Discussing the article: "Uncertainty as a Model (Part 4): Random Processes — The Dynamics of Uncertainty"

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Check out the new article: Uncertainty as a Model (Part 4): Random Processes — The Dynamics of Uncertainty.

The article introduces the concepts and tools for working with random processes in trading: definitions, characteristics, autocorrelation functions, and a practical classification. The article covers white noise, random walks, Wiener and Poisson processes, as well as Markov chains and martingales. MQL5 scripts demonstrate the generation of sample paths and allow you to simulate equity, highlighting the mathematical limitations of strategies.

We began by studying a single random variable, then moved on to collections consisting of a fixed number of variables. In examining limit theorems—the law of large numbers (LLN) and the central limit theorem (CLT)—we saw that such a collection can contain an arbitrarily large number of elements.

Now it is time for a key step: extending the concept of a collection of random variables to infinitely many variables. This will lead us to the concept of a random process.

Author: Aleksey Nikolayev