Time Series Clustering for Stock Exchange in Asean Based on Non-Hierarchical Methods
DOI:
https://doi.org/10.56294/dm2024.639Keywords:
Time Series Clustering, Stock Exchange, Non-Hierarchical Clustering, K-Means, K-MedoidsAbstract
Introduction: This study explores the impact of global economic volatility, particularly influenced by the Russia-Ukraine and Israel-Palestine conflicts, on the ASEAN stock markets. The research aims to analyze stock price patterns and trends to support sustainable economic planning and improve market stability.
Methods: The study employed non-hierarchical clustering techniques, including K-Means and K-Medoids, to analyze time series data from 18 ASEAN stocks over a 10-year period. Data preprocessing involved Min-Max normalization, and Principal Component Analysis (PCA) was utilized for dimensionality reduction. The clustering performance was evaluated using silhouette coefficients, and the Elbow Method determined the optimal number of clusters.
Results: K-Means demonstrated superior clustering performance with a silhouette coefficient of 0.63362 compared to K-Medoids (0.37133). The K-Means method identified seven distinct clusters, effectively grouping stocks with similar temporal patterns. The results revealed significant trends in price stability and volatility across different sectors.
Conclusions: The findings highlight the value of clustering techniques in understanding market dynamics and provide actionable insights for policymakers and investors. The study recommends the development of real-time market monitoring systems to mitigate price fluctuations and support sustainable economic growth in ASEAN. Future research could explore integrating machine learning models for enhanced market analysis
References
[1] M. Yu, M. Umair, Y. Oskenbayev, dan Z. Karabayeva, "Exploring the nexus between monetary uncertainty and volatility in global crude oil: A contemporary approach of regime-switching," Resources Policy, vol. 85, 2023. doi: 10.1016/j.resourpol.2023.10388.
[2] H. Tan dan Z. Wang, "The impact of confucian culture on the cost of equity capital: The moderating role of marketization process," International Review of Economics & Finance, vol. 86, pp. 112–126, 2023. doi: 10.1016/j.iref.2023.03.010.
[3] C. Deng dan J. Wu, "Macroeconomic downside risk and the effect of monetary policy," Finance Research Letters, vol. 54, 2023. doi: 10.1016/j.frl.2023.103803.
[4] D. Bathia, R. Demirer, R. Ferrer, dan I. D. Raheem, "Cross-border capital flows andinformation spillovers across the equity and currency markets in emerging economies," Journal of International Money and Finance, vol. 139, 2023. doi: 10.1016/j.jimonfin.2023.102948.
[5] S. Sunardi, C. Noviolla, S. Supramono, dan Y. B. Hermanto, "Stock market reaction to government policy on determining coal selling price," Heliyon, vol. 9, no. 2, 2023.
[6] Y.-T. Tu, A. I. Aljumah, S. Van Nguyen, C.-F. Cheng, T. D. Tai, dan R. Qiu, "Achieving sustainable development goals through a sharing economy: Empirical evidence from developing economies," Journal of Innovation & Knowledge, vol. 8, no. 1, 2023. doi: 10.1016/j .jik.2022.100299.
[7] P. M. E. Killian, "ASEAN’s External Economic Relations and the Limits of Its Economic Diplomacy," Intermestic: Journal of International Studies, vol. 6, no. 2, pp. 314-334, 2022.
[8] K. Shimizu, "The ASEAN Economic Community and the RCEP in the world economy," Journal of contemporary East Asia studies, vol. 10, no. 1, pp. 1-23, 2021.
studies, 10(1), 1-23.
[9] A. M. Acquah dan M. Ibrahim, "Foreign direct investment, economic growth and financial sector development in Africa," Journal of Sustainable Finance & Investment, vol. 10, no. 4, pp. 315-334, 2020.
[10] W. Dafri dan R. Al-Qaruty, "Challenges and opportunities to enhance digital financial transformation in crisis management," Social Sciences & Humanities Open, vol. 8, no. 1, 2023. doi: 10.1016/j. ssaho.2023.100662.
[11] K. Kim, "Towards sustainable and resilient ASEAN-Korea economic integration 2.0," Asia and the Global Economy, vol. 3, no. 2, 2023. doi: 10.1016/j.aglobe.2023.100061.
[12] M. F. F. Mardianto, I. S. Sediono, S. A. D. Safitri, dan N. Afifah, "Prediction of Indonesia strategic commodity prices during the COVID-19 pandemic based on a simultaneous comparison of Kernel and Fourier series estimator," Journal of Southwest Jiaotong University, vol. 55, no. 6, 2020.
[13] A. Saxena, M. Prasad, A. Gupta, N. Bharill, O. P. Patel, A. Tiwari, E. R. Joo, D. Weiping, dan C. T. Lin, "A review of clustering techniques and developments," Neurocomputing, vol. 267, pp. 664-681, 2017.
