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Jose Rizal
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FMIPA Universitas Bengkulu JLWR Supratman Kelurahan Kandang Limun Kecamatan Muara Bangkahulu Kota Bengkulu
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Diophantine Journal of Mathematics and Its Applications
Published by Universitas Bengkulu
ISSN : -     EISSN : 2987906X     DOI : https://doi.org/10.33369/diophantine
Core Subject : Economy, Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering
The DJMA is published twice a year in June and December. This journal is managed by the Mathematics Department of Bengkulu University. The scope of this journal includes the fields of: 1. Mathematics 2. Applied Mathematics 3. Statistics 4. Applied Statistics 5. Computer Science.
Arjuna Subject : Matematika - Matematika Terapan
Articles 41 Documents
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Pengoptimalan Portofolio Saham dengan Capital Asset Pricing Model dan Algoritma Simulated Annealing Subagja, Rizky Akhmad; Yulianti, Kartika; Agustina, Fitriani
Diophantine Journal of Mathematics and Its Applications Vol. 4 No. 2 (2025): Vol. 4 No. 2 (2025)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/diophantine.v4i2.45880

Abstract

Stock investment has become increasingly popular in Indonesia, and the construction of an optimal portfolio is essential for effective risk and return management. This study integrates the Capital Asset Pricing Model (CAPM) with the Simulated Annealing algorithm to optimize stock portfolios. The Simulated Annealing algorithm enables flexible and realistic portfolio management by addressing non-linear complexities and market constraints. In addition, this study develops a Graphical User Interface (GUI)-based application using Python to assist investors in calculating and determining optimal portfolio allocations. The application utilizes stock data and investment parameters as inputs and produces optimal allocation outputs based on CAPM and heuristic solutions generated by the Simulated Annealing algorithm. This research offers an efficient and adaptive solution for portfolio optimization in a fluctuating market environment.

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