Articles on trading system automation in MQL5

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Read articles on the trading systems with a wide variety of ideas at the core. Learn how to use statistical methods and patterns on candlestick charts, how to filter signals and where to use semaphore indicators.

The MQL5 Wizard will help you create robots without programming to quickly check your trading ideas. Use the Wizard to learn about genetic algorithms.

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MQL5 Wizard techniques you should know (Part 05): Markov Chains

MQL5 Wizard techniques you should know (Part 05): Markov Chains

Markov chains are a powerful mathematical tool that can be used to model and forecast time series data in various fields, including finance. In financial time series modelling and forecasting, Markov chains are often used to model the evolution of financial assets over time, such as stock prices or exchange rates. One of the main advantages of Markov chain models is their simplicity and ease of use.
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Developing a trading Expert Advisor from scratch (Part 22): New order system (V)

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.
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Advanced resampling and selection of CatBoost models by brute-force method

Advanced resampling and selection of CatBoost models by brute-force method

This article describes one of the possible approaches to data transformation aimed at improving the generalizability of the model, and also discusses sampling and selection of CatBoost models.
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Alan Andrews and his methods of time series analysis

Alan Andrews and his methods of time series analysis

Alan Andrews is one of the most famous "educators" of the modern world in the field of trading. His "pitchfork" is included in almost all modern quote analysis programs. But most traders do not use even a fraction of the opportunities that this tool provides. Besides, Andrews' original training course includes a description not only of the pitchfork (although it remains the main tool), but also of some other useful constructions. The article provides an insight into the marvelous chart analysis methods that Andrews taught in his original course. Beware, there will be a lot of images.
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Deep Learning Forecast and ordering with Python and MetaTrader5 python package and ONNX model file

Deep Learning Forecast and ordering with Python and MetaTrader5 python package and ONNX model file

The project involves using Python for deep learning-based forecasting in financial markets. We will explore the intricacies of testing the model's performance using key metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R2) and we will learn how to wrap everything into an executable. We will also make a ONNX model file with its EA.
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Creating an EA that works automatically (Part 08): OnTradeTransaction

Creating an EA that works automatically (Part 08): OnTradeTransaction

In this article, we will see how to use the event handling system to quickly and efficiently process issues related to the order system. With this system the EA will work faster, so that it will not have to constantly search for the required data.
How we developed the MetaTrader Signals service and Social Trading
How we developed the MetaTrader Signals service and Social Trading

How we developed the MetaTrader Signals service and Social Trading

We continue to enhance the Signals service, improve the mechanisms, add new functions and fix flaws. The MetaTrader Signals Service of 2012 and the current MetaTrader Signals Service are like two completely different services. Currently, we are implementing A Virtual Hosting Cloud service which consists of a network of servers to support specific versions of the MetaTrader client terminal.
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Multiple indicators on one chart (Part 05): Turning MetaTrader 5 into a RAD system (I)

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.
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Understanding MQL5 Object-Oriented Programming (OOP)

Understanding MQL5 Object-Oriented Programming (OOP)

As developers, we need to learn how to create and develop software that can be reusable and flexible without duplicated code especially if we have different objects with different behaviors. This can be smoothly done by using object-oriented programming techniques and principles. In this article, we will present the basics of MQL5 Object-Oriented programming to understand how we can use principles and practices of this critical topic in our software.
MQL5 Market Results for Q2 2013
MQL5 Market Results for Q2 2013

MQL5 Market Results for Q2 2013

Successfully operating for 1.5 years, MQL5 Market has become the largest traders' store of trading strategies and technical indicators. It offers around 800 trading applications provided by 350 developers from around the world. Over 100.000 trading programs have already been purchased and downloaded by traders to their MetaTrader 5 terminals.
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Developing a trading Expert Advisor from scratch (Part 28): Towards the future (III)

Developing a trading Expert Advisor from scratch (Part 28): Towards the future (III)

There is still one task which our order system is not up to, but we will FINALLY figure it out. The MetaTrader 5 provides a system of tickets which allows creating and correcting order values. The idea is to have an Expert Advisor that would make the same ticket system faster and more efficient.
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How to create a custom True Strength Index indicator using MQL5

