4 new signals now available for subscription:
| Growth: | 240.88 | % |
| Equity: | 1,868.00 | USD |
| Balance: | 1,868.00 | USD |
| Growth: | 240.88 | % |
| Equity: | 1,868.00 | USD |
| Balance: | 1,868.00 | USD |

In this article, we start considering one of the concepts that many beginners avoid. This is related to the fact that templates are not an easy topic, as many do not understand the basic principle underlying the template: overload of functions and procedures.

This article is a brief introduction to the concept of floating-point numbers. Since this text is very complex please, read it attentively and carefully. Do not expect to quickly master the floating-point system. It only becomes clear over time, as you gain experience using it. But this article will help you understand why your application sometimes produces results different from what you expect.

Perhaps this article will be the most confusing for novice programmers. As a matter of fact, here I will show that it is not always that all functions and procedures have unique names in the same code. Yes, we can easily use functions and procedures with the same name — and this is called overload.

In this article, we will continue our awareness of #define directive, but this time we will focus on its second form of use, that is, creating macros. Since this subject can be a bit complicated, we decided to use an application that we have been studying for some time. I hope you enjoy today's article.

In this article, we demonstrate an easy way to install MetaTrader 5 on popular Linux versions — Ubuntu and Debian. These systems are widely used on server hardware as well as on traders’ personal computers.

How to purchase a trading robot from the MetaTrader Market and to install it?
A product from the MetaTrader Market can be purchased on the MQL5.com website or straight from the MetaTrader 4 and MetaTrader 5 trading platforms. Choose a desired product that suits your trading style, pay for it using your preferred payment method, and activate the product.

Python-MetaTrader 5 Strategy Tester (Part 01): Trade Simulator
The MetaTrader 5 module offered in Python provides a convenient way of opening trades in the MetaTrader 5 app using Python, but it has a huge problem, it doesn't have the strategy tester capability present in the MetaTrader 5 app, In this article series, we will build a framework for back testing your trading strategies in Python environments.

We will explore how the Parabolic SAR and the Fractal indicator can be combined to create a new oscillator-based indicator. By integrating the unique strengths of both tools, traders can aim at developing a more refined and effective trading strategy.

In the previous work, we discussed the theoretical aspects of the PSformer framework, which includes two major innovations in the classical Transformer architecture: the Parameter Shared (PS) mechanism and attention to spatio-temporal segments (SegAtt). In this article, we continue the work we started on implementing the proposed approaches using MQL5.

In this article we will do things that many will find strange and completely out of context, but which, if used correctly, will make your learning much more fun and interesting: we will be able to build quite interesting things based on what is shown here. This will allow you to better understand the syntax of the MQL5 language. The materials provided here are for educational purposes only. It should not be considered in any way as a final application. Its purpose is not to explore the concepts presented.

Harness the full potential of your MetaTrader 5 terminal by leveraging Python’s data-science ecosystem and the official MetaTrader 5 client library. This article demonstrates how to authenticate and stream live tick and minute-bar data directly into Parquet storage, apply sophisticated feature engineering with Ta and Prophet, and train a time-aware Gradient Boosting model. We then deploy a lightweight Flask service to serve trade signals in real time. Whether you’re building a hybrid quant framework or enhancing your EA with machine learning, you’ll walk away with a robust, end-to-end pipeline for data-driven algorithmic trading.

In this article, we'll look at how the code of DispatchMessage, missing from the previous article, works. We will laso introduce the topic of the next article. For this reason, it is important to understand how this code works before moving on to the next topic. The content presented here is intended solely for educational purposes. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.

This article introduces the new PSformer framework, which adapts the architecture of the vanilla Transformer to solving problems related to multivariate time series forecasting. The framework is based on two key innovations: the Parameter Sharing (PS) mechanism and the Segment Attention (SegAtt).