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

Bakti Siregar; F. Anthon  Pangruruk

doi:10.55927/ijba.v1i1.5

Authors

Bakti Siregar Matana University
F. Anthon Pangruruk Matana University

DOI:

https://doi.org/10.55927/ijba.v1i1.5

Keywords:

Clustering Method, Modern Portfolio Theory, Return Correlation Matrix, and Efficient Frontier

Abstract

In general portfolio optimization is a technique for selecting the proportion of assets to make a better portfolio by maximizing the expectation return while also minimizing the risk. In this research, k-means clustering method is used to classify stocks are listed on the LQ45 Index and select stocks whose has the price tend to be increase. 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 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 LQ45 index and support them decide which stocks that should be include to their portfolios, thus prevent wrong decisions.

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