investment plays a vital role on economic growth. one of the main objectives of all countries is to achieve sustainable economic growth and development. nowadays, a considerable amount of activities performed by the managers and investors in general is to make a portfolio of assets effectively meeting demand goals. in this study, mean-variance markowitz model by cardinality constraints and also...

This paper revisits the dynamic MV portfolio selection problem with cone constraints in continuous-time. We first reformulate our constrained model into a special LQ optimal control and develop policy of model. In addition, we provide an alternative method to resolve this constraints. More specifically, instead solving correspondent HJB equation directly, solution for by using properties value ...

Based on the definition of approximate solution (also known as $ \varepsilon $-solution), we propose idea generalized convexity semi-infinite optimization in this research. The nonsmooth sufficient and necessary criteria resilient solutions are then provided. Additionally, it is demonstrated that approximative assumption holds for both strong weak robust dual theorems. efficient cardinality/mea...

Portfolio optimization is an activity for balancing return and risk. In this paper, we used mean-variance (M-V) portfolio models with buy-in threshold cardinality constraints. This model can be formulated as a mixed integer nonlinear programming (MINLP) problem. To solve constrained problem, propose the use of modified spiral algorithm (SOA). Then, Bartholomew-Biggs Kane’s data to validate our ...

In this report, we study the class of Cardinality Constrained Quadratic Programs (CCQP), problems with (not necessarily convex) quadratic objective and cardinality constraints. Many practical problems of importance can be formulated as CCQPs. Examples include sparse principal component analysis [1], [2], cardinality constrained mean-variance portfolio selection problem [3]–[5], subset selection...

In analogy to the PCA setting, the sparse PCA problem is often solved by iteratively alternating between two subtasks: cardinality-constrained rank-one variance maximization and matrix deflation. While the former has received a great deal of attention in the literature, the latter is seldom analyzed and is typically borrowed without justification from the PCA context. In this work, we demonstra...

We propose an improvement of the Approximated Projected Perspective Reformulation (APR) for dealing with constraints linking the binary variables. The new approach solves the Perspective Reformulation (PR) once, and then use the corresponding dual information to reformulate the problem prior to applying APR, thereby combining the root bound quality of the PR with the reduced relaxation computin...