Food Sector Stock Investment Portfolio Optimization using Mean-Expected Shortfall Model with Particle Swarm Optimization

https://doi.org/10.47194/orics.v4i3.252

Authors

  • Carlos Naek Tua Tampubolon Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran
  • Betty Subartini Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran
  • Sukono Sukono Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran

Keywords:

Investment, Risk, Optimization, Expected Shortfall, Particle Swarm Optimization, Return

Abstract

One of the most promising investment products is stocks. Stocks have great profit potential, but the risks associated with this investment should not be ignored by investors. Therefore, an optimal investment strategy is needed by forming an investment portfolio, in order to minimize risk and maximize profits that can be obtained. This study aims to optimize the investment portfolio. The method used in this research is based on the Mean-Expected Shortfall (Mean-ES) model. The use of this method is expected that investors can get a more accurate picture of the level of risk associated with their stock portfolio. In addition, Particle Swarm Optimization (PSO) can also be used to optimize the allocation of funds in a stock portfolio.  Applying PSO, investors can find the optimal combination of fund allocation to achieve a high level of return. Based on the results of the analysis conducted on the following five stocks AALI, BISI, DSNG, LSIP and SMAR, the results show a risk level of 0.0014 and a return level of 0.021%.  Thus, investors can form a stock portfolio that has a high potential return, while minimizing the risks associated with stock investment. The implementation of this optimal investment strategy can assist investors in achieving their financial goals in a more effective manner.  Considering the potential returns and risks involved, investors can make wiser investment decisions and optimize the performance of their stock portfolio.

References

Cholissodin, I. (2016). Buku Ajar Swarm Intelligence Deep Intelligent Agriculture View project Deep Intelligent Robotic System View project. https://www.researchgate.net/publication/317706705

Embrechts, P., Resnick, S. I., & Samorodnitsky, G. (1999). Extreme Value Theory as a Risk Management Tool. North American Actuarial Journal, 3(2), 30–41. https://doi.org/10.1080/10920277.1999.10595797

Jogiyanto, H. (2010). Teori portofolio dan analisis investasi. Edisi Ketujuh. BPFE. Yogyakarta, 579–591.

Mardhiyah, A. (2017). Peranan analisis return dan risiko dalam investasi. J-EBIS (Jurnal Ekonomi Dan Bisnis Islam).

Tandelilin, E. (2010). Analisis Investasi dan Manajemen Portofolio. Kanisius.

Published

2023-09-06

How to Cite

Tampubolon, C. N. T., Subartini, B., & Sukono, S. (2023). Food Sector Stock Investment Portfolio Optimization using Mean-Expected Shortfall Model with Particle Swarm Optimization. Operations Research: International Conference Series, 4(3), 99–104. https://doi.org/10.47194/orics.v4i3.252

Issue

Vol. 4 No. 3 (2023): Operations Research International Conference Series (ORICS), September 2023

Section

Articles
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