International Journal of Quantitative Research and Modeling
Vol. 5 No. 2 (2024)

Forecasting Indonesian Stock Index Using ARMA-GARCH Model

Susanti, Dwi (Unknown)
Labitta, Kirana Fara (Unknown)
Sukono, Sukono (Unknown)



Article Info

Publish Date
10 Jun 2024

Abstract

The stock market is an institution that provides a facility for buying and selling stocks. Covid-19 is an issue that has affected the stock markets of many countries, including Indonesia. Due to the pandemic, the condition of stocks before and during Covid-19 is certainly different. Stocks can be measured using stock indices. To predict future stock conditions, it is necessary to forecast the stock index. This research aims to predict the Indonesian stock index in the before and during Covid-19 period, using ARMA-GARCH time series model. According to the results obtained for before Covid-19 data, the best predictive model is the ARMA(0,2)-GARCH(1,0), and for the data during Covid-19, it is ARMA(3,3)-GARCH(3,3). Since the MAE is close to zero, it indicates that the model is quite accurate. These findings can help investors make better investment decisions in the future.

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Journal Info

Abbrev

ijqrm

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Physics

Description

International Journal of Quantitative Research and Modeling (IJQRM) is published 4 times a year and is the flagship journal of the Research Collaboration Community (RCC). It is the aim of IJQRM to present papers which cover the theory, practice, history or methodology of Quatitative Research (QR) ...