History of MQL5.community development

In this article, we'll complete our series about how to design a trading system based on the most popular technical indicator. We'll learn how to create a trading system based on the Alligator indicator.

In this article, I will fix and optimize handling the appearance of WinForms objects after moving the mouse cursor away from the object, as well as start the development of the TabControl WinForms object.

We continue to study unsupervised learning algorithms. This time I suggest that we discuss the features of autoencoders when applied to recurrent model training.

In this article, I will make additional changes to the CCI affecting the very logic of this indicator. Moreover, we will be able to see it in the main chart window.

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.

In this article, I am going to create the base object of WinForms object lists, as well as the two new objects: ListBox and ButtonListBox.

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.

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.

We will make the order system more flexible. Here we will consider changes to the code that will make it more flexible, which will allow us to change position stop levels much faster.

The article considers grouping WinForms objects and creation of the CheckBox objects list object.