
Trade Events in MetaTrader 5
A monitoring of the current state of a trade account implies controlling open positions and orders. Before a trade signal becomes a deal, it should be sent from the client terminal as a request to the trade server, where it will be placed in the order queue awaiting to be processed. Accepting of a request by the trade server, deleting it as it expires or conducting a deal on its basis - all those actions are followed by trade events; and the trade server informs the terminal about them.

Data Science and Machine Learning — Neural Network (Part 01): Feed Forward Neural Network demystified
Many people love them but a few understand the whole operations behind Neural Networks. In this article I will try to explain everything that goes behind closed doors of a feed-forward multi-layer perception in plain English.

CatBoost machine learning algorithm from Yandex with no Python or R knowledge required
The article provides the code and the description of the main stages of the machine learning process using a specific example. To obtain the model, you do not need Python or R knowledge. Furthermore, basic MQL5 knowledge is enough — this is exactly my level. Therefore, I hope that the article will serve as a good tutorial for a broad audience, assisting those interested in evaluating machine learning capabilities and in implementing them in their programs.


Universal Expert Advisor: Trading in a Group and Managing a Portfolio of Strategies (Part 4)
In the last part of the series of articles about the CStrategy trading engine, we will consider simultaneous operation of multiple trading algorithms, will learn to load strategies from XML files, and will present a simple panel for selecting Expert Advisors from a single executable module, and managing their trading modes.

Risk and capital management using Expert Advisors
This article is about what you can not see in a backtest report, what you should expect using automated trading software, how to manage your money if you are using expert advisors, and how to cover a significant loss to remain in the trading activity when you are using automated procedures.

Data Science and Machine Learning — Neural Network (Part 02): Feed forward NN Architectures Design
There are minor things to cover on the feed-forward neural network before we are through, the design being one of them. Let's see how we can build and design a flexible neural network to our inputs, the number of hidden layers, and the nodes for each of the network.

Neural networks made easy (Part 11): A take on GPT
Perhaps one of the most advanced models among currently existing language neural networks is GPT-3, the maximal variant of which contains 175 billion parameters. Of course, we are not going to create such a monster on our home PCs. However, we can view which architectural solutions can be used in our work and how we can benefit from them.

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.

Creating a comprehensive Owl trading strategy
My strategy is based on the classic trading fundamentals and the refinement of indicators that are widely used in all types of markets. This is a ready-made tool allowing you to follow the proposed new profitable trading strategy.

Custom Indicators (Part 1): A Step-by-Step Introductory Guide to Developing Simple Custom Indicators in MQL5
Learn how to create custom indicators using MQL5. This introductory article will guide you through the fundamentals of building simple custom indicators and demonstrate a hands-on approach to coding different custom indicators for any MQL5 programmer new to this interesting topic.

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.

Developing a trading Expert Advisor from scratch (Part 7): Adding Volume at Price (I)
This is one of the most powerful indicators currently existing. Anyone who trades trying to have a certain degree of confidence must have this indicator on their chart. Most often the indicator is used by those who prefer “tape reading” while trading. Also, this indicator can be utilized by those who use only Price Action while trading.

Learn how to design a trading system by Awesome Oscillator
In this new article in our series, we will learn about a new technical tool that may be useful in our trading. It is the Awesome Oscillator (AO) indicator. We will learn how to design a trading system by this indicator.


Synthetic Bars - A New Dimension to Displaying Graphical Information on Prices
The main drawback of traditional methods for displaying price information using bars and Japanese candlesticks is that they are bound to the time period. It was perhaps optimal at the time when these methods were created but today when the market movements are sometimes too rapid, prices displayed in a chart in this way do not contribute to a prompt response to the new movement. The proposed price chart display method does not have this drawback and provides a quite familiar layout.


Library for easy and quick development of MetaTrader programs (part XVI): Symbol collection events
In this article, we will create a new base class of all library objects adding the event functionality to all its descendants and develop the class for tracking symbol collection events based on the new base class. We will also change account and account event classes for developing the new base object functionality.


Universal Regression Model for Market Price Prediction
The market price is formed out of a stable balance between demand and supply which, in turn, depend on a variety of economic, political and psychological factors. Differences in nature as well as causes of influence of these factors make it difficult to directly consider all the components. This article sets forth an attempt to predict the market price on the basis of an elaborated regression model.


Using the TesterWithdrawal() Function for Modeling the Withdrawals of Profit
This article describes the usage of the TesterWithDrawal() function for estimating risks in trade systems which imply the withdrawing of a certain part of assets during their operation. In addition, it describes the effect of this function on the algorithm of calculation of the drawdown of equity in the strategy tester. This function is useful when optimizing parameter of your Expert Advisors.


Statistical Carry Trade Strategy
An algorithm of statistical protection of open positive swap positions from unwanted price movements. This article features a variant of the carry trade protection strategy that allows to compensate for potential risk of the price movement in the direction opposite to that of the open position.

Neural networks made easy (Part 12): Dropout
As the next step in studying neural networks, I suggest considering the methods of increasing convergence during neural network training. There are several such methods. In this article we will consider one of them entitled Dropout.


Visualizing trading strategy optimization in MetaTrader 5
The article implements an MQL application with a graphical interface for extended visualization of the optimization process. The graphical interface applies the last version of EasyAndFast library. Many users may ask why they need graphical interfaces in MQL applications. This article demonstrates one of multiple cases where they can be useful for traders.


The Magic of Filtration
Most of the automated trading systems developers use some form of trading signals filtration. In this article, we explore the creation and implementation of bandpass and discrete filters for Expert Advisors, to improve the characteristics of the automated trading system.


