Abstract
Purpose – This study is based on the price behavior of stocks included in the Borsa Istanbul 30 (BIST 30) index over many years. With the help of the variables used in the research, it is aimed to determine in which cluster the stocks in the Borsa Istanbul 30 index are included with the Canopy Clustering Algorithm. Design/Methodology/Approach – In this study, clustering was performed with the Canopy Algorithm, and then it was examined whether there was a significant difference on the basis of variables with the Wilcoxon and Paired Sample t test. The stocks included in the study consist of stocks included in the BIST 30 index as of 07.12.2020. The data set used in the study covers the period of 2012-2020 and each stock's daily; closing, beta coefficient, volatility, volume, market value/book value (PD/DD) variables. In this context, the data set was included in the analysis in two groups, pre-COVID-19 pandemic and COVID-19 period. Findings – It was seen that the Canopy Algorithm revealed significant results in the clustering analysis and when the clustering results were examined, 19 of the 30 stocks were in the same cluster both before and after the pandemic. The effects of variables on the formation of clusters were examined and it was concluded that the variables were the right choices for cluster analysis. Discussion – Investment instruments have different risk-return relationships. Investors who want to invest in stocks should have information about the behavior of stocks while diversifying their portfolio. In other words, it is not thought that it would be beneficial to include stocks that move together in decreases and increases in the same portfolio in terms of reducing the total risk of the portfolio. At this point, getting to know the stocks will provide various benefits to the investors.
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