Portfolio Optimization Based on Clustering in Indonesia Stock Exchange: A Case Study of The Index LQ45

Abstract

In general portfolio, optimization is a technique for selecting the proportion of assets to make a better portfolio by maximizing the expected return while also minimizing the risk. In this research, the k-means clustering method is used to classify stocks are listed on the LQ45 Index and select stocks whose has prices tend to be increased. Then the Markowitz approach is used to analyze the performance of optimization portfolio models that have a minimum variance in expected return and risk. After understanding the performance of this portfolio optimization, future works will be able to apply this model in cloud computing or artificial intelligence. In addition, investors will develop a better view of the latest performance of the stocks are listed in the LQ45 index and support them decide which stocks should be included in their portfolios, thus prevent wrong decisions.