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.
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Experiments with neural networks (Part 5): Normalizing inputs for passing to a neural network

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.
Timeseries in DoEasy library (part 47): Multi-period multi-symbol standard indicators
Timeseries in DoEasy library (part 47): Multi-period multi-symbol standard indicators

Timeseries in DoEasy library (part 47): Multi-period multi-symbol standard indicators

In this article, I will start developing the methods of working with standard indicators, which will ultimately allow creating multi-symbol multi-period standard indicators based on library classes. Besides, I will add the "Skipped bars" event to the timeseries classes and eliminate excessive load from the main program code by moving the library preparation functions to CEngine class.
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MQL5 Wizard techniques you should know (Part 03): Shannon's Entropy

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.
MQL5 Market Results for Q1 2013
MQL5 Market Results for Q1 2013

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.
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Neural networks made easy (Part 32): Distributed Q-Learning

Neural networks made easy (Part 32): Distributed Q-Learning

We got acquainted with the Q-learning method in one of the earlier articles within this series. This method averages rewards for each action. Two works were presented in 2017, which show greater success when studying the reward distribution function. Let's consider the possibility of using such technology to solve our problems.
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Creating an EA that works automatically (Part 10): Automation (II)

Creating an EA that works automatically (Part 10): Automation (II)

Automation means nothing if you cannot control its schedule. No worker can be efficient working 24 hours a day. However, many believe that an automated system should operate 24 hours a day. But it is always good to have means to set a working time range for the EA. In this article, we will consider how to properly set such a time range.
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Neural networks made easy (Part 15): Data clustering using MQL5

Neural networks made easy (Part 15): Data clustering using MQL5

We continue to consider the clustering method. In this article, we will create a new CKmeans class to implement one of the most common k-means clustering methods. During tests, the model managed to identify about 500 patterns.
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Learn how to deal with date and time in MQL5

Learn how to deal with date and time in MQL5

A new article about a new important topic which is dealing with date and time. As traders or programmers of trading tools, it is very crucial to understand how to deal with these two aspects date and time very well and effectively. So, I will share some important information about how we can deal with date and time to create effective trading tools smoothly and simply without any complicity as much as I can.
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Timeseries in DoEasy library (part 53): Abstract base indicator class

Timeseries in DoEasy library (part 53): Abstract base indicator class

The article considers creation of an abstract indicator which further will be used as the base class to create objects of library’s standard and custom indicators.
MQL5 Market Turns One Year Old
MQL5 Market Turns One Year Old

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.
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Automated grid trading using limit orders on Moscow Exchange (MOEX)

Automated grid trading using limit orders on Moscow Exchange (MOEX)

The article considers the development of an MQL5 Expert Advisor (EA) for MetaTrader 5 aimed at working on MOEX. The EA is to follow a grid strategy while trading on MOEX using MetaTrader 5 terminal. The EA involves closing positions by stop loss and take profit, as well as removing pending orders in case of certain market conditions.
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Neural networks made easy (Part 21): Variational autoencoders (VAE)

Neural networks made easy (Part 21): Variational autoencoders (VAE)

In the last article, we got acquainted with the Autoencoder algorithm. Like any other algorithm, it has its advantages and disadvantages. In its original implementation, the autoenctoder is used to separate the objects from the training sample as much as possible. This time we will talk about how to deal with some of its disadvantages.
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Neural networks made easy (Part 16): Practical use of clustering

Neural networks made easy (Part 16): Practical use of clustering

In the previous article, we have created a class for data clustering. In this article, I want to share variants of the possible application of obtained results in solving practical trading tasks.
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Developing a trading Expert Advisor from scratch (Part 13): Time and Trade (II)

Developing a trading Expert Advisor from scratch (Part 13): Time and Trade (II)

Today we will construct the second part of the Times & Trade system for market analysis. In the previous article "Times & Trade (I)" we discussed an alternative chart organization system, which would allow having an indicator for the quickest possible interpretation of deals executed in the market.
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Developing a Replay System — Market simulation (Part 21): FOREX (II)

Developing a Replay System — Market simulation (Part 21): FOREX (II)

