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

Y Utami, I Zuhroh, V Prasetya, Mochamad Rofik

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.

Keywords


k-means; insurance share price; rate of return

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DOI: http://dx.doi.org/10.26555/jifo.v15i3.a23372

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