Analysis of LQ45 Index Volatility Using the GARCH Model and Its Implications for Retail Investment Risk during the 2020-2025 Period.

Abstract

The growth of individual investors in the Indonesian capital market has resulted in greater trading activity in the stock market, particularly in the blue-chip stocks that are constituents of the LQ45 index. Although the LQ45 stocks have high liquidity and a significant market capitalization, they are still subject to market risk, which is reflected in the changing returns over time. This study examines the volatility of the LQ45 index, which is a measure of the risk of retail investment in Indonesia, using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. For the study, the author uses secondary data of daily returns of the LQ45 index from 2021 to 2025 and uses the time series econometric method. The author undertakes the following analytical steps: tests for stationarity, tests for the presence of ARCH (conditional heteroskedasticity), and estimates the GARCH(1,1) model. The findings show that the returns on the LQ45 index are stationary and that they contain conditional heteroskedasticity and volatility clustering. Estimation from the GARCH(1,1) model shows that prior shocks, and the prior period's variance, strongly affect volatility, reflecting the model's volatility persistence. Additionally, further standardized residual diagnostics reveal that GARCH(1,1) model appropriately describes the volatility dynamics. These findings indicate that the risk related to retail investment in LQ45 stocks is both dynamic and persistent, which calls for adaptive risk management. This study theoretically advances the measurement of stock market volatility, and in Indonesia, it has practical implications for retail investors and regulators in risk management and financial education.