The stock market plays a crucial role in modern financial systems, serving as an important platform for corporate financing, resource allocation, enterprise value discovery, and investor wealth growth. The volatility of the stock market directly impacts investors' returns, market stability, and economic development. Therefore, studying the sources and influencing factors of stock market volatility is of great significance for maintaining financial stability, guiding investment strategies, and formulating effective economic policies. Research on stock market volatility has undergone a long evolution. Early studies focused primarily on testing market efficiency and constructing volatility models. As time went on, attention began to shift to the time-varying nature of volatility, volatility clustering, long memory, and the relationship between volatility and other market variables. In recent years, with the rapid development of big data and artificial intelligence technologies, new data sources and methodologies have been applied to research on stock market volatility, revealing the impact of subjective factors such as market sentiment and investor behavior on stock market volatility. In the current economic and financial context, in-depth research on stock market volatility holds significant theoretical and practical value. Through comprehensive analysis of stock market volatility, one can understand the operating status of the market, grasp its future trends, and provide effective investment decision-making basis for investors. At the same time, governments and regulatory agencies can also rely on these research findings to formulate more reasonable and effective economic policies to maintain the stability and prosperity of financial markets. Furthermore, for academia, research on stock market volatility also contributes to driving innovation and development in financial theory, providing theoretical support for the standardized operation of financial markets.