Clustering and Portfolio Optimization on LQ45 Stocks with Fuzzy C-Means and Single Index Model

Gunawan, Risky; Owen, Geraldo

doi:10.20956/j.v21i3.42386

Open access Jurnal

Clustering and Portfolio Optimization on LQ45 Stocks with Fuzzy C-Means and Single Index Model

Jurnal Matematika, Statistika dan Komputasi · Vol. 21 No. 3 (2025) · pp. 655–668

DOI: 10.20956/j.v21i3.42386
ISSN: 2614-8811, 1858-1382
Published: 2025-05-14
Publisher: Department of Mathematics, Hasanuddin University
Language: en
License: creativecommons.org/licenses/by/4.0

Abstract

Spreading money or capital across several assets through portfolio formation is more recommended when investing in stocks. The selection of the optimal portfolio can use the Fuzzy C-Means and Single Index Model methods. This research used stock data on the LQ45 Index from January 27, 2020, to November 27, 2024, with the results of 3 portfolios formed. Portfolio 1 has members ADRO, ANTM, and PTBA with an expected return value of 0.001123 and a risk of 0.000670 with a sharpe index performance of 1.393. Portfolio 2 has members BBNI, BMRI, and INCO with an expected return value of 0.000456 and a risk of 0.000524 which has a sharpe index of 0.509. Portfolio 3 with BBCA and INKP has an expected return of 0.000343 and a risk of 0.000453 with a performance of 0.338. For investors who are very risk tolerant, it is recommended to invest in portfolio 1, and for investors who are slightly risk tolerant, portfolio 2 will be suitable, and for investor who are intolerant of risk, portfolio 3 is more suitable. Based on the results obtained in this study, it can be concluded that portfolio building through clustering from Fuzzy C-Means and continued by portfolio weighting based on the Single Index Model produces an optimal portfolio with a fairly high sharpe index performance.

Keywords

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Co-author	Organisation	Joint articles
Cinta Priscillia Maharani	Affiliation unknown	2
Shantika Martha	Affiliation unknown	1
Wirda Andani	Affiliation unknown	1
Evy Sulistianingsih	Affiliation unknown	1
Hendri Agustono	Affiliation unknown	1
Rifki Pebriyandi	Affiliation unknown	1
Gita Fitriyana	Affiliation unknown	1
Dwi Indah Maharani	Affiliation unknown	1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.

Original metadata (oai_dc)

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	<dc:title xml:lang="en">Clustering and Portfolio Optimization on LQ45 Stocks  with Fuzzy C-Means and Single Index Model</dc:title>
	<dc:creator xml:lang="en">Gunawan, Risky</dc:creator>
	<dc:creator xml:lang="en">Owen, Geraldo</dc:creator>
	<dc:subject xml:lang="en">Clustering</dc:subject>
	<dc:subject xml:lang="en">Fuzzy C-Means</dc:subject>
	<dc:subject xml:lang="en">LQ45</dc:subject>
	<dc:subject xml:lang="en">Portfolio</dc:subject>
	<dc:subject xml:lang="en">Single Index Model</dc:subject>
	<dc:description xml:lang="en">Spreading money or capital across several assets through portfolio formation is more recommended when investing in stocks. The selection of the optimal portfolio can use the Fuzzy C-Means and Single Index Model methods. This research used stock data on the LQ45 Index from January 27, 2020, to November 27, 2024, with the results of 3 portfolios formed. Portfolio 1 has members ADRO, ANTM, and PTBA with an expected return value of 0.001123 and a risk of 0.000670 with a sharpe index performance of 1.393. Portfolio 2 has members BBNI, BMRI, and INCO with an expected return value of 0.000456 and a risk of 0.000524 which has a sharpe index of 0.509. Portfolio 3 with BBCA and INKP has an expected return of 0.000343 and a risk of 0.000453 with a performance of 0.338. For investors who are very risk tolerant, it is recommended to invest in portfolio 1, and for investors who are slightly risk tolerant, portfolio 2 will be suitable, and for investor who are intolerant of risk, portfolio 3 is more suitable. Based on the results obtained in this study, it can be concluded that portfolio building through clustering from Fuzzy C-Means and continued by portfolio weighting based on the Single Index Model produces an optimal portfolio with a fairly high sharpe index performance.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2025-05-14</dc:date>
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	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/42386</dc:identifier>
	<dc:identifier>10.20956/j.v21i3.42386</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 21 No. 3 (2025): MAY 2025; 655-668</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/42386/12797</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Jurnal Matematika, Statistika dan Komputasi</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
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