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All Journal International Journal of Quantitative Research and Modeling
Kalfin Kalfin
Universitas Negeri Makassar
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Physics

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Analysis of Stock Return Volatility of PT Asuransi Multi Artha Guna Tbk Using the GARCH-M Model Muh. Yahya; Kalfin Kalfin; Hisyam Ihsan; Atikafairuq Selviana; Andi Widya Pratiwi Anas
International Journal of Quantitative Research and Modeling Vol. 7 No. 2 (2026): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v7i2.1334

Abstract

This study aims to analyze the volatility of stock returns of PT Asuransi Multi Artha Guna Tbk using the Generalized Autoregressive Conditional Heteroskedasticity in Mean (GARCH-M) model during the 2019–2024 period. The data used in this study are secondary data in the form of daily closing stock prices of AMAG.JK obtained from Yahoo Finance, with a total of 1,466 observations. The analytical stages include the calculation of log returns, stationarity testing using the Augmented Dickey-Fuller (ADF) test, Ljung-Box autocorrelation test, ARCH-LM test, selection of the best GARCH model based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), estimation of the GARCH-M model, conditional volatility analysis, and volatility forecasting. The results indicate that the stock return data of AMAG.JK are stationary and contain ARCH effects, making them appropriate for analysis using the GARCH model. Based on the AIC and BIC criteria, the best model selected is GARCH(1,2). The estimation results of the GARCH(1,2)-M model show that the ARCH and GARCH parameters are statistically significant, indicating the presence of volatility clustering and volatility persistence phenomena in the stock returns of AMAG.JK. However, the risk premium parameter in the GARCH-M model is not statistically significant, implying that conditional volatility does not significantly affect expected stock returns. The volatility forecasting results show that the volatility level of AMAG.JK stock tends to increase gradually in future periods. Overall, the GARCH(1,2)-M model is capable of describing the dynamics of volatility in AMAG.JK stock returns during the research period effectively.
Co-Authors Andi Widya Pratiwi Anas Atikafairuq Selviana Hisyam Ihsan Muh. Yahya