An Optimal Stock Market Portfolio Proportion Model Using Genetic Algorithm

https://doi.org/10.22146/ijccs.36154

Wahyono Wahyono(1*), Chasandra Puspitasari(2), Muhammad Dzulfikar Fauzi(3), Kasliono Kasliono(4), Wahyu Sri Mulyani(5), Laksono Kurnianggoro(6)

(1) Department of Computer Sciences and Electronics, FMIPA, Universitas Gadjah Mada
(2) Master Program in Computer Science, FMIPA, Universitas Gadjah Mada
(3) Master Program in Computer Science, FMIPA, Universitas Gadjah Mada
(4) Master Program in Computer Science, FMIPA, Universitas Gadjah Mada
(5) Master Program in Computer Science, FMIPA, Universitas Gadjah Mada
(6) Department of Electrical Engineering, University of Ulsan
(*) Corresponding Author

Abstract


To reduce the amount of loss due to investment risk, an investor or stockbroker usually forms an optimal stock portfolio. This technique is done to get the maximum return of investment on shares to be purchased. However, in forming a stock portfolio required a fairly complex calculations and certain skills. This work aims to provide an alternative solution in the problem of forming the optimal and efficient stock portfolio composition by designing a system that can help decision making of investors or stockbrokers in preparing stock portfolio in accordance with the policy and risk investment. In this work, determination of optimal stock portfolio composition is constructed by using Genetic Algorithm. The data used in this work are the 4 selected stocks listed on the LQ45 index in 2017. Meanwhile, the calculation of profit and loss rate utilizes a single index model theory. The efficiency of the algorithm has been examined against the population size and crossover and mutation probabilities. The experimental results show that the proposed algorithm can be used as one of solutions to select the optimal stock portfolio.

Keywords


genetic algorithm; LQ45 index; stock market portfolio; single index model

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References

[1] L. McGinty, and B. Smyth, “Adaptive selection: analysis of critiquing and preference based feed back in conversation on recommender system.” International J Electron Commerce vol. 11, no. 2, p. 35-57. 2006

[2] R. Wahyuni, W. F. Mahmudi, and B. D. Setiawan, Determination of Stock Portfolio Using Genetic Algorithm,” (in Indonesian) Penentuan Portofolio Saham Optimal Menggunakan Algoritma Genetika, Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, Universitas Brawijaya, Malang, 2017.

[3] W. F. Mahmudi, "The introduction of genetic algorithm,” (in Indonesia) Dasar-dasar Algoritma Evolusi, Program Teknologi Informasi dan Ilmu Komputer, Universitas Brawijaya, Malang, 2015.

[4] C. Fiarni and Bastiyan, “Recommender System of Stock Portfolio Based on Genetic Algorithm,” (in Indonesian) Sistem Rekomendasi Portofolio Investasi Berbasis Algoritma Genetika, Seminar Nasional Sistem Informasi Indonesia., 2013.

[5] A. Shritashava and A. Singh, “An Optimal Stock Portfolio Construction Model Using Genetic Algorithm,” Proceedings of 2013 International Conference on Machine Intelligence and Research Advancement (ICMIRA), 21-22 December 2013.

[6] Y.-H. Chou, S.-Y. Kuo, and Y.-T. Lo, “Portfolio Optimization Based on Funds Standardization and Genetic Algorithm,” IEEE Access, vol. 5, p. 21885-21900, 2017.

[7] P. Paranjape-Voditela and U. Deshpandeb, “A stock market portfolio recommender system based on association rule mining,” Applied Soft Computing, vol. 13, no. 2, February 2013, p. 1055-1063, [Online] Available: https://www.sciencedirect.com/science/article/pii/S1568494612004322 [Accessed: 31-May-2018]

[8] S. Husnan, "The Basic Theory of Stock Portfolio and Analysis”, (in Indonesian) Dasar-Dasar Teori Portofolio dan Analisis Sekuritas, Unit Penerbit dan Percetakan AMP YKPN, Indonesia. 2005.

[9] A. K. Wardana and S. Hartati, “Scheduling System of Pencak Silat Based on Genetic Algorithm,” (in Indonesia) Sistem Penjadwalan Pertandingan Pencak Silat Berbasis Algoritma Genetika, IJCCS (Indonesian J. Comput. Cybern. Syst.), vol. 11, no. 2, p. 177, July. 2017 [Online]. Available: https://jurnal.ugm.ac.id/ijccs/article/view/24214. [Accessed: 24-May-2018]

[10] Z. Indra and Subanar, “Optimasi Biaya Distribusi Rantai Pasok Tiga Tingkat dengan Menggunakan Algoritma Genetika Adaptif dan Terdistribusi,” IJCCS (Indonesian J. Comput. Cybern. Syst.), vol. 8, no. 2, July. 2014 [Online]. Available: https://jurnal.ugm.ac.id/ijccs/article/view/1062. [Accessed: 24-May-2018]

[11] K. Hakiim, A. Darmawan, and Faizah, “Optimasi Kendali PID menggunakan Algoritma Genetika untuk Penerbangan Quadrotor,” IJEIS (Indonesian J. Electron. Instrum. Syst.), vol. 7, no. 2, October. 2017 [Online]. Available: https://jurnal.ugm.ac.id/ijeis/article/view/2321. [Accessed: 29-May-2018]



DOI: https://doi.org/10.22146/ijccs.36154

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