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GARCH-M Approach for Energy Stock Volatility Estimation in the LQ45 Index Adeliya Fernanda; Chairamanda Binar Gunawan Gunawan
International Journal of Quantitative Research and Modeling Vol. 7 No. 1 (2026): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v7i1.1118

Abstract

Stock price movements in the energy sector in Indonesia often exhibit high volatility, especially for stocks listed in the LQ45 Index. This high volatility is caused by vulnerability to fluctuations in global commodity prices, energy transition issues, and regulatory changes, which in turn pose challenges in investment decision-making and risk management. This study aims to estimate the volatility of energy stocks in the LQ45 Index using the Generalized Autoregressive Conditional Heteroskedasticity in Mean (GARCH-M) approach. This model was chosen because of its ability to dynamically model return variance (volatility) while linking it to expected returns, thus enabling a direct analysis of the risk-return trade-off. The data analyzed are daily returns from January 17, 2020, to December 27, 2024, for eight energy stocks in the LQ45 Index: ADRO, BRPT, ITMG, MEDC, PGAS, PGEO, PTBA, and UNTR. The analysis was conducted by building the most optimal GARCH-M model and evaluating the estimation results through statistical criteria. The research results are expected to demonstrate significant volatility persistence in energy stocks, while providing strong evidence of the link between increased risk and expected returns. Therefore, the application of the GARCH-M model is expected to make a significant contribution to understanding the risk-return dynamics in the domestic energy sector and provide a basis for investors and portfolio managers in formulating more adaptive strategies.