Dominating estimators for minimum-variance portfolios

In this paper, we derive two shrinkage estimators for minimum-variance portfolios that dominate the traditional estimator with respect to the out-of-sample variance of the portfolio return. The presented results hold for any number of assets d ≥ 4 and number of observations n ≥ d + 2 . The small-sample properties of the shrinkage estimators as well as their large-sample properties for fixed d but n → ∞ and n , d → ∞ but n / d → q ≤ ∞ are investigated. Furthermore, we present a small-sample test for the question of whether it is better to completely ignore time series information in favor of naive diversification.