Analisis Volatilitas dan Peramalan Return Saham Perusahaan Asuransi Menggunakan Model Garch: Studi Kasus PT Maskapai Reasuransi Indonesia Tbk - Azmilah Hapidhatur Rahmah; Fithri Sri Mulyani; Ahmad Fitri (Pusat Studi Bahasa dan Publikasi Ilmiah, 2026)
This study aims to analyze the volatility and forecast the stock returns of PT Maskapai Reasuransi Indonesia Tbk. during the 2022–2025 period using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. The company was selected because it represents the reinsurance subsector, which has received relatively limited attention in stock return volatility studies compared with other financial sectors listed on the Indonesia Stock Exchange. This study uses secondary data in the form of daily closing stock prices, which were transformed into log returns. The analysis consisted of descriptive statistics, stationarity testing using the Augmented Dickey-Fuller (ADF) test, ARIMA model identification, ARCH-LM testing, GARCH(1,1) estimation, model evaluation, and forecasting. The results show that the return series is stationary (ADF p-value = 0.01), and the best mean model is ARIMA(1,0,1). The ARCH-LM test confirms the presence of heteroscedasticity (p-value = 9.258 × 10⁻¹⁰), supporting the application of the GARCH model. The estimated GARCH(1,1) model produced α = 0.138186 and β = 0.816668, indicating persistent stock return volatility. Model evaluation confirmed that the model satisfied residual diagnostic criteria, with no residual autocorrelation, no remaining ARCH effects, and an RMSE of 0.03960696. Forecasting results indicate that stock returns and volatility tend to converge toward more stable conditions, while volatility is influenced more by previous-period volatility than by short-term shocks. These findings contribute to the literature on stock return volatility modeling in the Indonesian reinsurance sector and provide useful information for risk management and investment decision-making.