History of MQL5.community development

This discussion covers the updated TradeManagementPanel in our New_Admin_Panel EA. The update enhances the panel by using built-in classes to offer a user-friendly trade management interface. It includes trading buttons for opening positions and controls for managing existing trades and pending orders. A key feature is the integrated risk management that allows setting stop loss and take profit values directly in the interface. This update improves code organization for large programs and simplifies access to order management tools, which are often complex in the terminal.

We continue studying the Hierarchical Vector Transformer method. In this article, we will complete the construction of the model. We will also train and test it on real historical data.

We continue our last article on DDPG with MA and stochastic indicators by examining other key Reinforcement Learning classes crucial for implementing DDPG. Though we are mostly coding in python, the final product, of a trained network will be exported to as an ONNX to MQL5 where we integrate it as a resource in a wizard assembled Expert Advisor.

In this article, we will look at how to use the RETURN, BREAK, and CONTINUE statements in a loop. Understanding what each of these statements does in the loop execution flow is very important for working with more complex applications. 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.

Discover practical techniques to optimize memory usage in MQL5 trading systems. Learn to build efficient, stable, and fast-performing Expert Advisors and indicators. We’ll explore how memory really works in MQL5, the common traps that slow your systems down or cause them to fail, and — most importantly — how to fix them.