TL;DR: Sometimes P123 plays close attention to important statistical and machine learning concepts so we don’t have to.
That change has an elegant implication—it places the y-intercept at zero for every factor, which means we can evaluate slope without needing to account for the intercept or consider whether to force it to zero.
And because NAs are filled with 0 after this normalization, they now have exactly zero leverage in any slope-based model or rank-vs-return regression. That eliminates the concern that missing values might distort the regression line.
Nice! Discussion of the importance of removing leverage in another thread: From Stanford to Miami: Teaching Finance with Portfolio123 — My CAPM Test Study - #8 by fwouters