A Portfolio Optimization Approach with a Large Number of Assets: Applications to the US and Korean Stock Markets1. (2nd November 2018) - Lee, Miyoung
Abstract: We propose a new approach for determining optimal portfolio weights in a mean‐variance framework in cases when there are more assets than observations. We empirically show that our approach attains a higher out‐of‐sample Sharpe ratio, M 2 measure, and CEQ return than other methods. Our approach is also free from problems related to the estimation of the covariance matrix because it does not need and solves the so‐called "corner‐solution problem" of the Markowitz model by minimizing the 2‐norm of the portfolio weight vector.