When A Ridge Regression Maxi Meets Random Forest
Chief Ridge Officer strikes back
Topic
Premium
A collection of 20 issues
Intuitive Portfolio Shrinkage That Even Your Mum Can Understand
For all of you who are degenerates at constructing portfolios
Lowkey-Advanced Ridge Regression (Part II): Non-Zero Priors, Subset Shrinkage, Cluster Shrinkage
I Studied Regressions *Only* for 30 Days So You Don't Have To But You Have To Subscribe Part II
Lowkey-Advanced Ridge Regression (Part I)
I Studied Regressions *Only* for 30 Days So You Don't Have To But You Have To Subscribe
A Non-Guide on Building Personal Projects For HF Quant Roles (Part I)
yes I finally wrote about it.
Farewell Episode: Risk Parity Without Correlations
Never get into a committed relationship with assets' covariance. They're too unstable.
Cross-Predictability Between Assets (Part I): All Signals Matter
As the King of the quantymacro Land, I have passed an executive order of "No Signal Left Behind" effective immediately.
All my homies hate LASSO
I fell out of love with LASSO. it's not you it's me baby :(
Should you combine positions or signals? (Part II): Having your cake and eating it too
Do we actually have to extract assets' expected returns to harvest the benefits of factor model? Here we will talk about another approach where we can sum up our positions, and still integrate a factor risk model, without having to explicitly extract the expected returns of the underlying assets.
Should you combine positions or signals? (Part I): Having your cake and eating it too
Let’s just assume we have 2 signals (Trend and Carry). How do we combine these signals together? Generally there are two broad ways of doing it:
1. Combining positions of the individual signals
2. Regress future returns against the signals to get expected returns of each asset
In this