Overview

Minimum-variance allocation requires covariance matrix estimate. Sample covariance is noisy. Shrinkage estimators (Ledoit-Wolf) reduce noise: blend sample cov with identity matrix. Shrunk cov yields more stable, better out-of-sample min-var portfolios.