[14] E. Pusporani, M. F. F. Mardianto, A. Iffah, A. R. Firdausy, E. Widyatama, dan M. F. Huda, "Prediction of national strategic commodity prices based on multivariate nonparametric time series analysis," Commun. Math. Biol. Neurosci., 2022.
[15] Z.-M. Ren, A. Zeng, dan Y.-C. Zhang, "Structure-oriented prediction in complex networks," Physics Reports, vol. 750, pp. 1–51, 2018. doi: 10.1016/j.physrep.2018.05.002.
[16] K. Deswiaqsa, E. Darmawan, dan S. Sugiyarto, "Application of K-Means for Clustering Based on the Severity of COVID-19 in Indonesian Private Hospitals," EKSAKTA J. Sci. Data Anal., vol. 3, no. 2, pp. 95–102, 2022. doi: 10.20885/eksakta.vol3.iss2.art5.
[17] P. M. A. Putra dan I. G. A. G. A. Kadyanan, "Implementation of K-Means Clustering Algorithm in Determining Classification of the Spread of the COVID-19 Virus in Bali," JELIKU (Jurnal Elektron. Ilmu Komput. Udayana), vol. 10, no. 1, p. 11, 2021. doi: 10.24843/jlk.2021.v10.i01.p03.
[18] A. D. Andini dan T. Arifin, "Implementation of K-Medoids Algorithm for Clustering Patient Disease Data at Bandung City Hospital," J. RESPONSIF Ris. Sains, vol. 2, no. 2, pp. 128–138, 2020.
[19] E. Hernando S. O., L. Travé-Massuyès, A. Subias, M. Pavlov, dan C. Alonso, "DTW K-Means clustering for fault detection in photovoltaic modules," XI Congreso Internacional de Ingeniería Mecánica, Mecatrónica y Automatización, 2023.
[20] H. Hu, J. Liu, X. Zhang, dan M. Fang, "An Effective and Adaptable K-means Algorithm for Big Data Cluster Analysis," Pattern Recognition, vol. 139, p. 109404, 2023.
[21] A. M. Bagirov, R. M. Aliguliyev, dan N. Sultanova, "Finding compact and well-separated clusters: Clustering using silhouette coefficients," Pattern Recognition, vol. 135, 2023.
[22] T. T. Hanifa, S. Al-faraby, F. Informatika, dan U. Telkom, "Churn Prediction Analysis on PT. Telecommunications with Logistic Regression and Underbagging," vol. 4, no. 2, pp. 3210–3225, 2017.
[23] Soemartini, "Principal Component Analysis (PCA) as a Method to Solve Multicollinearity Problem," Journal of Technology and Information, vol. 6, pp. 1-9, 2008.
[24] S. Y. Ghaisani, N. Hikmah, A. H. Prasetyo, dan E. Widodo, "Hierarchical Cluster Analysis for Grouping Provinces in Indonesia Based on Indonesian Democracy Indicators in 2016," pp. 1-11, 2018.
[25] A. K. Jain, Data clustering: 50 years beyond K-Means, Pattern Recognition, 31(8), 651-666, 2010.
[26] G . Wang, C. Xing, J. S. Wang, H. Y. Wang, dan J. X. Liu, "Clustering Validity Evaluation Method Based on Two Typical Clustering Algorithms," IAENG International Journal of Computer Science, vol. 49, no. 3, 2022.
[27] D. Gustian, M. Muslih, D. A. Dewi, V. Siti, R. Rustiana, dan Purnamawati, "K-Means In Clustering The Satisfaction Level of Cikundul Hot Water," Journal of Theoretical and Applied Information Technology, vol. 101, no. 17, pp. 6980-6990, 2023.
[28] M. A. Zen, S. Wahyuningsih, dan A. T. R. Dani, "Application of Time-Sequence Data Clustering with K-Medoids Algorithm," INFERENSI, vol. 6, no. 2, pp. 117-123, 2023.
[29] J. Han, M. Kamber, dan J. Pei, Data Mining: Concept and Techniques, 3rd ed., Waltham, 2012.
[30] C. Holder, D. Guijo-Rubio, and A. Bagnall, “Clustering Time Series with k-Medoids Based Algorithms,” in Advanced Analytics and Learning on Temporal Data, 2023, vol. 14343, pp. 39–55, doi: 10.1007/978-3-031-49896-1_4.
[31] T. M. Kodinariya and P. R. Makwana, "Review on Determining Number of Cluster in K-Means Clustering," International Journal of Advance Research in Computer Science and Management Studies, vol. 1, no. 6, pp. 90-95, 2013. [Online]. Available: https://www.researchgate.ne t/publication/303117595_Review_on_Determining_of_Cluster_in_K-means_Clustering
[32] J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, San Francisco, CA: Morgan Kaufmann Publishers, 2012.
Published
Issue
Section
License
Copyright (c) 2024 M. Fariz Fadillah Mardianto , Adnan Syawal Adilaha Sadikin , Grace Lucyana Koesnadi , Elly Pusporani , Goh Khang Wen (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
