Discussing the article: "Uncertainty as a Model (Part 5): The Basics of Regression"

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Check out the new article: Uncertainty as a Model (Part 5): The Basics of Regression.

A practical introduction to time series regression models: regression on a constant and simple regression with deterministic, exogenous, and endogenous regressors. It describes the key steps in the diagnostic process, including residual analysis and hypothesis testing, that are necessary for making informed trading decisions. MQL5 scripts for MetaTrader 5 are included; they implement tests and plots using real data.

When moving from looking at charts to developing trading algorithms, the question inevitably arises: how can we formalize the relationship between events? Attempts to find the "golden ratio" or draw a trend line "by eye" often lead us to see a pattern where none exists. Econometrics provides us with the language and tools needed to transform intuitive guesses into rigorous mathematical models.

This article is a practical introduction to regression analysis. First, we'll learn how to distinguish market signals from noise, verify the adequacy of models, and interpret residuals. Instead of blindly trusting return rates, we will learn to spot volatility regime shifts and understand when a mathematical model no longer matches reality. Stock and index quotes are used as examples. We will move from a basic statistical audit to modeling intermarket relationships and obtain a testable basis for trading decisions.


Author: Aleksey Nikolayev

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