Stock market volatility is a crucial topic in financial research due to its impact on investment decisions and economic stability. This study conducts a bibliometric analysis of existing literature from 2020 to 2025, identifying key theoretical frameworks, methodologies, and research gaps. The analysis highlights theories such as the Efficient Market Hypothesis, Behavioral Finance, and Volatility Spillover Theory, along with common forecasting techniques like GARCH models and sentiment analysis. By connecting these insights to knowledge management principles, this study demonstrates how financial research can contribute to knowledge discovery, sharing, and innovation. Additionally, it proposes future research directions that align with the goals of knowledge management, including integrating alternative data sources, improving long-term volatility predictions, and enhancing macroeconomic-firm level interactions. Addressing these gaps can enhance market prediction models and improve financial stability.