Hands-On Machine Learning for Algorithmic Trading

The Gauss-Markov theorem

To assess the statistical of the model and conduct inference, we need to make assumptions about the residuals, that is, the properties of the unexplained part of the input. The Gauss-Markov theorem (GMT) defines the assumptions required for OLS to produce unbiased estimates of the model parameters , and when these estimates have the lowest standard error among all linear models for cross-sectional data.

The baseline multiple regression model makes the following GMT assumptions:

1. In the population, linearity holds,