Forecasting the Share Price of Islamic Banks in Indonesia Using the Arima and Garch Methods - Amelia Laelani Nur; Siti Parida; Zia Aliya Luthfiani; Danu Wangsa (Cahaya Abadi Publisher, 2026)
This study aims to analyze and forecast the stock price movements of PT Bank Syariah Indonesia Tbk (BRIS) using a time series approach. The Autoregressive Integrated Moving Average (ARIMA) model is employed to capture the mean pattern of stock prices, while the Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models are applied to analyze volatility dynamics characterized by heteroskedasticity. Daily stock price data of BRIS are tested for stationarity using the Augmented Dickey-Fuller (ADF) test and become stationary after differencing. The results indicate significant volatility, suggesting that the GARCH model is more appropriate for further analysis. Based on the evaluation using Akaike Information Criterion (AIC), Schwarz Criterion (SC), and Hannan-Quinn (HQ), the ARIMA dan GARCH model is selected as the best model, achieving an average accuracy of 80%. These findings demonstrate that the combination of ARIMA and GARCH provides a more comprehensive understanding of the movement and volatility patterns of Islamic stock prices, serving as a useful reference for investors and policymakers in formulating investment strategies.