Dominating estimators for the global minimum variance portfolio

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In this paper, we derive two shrinkage estimators for the global minimum variance portfolio 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 observations d + 2 and number of assets d 4. The small-sample properties of the shrinkage estimators as well as their large-sample properties for fixed d but n -> ∞ 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. -- Covariance matrix estimation ; global minimum variance portfolio ; James-Stein estimation : naive diversification : shrinkage estimator