<![CDATA[This study examines the impact of quantum trading algorithm implementation on the dynamics of LQ45 stock price volatility on the Indonesia Stock Exchange. The main objective of the study is to analyze changes in volatility patterns that occur after the implementation of quantum trading, as well as evaluate its effectiveness in predicting price movements. The research uses an experimental quantitative approach with tick-by-tick data of LQ45 stocks during the period 2020-2024. The applied methodology combines quantum feature mapping and quantum kernel estimation for algorithm development, as well as GARCH and realized volatility models for volatility measurement. The results showed that the implementation of the quantum trading algorithm significantly affected the market microstructure, with a decrease in volatility of 18.5% in the post-implementation period. The quantum algorithm exhibits 87.3% predictive accuracy in identifying price movements, far surpassing conventional methods. The findings have important implications for regulators in developing a regulatory framework for algorithmic trading, as well as for market participants in optimizing investment strategies. The research makes a significant contribution through the development of a hybrid model that integrates quantum computing with conventional volatility analysis, opening a new paradigm in the study of the microstructure of the Indonesian capital market.]]>
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