Multi-Objective Stochastic Goal Mixed Integer Programming in Gauging the Optimum Portfolio Selection in the Amman Stock Exchange towards Financial Sustainability

Abstract

The paper attempted to gauge the optimum portfolio selection in the Amman Stock Exchange by using multi-objective stochastic goal mixed-integer programming. This paper presents a solution approach for a complex portfolio selection problem that captures the uncertainty in financial markets. Data were collected from every stock that got listed and continuously traded in the ASE from January 2010 to December 2014. The findings confirmed that the pure stock portfolio, the combination of stock and bond portfolio and a large number of managing constraints allow the portfolio to hold a strategy that beat the benchmark portfolio in certain stages. The result revealed the SGMIP dynamic general portfolio for a single scenario compared to the benchmark portfolio and show that the portfolio achieved a 24% of the return. The SGMIP portfolio achieved 29.2% total return which is greater than the total return of the index portfolio. The portfolio results in a loss of 9.8% in total return from investing in security and achieves a profit of 5.1% from bonds. The SGMIP algorithm has a strong effect on solution speed. The SGMIP model managed to reduce the risk of both portfolios and outperform the performance of the benchmark in two-stage pure portfolio and in the first stage of stock and bond portfolio. This study offers new insights by investigating the dynamic role of multi-objective stochastic goal mixed integer programming to gauge optimum portfolio selection in the Amman stock exchange. This study is limited because its only applicable and useful to countries with similar policies and regulations. Further studies can explore a comparative study between developed and developing economies' stock exchange.