Mean-Variance vs Mean-CVaR Optimization with Machine Learning
Overview
Classical Markowitz (mean-variance) assumes returns are normal. Real distributions have fat tails. CVaR (Conditional Value-at-Risk) penalizes tail losses. ML models can predict both mean and tail distribution, enabling mean-CVaR optimization. More robust to crashes than mean-variance.