Abstract

The objective of this article is to categorize homogeneous stocks using cluster analysis methodology. It is easier for investors to deal with a small number of clusters of stocks compared to dealing with thousands of stocks. This has aroused their interest in comparing stocks with respect to different variables based on their risk appetite. Notwithstanding, the widespread availability of high processing power computing devices, investors get overwhelmed by the large number of stocks available at their disposal. Categorizing the large number of stocks into few distinct clusters would not only make the task easier for investors by letting him deal with less number of data, but would also give him the option to pick stocks from different clusters based on his preference. This article uses the cluster analysis methodology to group homogeneous stocks from a dataset of 33 listed Indian banks. This method provides a useful tool for interpolation and extrapolation of statistical data and sets up a measure to compare performance and profitability of a company.

Author: Naseem Ahamed

Received on: January, 2020

Accepted on: March, 2021