Rapid profiling of plantation stocks in Bursa Malaysia with Expectation Maximization clustering

Building a stock portfolio often requires extensive financial knowledge and Herculean efforts looking at the amount of financial data to analyze. In this preliminary study, the objective is to build a plantation stock portfolio using a clustering technique. We utilized Expectation Maximization (EM) clustering on 38 plantation stocks listed in Bursa Malaysia using 14 financial ratios derived from fundamental analysis. The stocks with the similar financial performance tend to group together and form clusters. This will allow investors to analyze and profile each cluster rapidly. The profiling shall assist the investors in selecting appropriate stocks for their stock portfolio. In this study, the EM algorithm yielded two clusters. The 1-year stock price movement was then used to assess the performance of these two clusters. The result showed that the cluster with a better profile obtained a higher average capital gain as compared with the other cluster