Machine Learning for Quants (Part 3) Introduction In Parts 1 and 2, we treated trading as a Regression problem; trying to predict the exact numerical return of an asset (e.g., “+1.2%” or “-0.5%”). However, predicting the exact magnitude of price movement is notoriously difficult due to market noise. Often, a Quant doesn’t need to know … Continue reading Predicting Market Direction with Classification and Logistic Regression