<![CDATA[Stock prices are very important financial assets and accurate forecasting of stock price movements is of great value in making investment decisions. This research methodology begins with the analysis of historical data of BBCA stock prices. The ARIMA (Autoregressive Integrated Moving Average) model is used to capture trends and patterns of stock price fluctuations that occur over time. This model is then improved with the application of the GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model to measure changes in volatility and heteroskedasticity in stock prices. The data used in this study includes the daily share price of BBCA in the period 1 October 2021 - 30 October 2023, obtained from reliable data sources. This research aims to develop an effective forecasting model for the stock price of PT Bank Central Asia Tbk (BBCA) using a combination of ARIMA and GARCH models. The results of the study show that the closing price of shares of PT Bank Central Asia Tbk (BBCA) contains elements of heteroskedasticity. The best model obtained is ARIMA (0,1,1)-GARCH (6,0). The MAPE value obtained is 0.9610548.]]>
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