Dominating estimators for minimum-variance portfolios

摘要

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 —infinity and n, d -> oo but n/d -> q < infinity 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.