A Multivariate Regression with Time Series Error in Forecasting Jakarta Composite Index and Stock Prices of Banking Industry in Indonesia by Considering COVID-19 Effect

The stability of the financial system in Indonesia and the world has been severely disrupted by COVID-19. With the unstable financial system conditions, there were drastic fluctuations in the composite stock price index and other stocks. This study focuses on stocks of the banking industry in Indonesia, especially banks that are State-Owned Enterprises. The main objectives of this study are to evaluate the significant effect of COVID-19 on the price of the Jakarta Composite Index (JCI) and some stocks in the banking industry, determine the dependence between the prices of these shares, and forecast the price of JCI and other stock prices in the banking industry. The method used in this study is Multivariate Regression with Time Series Errors, a multivariate technique for analyzing time series data. One of the interesting independent variables included in the model is a variable representing three phases of the COVID-19 pandemic, based on newly confirmed cases. The results indicate a significant impact of the pandemic on the Jakarta Composite Index (JCI) and stock prices of state-owned banks. Furthermore, the study reveals a dependency between the JCI and the stock prices of these banks.