Before revision:  To address this issue, we review recent covariance matrix estimators and extend the literature by suggesting a multi-fold cross-validation technique . In detail, conducting an extensive empirical analysis with four datasets based on the S\&P 500, we evaluate how the data-driven choice of specific tuning parameters within the proposed cross-validation approach affects the out-of-sample performance of the global minimum-variance portfolio .
After revision:  To address this issue, we review recent covariance matrix estimators and extend the literature by suggesting a multi-fold cross-validation technique for selecting the necessary tuning parameters within each method. Conducting an extensive empirical analysis with four datasets based on the S\&P 500, we evaluate how the data-driven choice of specific tuning parameters within the proposed cross-validation approach affects the out-of-sample performance of the global minimum-variance portfolio .