Agglomerative clustering in GARCH (1,1) model for stock data in Indonesia
Penulis/Author
Vemmie Nastiti Lestari, S.Si., M.Sc. (1); Prof. Dr. Abdurakhman, S.Si., M.Si. (2); Prof. Dr.rer.nat. Dedi Rosadi, S.Si.,, M.Sc. (3)
Tanggal/Date
18 2024
Kata Kunci/Keyword
Abstrak/Abstract
The development of various industries encourages companies to open investment opportunities for the public, one of which is by offering company shares on the stock exchange at both the national and global levels. This activity increases the number of shares traded. On the other hand, investors are faced with increasingly diverse choices. This diversity needs to be grouped according to the level of time-varying risk to make it easier for investors to choose stocks and form portfolios. This paper will discuss the clustering of twelve Islamic stock data from the Jakarta Islamic Index (JII) using the agglomerative algorithm with the Wald statistics to determine the cluster members and the distance between GARCH models to measure inequality in clustering. The GARCH model used is the GARCH (1,1) model, which is an excellent fit model for describing time series data. Three clusters were formed from the case study to consider in making a good portfolio.
