Congratulations, you may be the single most stubbornly ignorant poster on this site! From your inception as botpro, through TheCoder and EarthEmperator, and now Quanto, you have shown yourself impervious to good advice and incapable of learning anything.
AQR has, over time, been extremely generous in its publications. Options, Factors, Trading... covering a broad range of market related subjects. Papers by Bryan Kelly (mentioned in the article) are particularly insightful. I've cited his work previously here on ET and here is another extremely useful quote from a recent working paper:
"Contrary to conventional wisdom, low in-sample variance principal
components (PCs) are key to out-of-sample model performance."
In fact, most of the non-predictive noise in your model design matrix reside in the larger (higher variance) components. And those noise factors are much more temporally stable than factors with high predictivity. Constant noise-beta models have smaller forecast errors than dynamic noise-beta models across nearly all model structures, which is in contrast to predictive-beta models, where dynamic beta models dominate.
By filtering out even some of the noise in the larger components, you can improve your forecast models significantly. And all from reading just a few AQR sponsored papers!