Modeling the Volatility-Return Relationship in the Indonesian Stock Market using the GARCH-M Framework

The LQ45 Index was observed to be in the red zone, with a decline of 9.64% year-to-date (YTD), reaching the level of 877.02. The LQ45 Index became increasingly weakened following the announcement of Donald Trump's victory in the U.S. presidential election, which impacted the Indonesian capital market. It was recorded that the LQ45 Index fell by 5.3% during the final trading month of 2024. Nevertheless, there remains a potential for strengthening the stock prices of LQ45 constituent issuers in the remainder of this year, particularly in December 2024. One of the stocks recommended by IDX is PT Indofood CBP Sukses Makmur Tbk., which has also been one of the most liquid companies according to IDX throughout 2024. The return volatility of stocks in emerging markets is generally much higher than that of developed markets. High volatility reflects a higher level of risk faced by investors, as it indicates significant fluctuations in stock price movements. Therefore, equity investments in Indonesia carry a potentially high level of risk. A common characteristic of financial time series data, particularly return data, is that the probability distribution of returns exhibits fat tails and volatility clustering, often referred to as heteroscedasticity. Time series models that can be used to model these conditions include ARCH and GARCH models. One variation of the ARCH/GARCH models is the Generalized Autoregressive Conditional Heteroscedasticity in Mean (GARCH-M) model, which incorporates the effect of volatility into the mean equation. The purpose of this study is to predict volatility using the GARCH-M model in the analysis of daily closing price return data of PT Indofood CBP Sukses Makmur Tbk. The best model used for volatility forecasting is ARIMA(2,0,1) GARCH(1,1)-M.