History of MQL5.community development

In the previous article, we got acquainted with the Decision Transformer. But the complex stochastic environment of the foreign exchange market did not allow us to fully implement the potential of the presented method. In this article, I will introduce an algorithm that is aimed at improving the performance of algorithms in stochastic environments.

Although this is the third article on this topic, I must explain for those who have not yet understood the difference between the stock market and the foreign exchange market: the big difference is that in the Forex there is no, or rather, we are not given information about some points that actually occurred during the course of trading.

Unlock the secrets of MQL5 programming in our latest article! Delve into the essentials of structures, classes, and time functions, empowering your coding journey. Whether you're a beginner or an experienced developer, our guide simplifies complex concepts, providing valuable insights for mastering MQL5. Elevate your programming skills and stay ahead in the world of algorithmic trading!

The article discusses Stochastic Diffusion Search (SDS), which is a very powerful and efficient optimization algorithm based on the principles of random walk. The algorithm allows finding optimal solutions in complex multidimensional spaces, while featuring a high speed of convergence and the ability to avoid local extrema.

We will continue to build a system for working in the FOREX market. In order to solve this problem, we must first declare the loading of ticks before loading the previous bars. This solves the problem, but at the same time forces the user to follow some structure in the configuration file, which, personally, does not make much sense to me. The reason is that by designing a program that is responsible for analyzing and executing what is in the configuration file, we can allow the user to declare the elements he needs in any order.

We continue to explore reinforcement learning methods. In this article, I will focus on a slightly different algorithm that considers the Agent’s policy in the paradigm of constructing a sequence of actions.