Classifying the characteristics of insurance shares: a k-means clustering approach

Authors

  • Y Utami Universitas Muhammadiyah Malang
  • I Zuhroh Universitas Muhammadiyah Malang
  • V Prasetya Universitas Muhammadiyah Malang
  • Mochamad Rofik Universitas Muhammadiyah Malang

Keywords:

k-means, insurance share price, rate of return

Abstract

This study aims to apply the k-means clustering method in understanding the characteristics of insurance shares. The eight issuers are divided into three clusters based on price and rate of return. The k-means method's application shows that each cluster has different characteristics, especially for the price variable. Test with panel data regression also discovers different patterns between clusters 2 and 3 in responding to changes in interest rates. The findings of this study indicate that k-means clustering can be used as an initial analysis to understand the characteristics of issuers that investors can use to increase the optimal probability of return.

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Published

2021-09-30

Issue

Vol. 15 No. 3 (2021): September 2021

Section

Articles

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