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Clustering Stock Prices of Industrial and Consumer Sector Companies in Indonesia Using Fuzzy C-Means and Fuzzy C-Medoids Involving ACF and PACF

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Soft Computing in Data Science (SCDS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1771))

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Abstract

Fundamental and technical analysis that investors generally use to select the best stocks cannot provide information regarding the similarity of stock price characteristics of companies in one sector. Even though companies are in the same sector, each company has a different ability to earn profits and overcome financial difficulties. So, clustering is done to find the stock prices of companies with the same characteristics in one sector. This research uses data on industrial and consumer sector companies’ stock prices because the industrial and consumer sectors are one of the largest sectors in Indonesia. The variables used in this research are open, close, and HML (High Minus Low) stock prices. Several clustering methods that can be used to cluster time series data are Fuzzy C-Means and Fuzzy C-Medoids. In addition, this research also uses several approaches with ACF (Autocorrelation Function) and PACF (Partial Autocorrelation Function), which can handle data with high dimensions and allow the comparison of time series data with different lengths. Based on the highest FS (Fuzzy Silhouette) value, the empirical results show that the two best methods for clustering open, close, and HML stock prices are Fuzzy C-Means and Fuzzy C-Medoids. The clustering results using Fuzzy C-Means are the same for open stock prices and close stock prices data. Meanwhile, there are different clustering results for HML stock price data.

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Acknowledgment

This research is supported by Deputi Bidang Penguatan Riset dan Pengembangan, Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi & Badan Riset dan Inovasi Nasional under the scheme Penelitian Dasar, number of contract 008/E5/PG.02.00.PT/2022 & 1506/PKS/ITS/2022. The authors thank DRPM ITS for the support. The authors also thank the reviewers whose comments and valuable suggestions helped improve the quality of this paper.

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Authors and Affiliations

  1. Department of Statistics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

    Muhammad Adlansyah Muda, Dedy Dwi Prastyo & Muhammad Sjahid Akbar

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  1. Muhammad Adlansyah Muda
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  2. Dedy Dwi Prastyo
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  3. Muhammad Sjahid Akbar
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Correspondence to Dedy Dwi Prastyo .

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Editors and Affiliations

  1. Universiti Teknologi MARA, Shah Alam, Malaysia

    Marina Yusoff

  2. Baoji University of Arts and Sciences, Baoji, China

    Tao Hai

  3. Universiti Teknologi MARA, Shah Alam, Malaysia

    Murizah Kassim

  4. Universiti Teknologi MARA, Shah Alam, Malaysia

    Azlinah Mohamed

  5. Institute of Liberal Arts and Sciences, Nagoya, Japan

    Eisuke Kita

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Muda, M.A., Prastyo, D.D., Akbar, M.S. (2023). Clustering Stock Prices of Industrial and Consumer Sector Companies in Indonesia Using Fuzzy C-Means and Fuzzy C-Medoids Involving ACF and PACF. In: Yusoff, M., Hai, T., Kassim, M., Mohamed, A., Kita, E. (eds) Soft Computing in Data Science. SCDS 2023. Communications in Computer and Information Science, vol 1771. Springer, Singapore. https://doi.org/10.1007/978-981-99-0405-1_20

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  • DOI: https://doi.org/10.1007/978-981-99-0405-1_20

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