We will continue to build a system for working in the FOREX market. In order to solve this problem, we must first declare the loading of ticks before loading the previous bars. This solves the problem, but at the same time forces the user to follow some structure in the configuration file, which, personally, does not make much sense to me. The reason is that by designing a program that is responsible for analyzing and executing what is in the configuration file, we can allow the user to declare the elements he needs in any order.
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Timeseries in DoEasy library (part 52): Cross-platform nature of multi-period multi-symbol  single-buffer standard indicators

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.
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Data Science and Machine Learning (Part 07): Polynomial Regression

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.
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Backpropagation Neural Networks using MQL5 Matrices

Backpropagation Neural Networks using MQL5 Matrices

The article describes the theory and practice of applying the backpropagation algorithm in MQL5 using matrices. It provides ready-made classes along with script, indicator and Expert Advisor examples.
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Neural networks made easy (Part 67): Using past experience to solve new tasks

Neural networks made easy (Part 67): Using past experience to solve new tasks

In this article, we continue discussing methods for collecting data into a training set. Obviously, the learning process requires constant interaction with the environment. However, situations can be different.
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Forecasting with ARIMA models in MQL5

Forecasting with ARIMA models in MQL5

In this article we continue the development of the CArima class for building ARIMA models by adding intuitive methods that enable forecasting.
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Neural networks made easy (Part 49): Soft Actor-Critic

Neural networks made easy (Part 49): Soft Actor-Critic

We continue our discussion of reinforcement learning algorithms for solving continuous action space problems. In this article, I will present the Soft Actor-Critic (SAC) algorithm. The main advantage of SAC is the ability to find optimal policies that not only maximize the expected reward, but also have maximum entropy (diversity) of actions.
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Developing a trading Expert Advisor from scratch (Part 10): Accessing custom indicators

Developing a trading Expert Advisor from scratch (Part 10): Accessing custom indicators

How to access custom indicators directly in an Expert Advisor? A trading EA can be truly useful only if it can use custom indicators; otherwise, it is just a set of codes and instructions.
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Data Science and Machine Learning (Part 06): Gradient Descent

Data Science and Machine Learning (Part 06): Gradient Descent

The gradient descent plays a significant role in training neural networks and many machine learning algorithms. It is a quick and intelligent algorithm despite its impressive work it is still misunderstood by a lot of data scientists let's see what it is all about.
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Data Science and Machine Learning (Part 13): Improve your financial market analysis with Principal Component Analysis (PCA)

Data Science and Machine Learning (Part 13): Improve your financial market analysis with Principal Component Analysis (PCA)

Revolutionize your financial market analysis with Principal Component Analysis (PCA)! Discover how this powerful technique can unlock hidden patterns in your data, uncover latent market trends, and optimize your investment strategies. In this article, we explore how PCA can provide a new lens for analyzing complex financial data, revealing insights that would be missed by traditional approaches. Find out how applying PCA to financial market data can give you a competitive edge and help you stay ahead of the curve
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Experiments with neural networks (Part 2): Smart neural network optimization

Experiments with neural networks (Part 2): Smart neural network optimization

In this article, I will use experimentation and non-standard approaches to develop a profitable trading system and check whether neural networks can be of any help for traders. MetaTrader 5 as a self-sufficient tool for using neural networks in trading.
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Developing a trading Expert Advisor from scratch (Part 11): Cross order system

Developing a trading Expert Advisor from scratch (Part 11): Cross order system

In this article we will create a system of cross orders. There is one type of assets that makes traders' life very difficult for traders — futures contracts. But why do they make life difficult?
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Revisiting Murray system

Revisiting Murray system

Graphical price analysis systems are deservedly popular among traders. In this article, I am going to describe the complete Murray system, including its famous levels, as well as some other useful techniques for assessing the current price position and making a trading decision.
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Neural networks made easy (Part 31): Evolutionary algorithms

Neural networks made easy (Part 31): Evolutionary algorithms

In the previous article, we started exploring non-gradient optimization methods. We got acquainted with the genetic algorithm. Today, we will continue this topic and will consider another class of evolutionary algorithms.