Sample Eigenvalues Adjustment for Portfolio Performance Improvement under Factor Models
32 Pages Posted: 28 Apr 2017 Last revised: 31 Oct 2018
Date Written: October 2018
We identify a few sample eigenvalues adjustment patterns that lead to an improvement in the out-of-sample portfolio Sharpe ratio when the population covariance matrix admits a high-dimensional factor model. These patterns unveil the key to portfolio performance improvement and shed light on the effectiveness of a few well-known covariance matrix estimation methods which were not designed to improve the out-of-sample portfolio performance.
Keywords: Global Minimum Variance Portfolio, Tail Eigenvalues Amplification, Risk Reduction, High-Dimensionality
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