MODELING AND FORECASTING STOCK RETURN VOLATILITY OF THE JAKARTA ISLAMIC INDEX: GARCH VS EGARCH MODEL

Abstract

The aim of this study is to determine the most effective method of predicting volatility in select stocks of the Jakarta Islamic Index. To achieve this objective, two models - Symmetric Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and Asymmetric Exponential GARCH - were employed to identify any potential asymmetric effects. Daily data from May 1, 2018, to May 31, 2023, was used for this study, focusing on six stocks included in the Jakarta Islamic Index during the observation period - ADRO, ICBP, KLBF, TLKM, UNTR, and UNVR. The results of the study reveal that the Symmetric GARCH model is a suitable tool for analyzing volatility patterns in these six stocks. Moreover, the forecast results can be of great assistance to investors. Those who are willing to take risks may consider adding TLKM and KLBF to their portfolios, while those who prefer low-risk investments can opt for UNTR.