I would love to present the AI Factor from Portfolio123.com to you and do a video interview with you about what you think about it. My experience so far --> linear is fine if you want to produce low vola systems (Procter & Gamble has linear kind of data). Non-linear MLs (NVDA was a right tail event in terms of earnings acceleration) if you want to build total return systems (especially on small caps). One thing is important with nonlinear ML Algos --> you need tons of data (>20 Years)...
Great write up, very thorough
I would love to present the AI Factor from Portfolio123.com to you and do a video interview with you about what you think about it. My experience so far --> linear is fine if you want to produce low vola systems (Procter & Gamble has linear kind of data). Non-linear MLs (NVDA was a right tail event in terms of earnings acceleration) if you want to build total return systems (especially on small caps). One thing is important with nonlinear ML Algos --> you need tons of data (>20 Years)...
Interesting POV, blends with mine as well