Against the backdrop of globalization and changing financial markets, investors and policymakers need accurate market volatility forecasts to guide decision-making. Traditional forecasting models are difficult to fully explain the complex market volatility, thus requiring more refined research methods. This study provides an in-depth analysis of the impact of market returns and macroeconomic indicators on Amazon stock volatility by constructing a two-factor model to provide more accurate forecasts. A quantitative approach is used to construct the model, with market returns represented by the CAPM and selected macroeconomic indicators introduced as the second factor. The model parameters are estimated from historical data and empirical analyses verify the predictive effectiveness of the model in different market environments. Preliminary results show that market returns and macroeconomic indicators significantly influence Amazon stock volatility. Market factors dominate volatility in the short term, while macroeconomic factors may have a more significant impact in the long term. This finding contributes to a better understanding of Amazon stock price drivers and provides investors with more targeted decision support.