Chris Cosentino is a 3D Generalist, Writer, Animator, Illustrator, and sometimes Actor, with a penchant for talking about himself in the third person.

He’s made a multitude of short form content for a variety of mediums (some of which can be viewed in the Socials tab (press back and click on the phone (hey, brackets within brackets: neat!)))

He currently lives in the UK with his breathtaking partner and in his free time he enjoys TCG’s, watching cartoons, and electrocuting patchwork corpses in his laboratory so that he might one day create new life and elevate mankind into Godhood (only kidding: he has no free time, for he is an animator).

Inexplicably still wanna work with me or just fancy a chat? Here’s my work email:

chris@blackandwhitecomic.com

Cfa Level 2 Quantitative Guide

CFA Level 2 Quant: Moving Beyond Autocorrelation to Autoregression (And Why AI Won’t Replace You Yet)

How to survive the Big Data, Machine Learning, and Time-Series gauntlet. cfa level 2 quantitative

"Before I forecast, I check the residuals." Good luck conquering the L2 Quant jungle. Next stop: Derivatives (where the real fun begins). Need help with a specific ML algorithm or Time-Series model? Drop a comment below. CFA Level 2 Quant: Moving Beyond Autocorrelation to

If you passed CFA Level 1, you probably remember Quantitative Methods as the section where you learned to describe data (standard deviation, skew, kurtosis) and run a simple linear regression. Need help with a specific ML algorithm or Time-Series model

At Level 2, Quantitative Methods is no longer about describing the past; it’s about —and acknowledging how often those predictions fail. Between tricky time-series models and the sudden appearance of "Machine Learning," this topic has become a major hurdle for candidates.

Memorize the assumptions. Know the violations. Don't fear the Random Walk.

Here is the reality check you need to pass CFA Level 2 Quant. Forget cross-sectional data (looking at many companies at one point in time). At Level 2, you live in a time-series world (looking at one company over many points in time).