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All Journal Operations Research: International Conference Series International Journal of Quantitative Research and Modeling
Labitta, Kirana Fara
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Mathematics Physics

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Journal : Operations Research: International Conference Series

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Forecasting Indonesian Stock Index Using ARMA-GARCH Model Susanti, Dwi; Labitta, Kirana Fara; Sukono, Sukono
Operations Research: International Conference Series Vol. 5 No. 3 (2024): Operations Research International Conference Series (ORICS), September 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i3.328

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. Therefore, this research aims to forecast the Indonesian stock index before and during Covid-19 using the ARMA-GARCH time series model. The results show that the best forecasting model for before Covid-19 data is ARMA(0,2)-GARCH(1,0), and for the data during Covid-19, it is ARMA(3,3)-GARCH(3,3). These findings can help investors make better investment decisions in the future.
Co-Authors Dwi Susanti Sukono Sukono