TY - JOUR AU - Zaheer, Kashif Bin AU - Abd Aziz, Mohd Ismail Bin AU - Kashif, Amber Nehan AU - Raza, Syed Muhammad Murshid PY - 2018/05/28 Y2 - 2024/03/29 TI - Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization JF - MATEMATIKA JA - MATEMATIKA VL - 34 IS - 1 SE - Articles DO - 10.11113/matematika.v34.n1.1001 UR - https://matematika.utm.my/index.php/matematika/article/view/1001 SP - 125-141 AB - <pre>The selection criteria play an important role in the portfolio optimization using any </pre><pre>ratio model. In this paper, the authors have considered the mean return as profit and </pre><pre>variance of return as risk on the asset return as selection criteria, as the first stage to </pre><pre>optimize the selected portfolio. Furthermore, the sharp ratio (SR) has been considered </pre><pre>to be the optimization ratio model. In this regard, the historical data taken from </pre><pre>Shanghai Stock Exchange (SSE) has been considered. A <span>metaheuristic</span> technique has </pre><pre>been developed, with financial tool box available in MATLAB and the particle swarm </pre><pre>optimization (<span>PSO</span>) algorithm. Hence, called as the hybrid particle swarm optimization </pre><pre>(<span>HPSO</span>) or can also be called as financial tool box particle swarm optimization </pre><pre>(<span>FTB</span>-<span>PSO</span>). In this model, the budgets as constraint, where as two different models </pre><pre>i.e. with and without short sale, have been considered. The obtained results have </pre><pre>been compared with the existing literature and the proposed technique is found to be </pre><pre>optimum and better in terms of profit.</pre> ER -