Analysis of the BISNIS-27 Index Movement Using the Autoregressive Integrated Moving Average (ARIMA) Method During and After the COVID-19 Pandemic
DOI:
https://doi.org/10.59890/ijsas.v4i9.68Keywords:
ARIMA, BISNIS-27 Index, COVID-19 Pandemic, Time Series, Box-JenkinsAbstract
This study analyzes the BISNIS-27 Index during the COVID-19 pandemic (2020–2022) and after the pandemic (2023–2025) using ARIMA, as BISNIS-27 comprises blue-chip stocks with strong fundamentals and high liquidity. Daily closing prices for 2 January 2020–30 December 2025 (1,449 observations) were obtained from Investing.com and analyzed in EViews 12 using the Box-Jenkins procedure: descriptive analysis, ADF stationarity testing, ACF/PACF identification, estimation, and residual diagnostics. The series was non-stationary at level in both periods and stationary after first differencing. The best model was ARIMA ([3,9],1,[15]) during the pandemic and ARIMA ([2],1,[35]) afterward; both satisfied significant coefficients, minimum AIC/SIC, and white-noise residuals. The post-pandemic model fit better, indicating the pandemic altered BISNIS-27's temporal structure and that ARIMA specifications should be periodically re-evaluated.
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