters intended to minimize our losses whilst increasing our gains. In the end, we successfully made our system profitable and less prone to false breakouts.
Matrices and vectors in MQL5: Activation functions
Here we will describe only one of the aspects of machine learning - activation functions. In artificial neural networks, a neuron activation function calculates an output signal value based on the values of an input signal or a set of input signals. We will delve into the inner workings of the process.
MQL5 Trading Tools (Part 3): Building a Multi-Timeframe Scanner Dashboard for Strategic Trading
In this article, we build a multi-timeframe scanner dashboard in MQL5 to display real-time trading signals. We plan an interactive grid interface, implement signal calculations with multiple indicators, and add a close button. The article concludes with backtesting and strategic trading benefits
How to build and optimize a volatility-based trading system (Chaikin Volatility - CHV)
In this article, we will provide another volatility-based indicator named Chaikin Volatility. We will understand how to build a custom indicator after identifying how it can be used and constructed. We will share some simple strategies that can be used and then test them to understand which one can be better.
Creating a ticker tape panel: Improved version
How do you like the idea of reviving the basic version of our ticker tape panel? The first thing we will do is change the panel to be able to add an image, such as an asset logo or some other image, so that the user could quickly and easily identify the displayed symbol.
Exploring Advanced Machine Learning Techniques on the Darvas Box Breakout Strategy
The Darvas Box Breakout Strategy, created by Nicolas Darvas, is a technical trading approach that spots potential buy signals when a stock’s price rises above a set "box" range, suggesting strong upward momentum. In this article, we will apply this strategy concept as an example to explore three advanced machine learning techniques. These include using a machine learning model to generate signals rather than to filter trades, employing continuous signals rather than discrete ones, and using models trained on different timeframes to confirm trades.
MQL5 Market Turns One Year Old
One year has passed since the launch of sales in MQL5 Market. It was a year of hard work, which turned the new service into the largest store of trading robots and technical indicators for MetaTrader 5 platform.
Developing a trading Expert Advisor from scratch (Part 14): Adding Volume At Price (II)
Today we will add some more resources to our EA. This interesting article can provide some new ideas and methods of presenting information. At the same time, it can assist in fixing minor flaws in your projects.
Developing a multi-currency Expert Advisor (Part 1): Collaboration of several trading strategies
There are quite a lot of different trading strategies. So, it might be useful to apply several strategies working in parallel to diversify risks and increase the stability of trading results. But if each strategy is implemented as a separate Expert Advisor (EA), then managing their work on one trading account becomes much more difficult. To solve this problem, it would be reasonable to implement the operation of different trading strategies within a single EA.
DRAKON visual programming language — communication tool for MQL developers and customers
DRAKON is a visual programming language designed to simplify interaction between specialists from different fields (biologists, physicists, engineers...) with programmers in Russian space projects (for example, in the Buran reusable spacecraft project). In this article, I will talk about how DRAKON makes the creation of algorithms accessible and intuitive, even if you have never encountered code, and also how it is easier for customers to explain their thoughts when ordering trading robots, and for programmers to make fewer mistakes in complex functions.
Population optimization algorithms: Fish School Search (FSS)
Fish School Search (FSS) is a new optimization algorithm inspired by the behavior of fish in a school, most of which (up to 80%) swim in an organized community of relatives. It has been proven that fish aggregations play an important role in the efficiency of foraging and protection from predators.
Testing Visualization: Functionality Enhancement
The article describes software that can make strategy testing highly similar to the real trading.
MQL5 Wizard Techniques you should know (Part 09): Pairing K-Means Clustering with Fractal Waves
K-Means clustering takes the approach to grouping data points as a process that’s initially focused on the macro view of a data set that uses random generated cluster centroids before zooming in and adjusting these centroids to accurately represent the data set. We will look at this and exploit a few of its use cases.
Andrey Voitenko (avoitenko): "Developers benefit from the ideas that they code? Nonsense!"
A Ukrainian developer Andrey Voitenko (avoitenko) is an active participant of the "Jobs" service at mql5.com, helping traders from all over the world to implement their ideas. Last year Andrey's Expert Advisor was on the fourth place in the Automated Trading Championship 2010, being slightly behind the bronze winner. This time we are discussing the Jobs service with Andrey.
From Novice to Expert: Support and Resistance Strength Indicator (SRSI)
In this article, we will share insights on how to leverage MQL5 programming to pinpoint market levels—differentiating between weaker and strongest price levels. We will fully develop a working, Support and Resistance Strength Indicator (SRSI).
Expert System 'Commentator'. Practical Use of Embedded Indicators in an MQL4 Program
The article describes the use of technical indicators in programming on MQL4.
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.
Implementing the Janus factor in MQL5
Gary Anderson developed a method of market analysis based on a theory he dubbed the Janus Factor. The theory describes a set of indicators that can be used to reveal trends and assess market risk. In this article we will implement these tools in mql5.
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.
