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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.
The Influence of Numerical literacy on Students’ Mathematical Problem-Solving Ability Danial Danial; Kalfin Kalfin; Husnul Muawiyah
International Journal of Ethno-Sciences and Education Research Vol. 6 No. 2 (2026): International Journal of Ethno-Sciences and Education Research (IJEER)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v6i2.1201

Abstract

This study aims to determine the influence of numerical literacy on the improvement of mathematical problem-solving ability among Grade VIII students at State Junior High School of 13 Sinjai. This research employed an ex post facto design with a quantitative approach. The population of this study consisted of all Grade VIII students at State Junior High School of 13 Sinjai, totaling 57 students, with a saturated sampling technique. Data analysis was conducted using simple linear regression to examine the influence of numerical literacy on students’ mathematical problem-solving ability. The results showed that the significance value was 0.000 < 0.05 and the calculated t-value was 18.24, which was greater than the t-table value of 2.101, indicating a significant effect between numerical literacy and students’ mathematical problem-solving ability. In addition, the coefficient of determination (R Square) value of 0.948 indicates that numerical literacy contributes 94.8% to the improvement of students’ mathematical problem-solving ability, while the remaining percentage is influenced by other factors outside this study