Before revision: Investors often prefer the global minimum-variance portfolio over the Markowitz portfolio as this allows the estimation risk to be confined to the covariance matrix of returns. For high-dimensional data, however, it is well-known that the sample covariance matrix is ill-conditioned and leads to suboptimal portfolios  .
After revision: Investors often prefer the global minimum-variance portfolio over the Markowitz portfolio as this allows the estimation risk to be confined to the covariance matrix of asset returns, estimating the optimal solution remains a challenge. In the presence of high-dimensionality in the data, the sample covariance matrix is ill-conditioned and leads to suboptimal portfolios .