Discussing the article: "Self Optimizing Expert Advisors in MQL5 (Part 11): A Gentle Introduction to the Fundamentals of Linear Algebra"
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Check out the new article: Self Optimizing Expert Advisors in MQL5 (Part 11): A Gentle Introduction to the Fundamentals of Linear Algebra.
In this discussion, we will set the foundation for using powerful linear, algebra tools that are implemented in the MQL5 matrix and vector API. For us to make proficient use of this API, we need to have a firm understanding of the principles in linear algebra that govern intelligent use of these methods. This article aims to get the reader an intuitive level of understanding of some of the most important rules of linear algebra that we, as algorithmic traders in MQL5 need,to get started, taking advantage of this powerful library.
Today, we will build a statistical model that predicts multiple targets simultaneously. Typically, linear regression models are used to project a single target—for example, the future change in price. However, in this case, we aim to predict four different targets:
We will incorporate these predictions into our trading strategy to define both entry and exit rules, as well as filters for closing positions. The Matrix and Vector MQL5 API offers us powerful tools for building modern machine learning applications. But to realize the potential of the API, you must appreciate the basic linear algebra rules that stand behind the appropriate usage of these dedicated methods.
Linear Algebra can often be an abstract mathematical study. However, I wish to bring the subject to life for you so you can clearly see the benefits of what we are about to cover, and then we will discuss the mathematical towards the middle of the discussion. Finally, after the motivation of our discussion is clear, and all the requisite mathematical notation has been explained, we will demonstrate one example of how to employ linear algebra to build numerically driven trading algorithms capable of forecasting multiple targets simultaneously.
Author: Gamuchirai Zororo Ndawana