The Appplication of ARMAX-GARCH in Forecasting the Stock Return Volatility of Indonesian Banking Sector: A Case of BBCA and BBRI

Abstract

The volatility of stock returns in Indonesia's banking sector has become a primary concern for investors and regulators, especially amid market uncertainty. Previous studies have been limited in integrating external factors such as trading volume and the impact of the Covid-19 pandemic in volatility forecasting. This study evaluates the effectiveness of the ARMAX-GARCH model in capturing the volatility patterns of stock returns while considering these external factors. Using stock data from BBCA and BBRI for the period 2019–2024, this research examines market efficiency as well as the relationship between returns, volatility, and trading volume. The analysis results show that Indonesia's banking stock market is not fully efficient in the weak form, meaning that historical information can still be used to predict returns. Additionally, the ARMAX-GARCH model demonstrates good accuracy in short-term forecasting, with low RMSE and MAE values. These findings provide insights for investors and regulators in developing more adaptive risk mitigation strategies and investment decision-making.