Cycles and Forex
Cycles are of great importance in our lives. Day and night, seasons, days of the week and many other cycles of different nature are present in the life of any person. In this article, we will consider cycles in financial markets.
Timeseries in DoEasy library (part 52): Cross-platform nature of multi-period multi-symbol single-buffer standard indicators
In the article, consider creation of multi-symbol multi-period standard indicator Accumulation/Distribution. Slightly improve library classes with respect to indicators so that, the programs developed for outdated platform MetaTrader 4 based on this library could work normally when switching over to MetaTrader 5.
Who Is Who in MQL5.community?
The MQL5.com website remembers all of you quite well! How many of your threads are epic, how popular your articles are and how often your programs in the Code Base are downloaded – this is only a small part of what is remembered at MQL5.com. Your achievements are available in your profile, but what about the overall picture? In this article we will show the general picture of all MQL5.community members achievements.
Graphics in DoEasy library (Part 85): Graphical object collection - adding newly created objects
In this article, I will complete the development of the descendant classes of the abstract graphical object class and start implementing the ability to store these objects in the collection class. In particular, I will create the functionality for adding newly created standard graphical objects to the collection class.
Neural networks made easy (Part 55): Contrastive intrinsic control (CIC)
Contrastive training is an unsupervised method of training representation. Its goal is to train a model to highlight similarities and differences in data sets. In this article, we will talk about using contrastive training approaches to explore different Actor skills.
Automating Trading Strategies in MQL5 (Part 2): The Kumo Breakout System with Ichimoku and Awesome Oscillator
In this article, we create an Expert Advisor (EA) that automates the Kumo Breakout strategy using the Ichimoku Kinko Hyo indicator and the Awesome Oscillator. We walk through the process of initializing indicator handles, detecting breakout conditions, and coding automated trade entries and exits. Additionally, we implement trailing stops and position management logic to enhance the EA's performance and adaptability to market conditions.
Econometric tools for forecasting volatility: GARCH model
The article describes the properties of the non-linear model of conditional heteroscedasticity (GARCH). The iGARCH indicator has been built on its basis for predicting volatility one step ahead. The ALGLIB numerical analysis library is used to estimate the model parameters.
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.
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
Visual Testing of the Profitability of Indicators and Alerts
What indicator of trading alerts or just the methods of their calculating to use is usually decided when testing EAs using these alerts. However, it is not always possible/necessary/reasonable to write an EA for each indicator. You can promptly calculate the profitability of trading on the alerts from other indicators, using a special indicator that collects their alerts itself and draws a picture of ideal trading with them. It can help you both make a visual estimate of the results obtained and quickly choose most optimal parameters.
DoEasy. Controls (Part 18): Functionality for scrolling tabs in TabControl
In this article, I will place header scrolling control buttons in TabControl WinForms object in case the header bar does not fit the size of the control. Besides, I will implement the shift of the header bar when clicking on the cropped tab header.
Interview with Mariusz Zarnowski (ATC 2012)
As December 28 is approaching, the list of leaders of the Automated Trading Championship 2012 is becoming clearer. With only two weeks to go until the end of the Championship, Mariusz Zarnowski (zrn) from Poland stands a good chance to be in the top three. His EA has already demonstrated how it can triple the initial deposit in just a couple of weeks.
Installing MetaTrader 5 and Other MetaQuotes Apps on HarmonyOS NEXT
Easily install MetaTrader 5 and other MetaQuotes apps on HarmonyOS NEXT devices using DroiTong. A detailed step-by-step guide for your phone or laptop.
Fallacies, Part 2. Statistics Is a Pseudo-Science, or a Chronicle of Nosediving Bread And Butter
Numerous attempts to apply statistical methods to the objective reality, i.e. to financial series, crash when met with the nonstationarity of processes, "fat tails" of accompanying probability distributions, and insufficient volume of financial data.In this publication I will try to refer not to the financial series as such, but to their subjective presentation - in this case, to the way a trader tries to halter the series, i.e. to the trading system. The eduction of statistical regularities of the trading results process is a rather enthralling task. In some cases quite true conclusions about the model of this process can be made, and these can be applied to the trading system.
DoEasy. Controls (Part 9): Re-arranging WinForms object methods, RadioButton and Button controls
In this article, I will fix the names of WinForms object class methods and create Button and RadioButton WinForms objects.
Expert Advisors Based on Popular Trading Systems and Alchemy of Trading Robot Optimization (Part V)
In this article the author offers ways to improve trading systems described in his previous articles. The article will be interesting for traders that already have some experience of writing Expert Advisors.
Building Your First Glass-box Model Using Python And MQL5
Machine learning models are difficult to interpret and understanding why our models deviate from our expectations is critical if we want to gain any value from using such advanced techniques. Without comprehensive insight into the inner workings of our model, we might fail to spot bugs that are corrupting our model's performance, we may waste time over engineering features that aren't predictive and in the long run we risk underutilizing the power of these models. Fortunately, there is a sophisticated and well maintained all in one solution that allows us to see exactly what our model is doing underneath the hood.