Volatility dynamics and value at risk (var) estimation: an application of the arima-garch model to icbp and indf stocks
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volatility,
value at risk,
icbp stock,
indf stock
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Abstract
Capital market uncertainty during the COVID-19 pandemic and the economic recovery period emphasizes the importance of accurate volatility modeling and investment risk measurement. This study aims to analyze the volatility dynamics and estimate the risk of losses in shares of PT Indofood CBP Sukses Makmur Tbk (ICBP) and PT Indofood Sukses Makmur Tbk (INDF) from January 2019 to November 2025 using the ARIMA–GARCH and Value at Risk (VaR) approaches. The study uses daily closing stock price data transformed into logarithmic returns. The analysis stages include the Augmented Dickey–Fuller (ADF) stationarity test, ARIMA model identification, ARCH-LM heteroscedasticity testing, GARCH modeling, VaR estimation at the 95% confidence level, and backtesting using the Kupiec test. The results show that the ARIMA(2,0,1) and ARIMA(1,0,1) models are selected for ICBP and INDF shares, respectively, while GARCH(1,1) is the best volatility model for both. The daily VaR estimate indicates a loss risk for INDF of 2.92%, slightly higher than ICBP's 2.86%. The Kupiec test indicates that the frequency of VaR violations corresponds to the expected level. These findings demonstrate that the ARIMA–GARCH approach can be used to describe volatility dynamics and support the risk evaluation of individual stock investments.
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