Portfolio Optimization With Buy-in Thresholds Constraint Using Simulated Annealing Algorithm

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Published Nov 1, 2017

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Indana Lazulfa
Hasyim Asyari University

Abstract

Portfolio optimization is a solution for investors to get the return as much as possible and also to minimize risk as small as possible. In this research, we use risk measures for portfolio optimization, namely mean-variance model. For single objective portfolio optimization problem, especially minimizing risk of portfolio, we used mean-variance as risk measure with constraint such as buy-in thresholds. Buy-in thresholds set a lower limit on all assets that are part of portfolio. All this portfolio optimization problems will be solved by simulated annealing algorithm. The performance of the tested metaheuristics was good enough to solve portfolio optimization.


 

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LAZULFA, Indana. Portfolio Optimization With Buy-in Thresholds Constraint Using Simulated Annealing Algorithm. Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami), [S.l.], v. 1, n. 1, p. 395-402, nov. 2017. Available at: <http://conferences.uin-malang.ac.id/index.php/SIMANIS/article/view/135>. Date accessed: 26 apr. 2024.
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Issue
Vol 1 No 1 (2017): Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai Islami )
Section
Mathematics
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Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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