In summary, investors can construct sparse tangent portfolios by solving the relaxed semi-definite programming problem (P7) with an appropriate choice of the ...

Sep 1, 2015 · We find that the relaxed model becomes a semi-definite programming problem that is efficiently solved with existing optimization solvers.

This study first performs semi-definite relaxation to develop a sparse mean-variance portfolio selection model, and further extend the model by using -norm ...

The high-cardinality of mean-variance portfolios is a concern in practice because it increases transaction costs and management fees.

Kim, Lee, Kim, and Kim (2016) applied the semi-definite relaxation method to the sparse portfolio selection problem, particularly, a Sharpe ratio maximization ...

We find that the relaxed model becomes a semi-definite programming problem that is efficiently solved with existing optimization solvers. Numerical analyses ...

The high-cardinality of mean-variance portfolios is a concern in practice because it increases transaction costs and management fees.

Oct 22, 2024 · This paper aims to discuss a robust multi-objective portfolio selection problem based on the minimax regret criterion under an ellipsoidal ...

Sparse and robust portfolio selection via semi-definite relaxation ... tangent portfolio (with maximum Sharpe ratio) ... portfolio selection models based on the semi ...

This study first performs semi-definite relaxation to develop a sparse mean-variance portfolio selection model, and further extend the model by using -norm ...