Testing patterns that arise when trading currency pair baskets. Part II
We continue testing the patterns and trying the methods described in the articles about trading currency pair baskets. Let's consider in practice, whether it is possible to use the patterns of the combined WPR graph crossing the moving average. If the answer is yes, we should consider the appropriate usage methods.


Extending Strategy Builder Functionality
In the previous two articles, we discussed the application of Merrill patterns to various data types. An application was developed to test the presented ideas. In this article, we will continue working with the Strategy Builder, to improve its efficiency and to implement new features and capabilities.


The Last Crusade
Take a look at your trading terminal. What means of price presentation can you see? Bars, candlesticks, lines. We are chasing time and prices whereas we only profit from prices. Shall we only give attention to prices when analyzing the market? This article proposes an algorithm and a script for point and figure charting ("naughts and crosses") Consideration is given to various price patterns whose practical use is outlined in recommendations provided.

Automating Trading Strategies in MQL5 (Part 9): Building an Expert Advisor for the Asian Breakout Strategy
In this article, we build an Expert Advisor in MQL5 for the Asian Breakout Strategy by calculating the session's high and low and applying trend filtering with a moving average. We implement dynamic object styling, user-defined time inputs, and robust risk management. Finally, we demonstrate backtesting and optimization techniques to refine the program.


Developing a cross-platform grider EA (part III): Correction-based grid with martingale
In this article, we will make an attempt to develop the best possible grid-based EA. As usual, this will be a cross-platform EA capable of working both with MetaTrader 4 and MetaTrader 5. The first EA was good enough, except that it could not make a profit over a long period of time. The second EA could work at intervals of more than several years. Unfortunately, it was unable to yield more than 50% of profit per year with a maximum drawdown of less than 50%.

Learn how to design a trading system by Relative Vigor Index
A new article in our series about how to design a trading system by the most popular technical indicator. In this article, we will learn how to do that by the Relative Vigor Index indicator.


Dr. Tradelove or How I Stopped Worrying and Created a Self-Training Expert Advisor
Just over a year ago joo, in his article "Genetic Algorithms - It's Easy!", gave us a tool for implementation of the genetic algorithm in MQL5. Now utilizing the tool we will create an Expert Advisor that will genetically optimize its own parameters upon certain boundary conditions...


Library for easy and quick development of MetaTrader programs (part XII): Account object class and collection of account objects
In the previous article, we defined position closure events for MQL4 in the library and got rid of the unused order properties. Here we will consider the creation of the Account object, develop the collection of account objects and prepare the functionality for tracking account events.


A Pause between Trades
The article deals with the problem of how to arrange pauses between trade operations when a number of experts work on one МТ 4 Client Terminal. It is intended for users who have basic skills in both working with the terminal and programming in MQL 4.

Automating Trading Strategies in MQL5 (Part 11): Developing a Multi-Level Grid Trading System
In this article, we develop a multi-level grid trading system EA using MQL5, focusing on the architecture and algorithm design behind grid trading strategies. We explore the implementation of multi-layered grid logic and risk management techniques to handle varying market conditions. Finally, we provide detailed explanations and practical tips to guide you through building, testing, and refining the automated trading system.


Building a Social Technology Startup, Part II: Programming an MQL5 REST Client
Let's now shape the PHP-based Twitter idea which was introduced in the first part of this article. We are assembling the different parts of the SDSS. Regarding the client side of the system architecture, we are relying on the new MQL5 WebRequest() function for sending trading signals via HTTP.

Improve Your Trading Charts With Interactive GUI's in MQL5 (Part III): Simple Movable Trading GUI
Join us in Part III of the "Improve Your Trading Charts With Interactive GUIs in MQL5" series as we explore the integration of interactive GUIs into movable trading dashboards in MQL5. This article builds on the foundations set in Parts I and II, guiding readers to transform static trading dashboards into dynamic, movable ones.


The market and the physics of its global patterns
In this article, I will try to test the assumption that any system with even a small understanding of the market can operate on a global scale. I will not invent any theories or patterns, but I will only use known facts, gradually translating these facts into the language of mathematical analysis.

Learn how to design a trading system by VIDYA
Welcome to a new article from our series about learning how to design a trading system by the most popular technical indicators, in this article we will learn about a new technical tool and learn how to design a trading system by Variable Index Dynamic Average (VIDYA).


Library for easy and quick development of MetaTrader programs (part X): Compatibility with MQL4 - Events of opening a position and activating pending orders
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 ninth part, we started improving the library classes for working with MQL4. Here we will continue improving the library to ensure its full compatibility with MQL4.

Data Science and Machine Learning (Part 03): Matrix Regressions
This time our models are being made by matrices, which allows flexibility while it allows us to make powerful models that can handle not only five independent variables but also many variables as long as we stay within the calculations limits of a computer, this article is going to be an interesting read, that's for sure.


The Prototype of a Trading Robot
This article summarizes and systematizes the principles of creating algorithms and elements of trading systems. The article considers designing of expert algorithm. As an example the CExpertAdvisor class is considered, which can be used for quick and easy development of trading systems.

How to create a custom indicator (Heiken Ashi) using MQL5
In this article, we will learn how to create a custom indicator using MQL5 based on our preferences, to be used in MetaTrader 5 to help us read charts or to be used in automated Expert Advisors.

Mastering Market Dynamics: Creating a Support and Resistance Strategy Expert Advisor (EA)
A comprehensive guide to developing an automated trading algorithm based on the Support and Resistance strategy. Detailed information on all aspects of creating an expert advisor in MQL5 and testing it in MetaTrader 5 – from analyzing price range behaviors to risk management.