Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization

Authors

  • Kashif Bin Zaheer Department of Mathematical Sciences, UTM, Malaysia, Johor Bahru, Malaysia. Department of Mathematical Sciences, Faculty of Science, FUUAST, Karachi, Pakistan.
  • Mohd Ismail Bin Abd Aziz Department of Mathematical Sciences, UTM, Malaysia, Johor Bahru, Malaysia.
  • Amber Nehan Kashif Department of Mathematical Sciences, UTM, Malaysia, Johor Bahru, Malaysia. Department of Mathematical Sciences, Faculty of Science, FUUAST, Karachi, Pakistan.
  • Syed Muhammad Murshid Raza Department of Mathematical Sciences, Faculty of Science, FUUAST, Karachi, Pakistan.

DOI:

https://doi.org/10.11113/matematika.v34.n1.1001

Abstract

The selection criteria play an important role in the portfolio optimization using any ratio model. In this paper, the authors have considered the mean return as profit and variance of return as risk on the asset return as selection criteria, as the first stage to optimize the selected portfolio. Furthermore, the sharp ratio (SR) has been considered to be the optimization ratio model. In this regard, the historical data taken from Shanghai Stock Exchange (SSE) has been considered. A metaheuristic technique has been developed, with financial tool box available in MATLAB and the particle swarm optimization (PSO) algorithm. Hence, called as the hybrid particle swarm optimization (HPSO) or can also be called as financial tool box particle swarm optimization (FTB-PSO). In this model, the budgets as constraint, where as two different models i.e. with and without short sale, have been considered. The obtained results have been compared with the existing literature and the proposed technique is found to be optimum and better in terms of profit.

Downloads

Published

2018-05-28

Issue

Section

Articles