History of MQL5.community development

Today we will continue to develop the order system. As you will see, we will be massively reusing what has already been shown in other articles. Nevertheless, you will receive a small reward in this article. First, we will develop a system that can be used with a real trading server, both from a demo account or from a real one. We will make extensive use of the MetaTrader 5 platform, which will provide us with all the necessary support from the beginning.

In this article, I will consider the option of obtaining information about closed positions based on their trading history. Besides, I will create a simple indicator that displays the approximate profit/loss of positions on each bar as a diagram.

In this article, we will review the structure of the indicator buffer in multi-symbol, multi-period indicators and organize the display of colored buffers of these indicators on the chart.

Principal Component Analysis, a dimensionality reducing technique in data analysis, is looked at in this article, with how it could be implemented with Eigen values and vectors. As always, we aim to develop a prototype expert-signal-class usable in the MQL5 wizard.

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.

The article examines the impact of changing the shape of probability distributions on the performance of optimization algorithms. We will conduct experiments using the Smart Cephalopod (SC) test algorithm to evaluate the efficiency of various probability distributions in the context of optimization problems.

The first part was devoted to the well-known and popular algorithm - simulated annealing. We have thoroughly considered its pros and cons. The second part of the article is devoted to the radical transformation of the algorithm, which turns it into a new optimization algorithm - Simulated Isotropic Annealing (SIA).

The Simulated Annealing algorithm is a metaheuristic inspired by the metal annealing process. In the article, we will conduct a thorough analysis of the algorithm and debunk a number of common beliefs and myths surrounding this widely known optimization method. The second part of the article will consider the custom Simulated Isotropic Annealing (SIA) algorithm.

We will analyze the question of what quantitative analysis is and how it is used by major players. We will create one of the quantitative analysis algorithms in the MQL5 language.