This study aims to determine the effect of inflation, interest rates, and global oil prices on the Jakarta Composite Index (JCI) in Indonesia from January 2019 to December 2024. This study uses two analytical methods: the Autoregressive Distributed Lag (ARDL) model to analyze short-term and long-term relationships, and the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to measure JCI volatility. The results of the ARDL analysis indicate that in the short term, only inflation and interest rates have a significant effect. In the long term, inflation has a negative effect, while interest rates and global oil prices have a positive effect on the JCI. The GARCH analysis indicates that the JCI experienced high volatility during the study period, primarily due to fluctuations in oil prices and changes in interest rates.