This study proposes a quantitative analytical framework for evaluating and forecasting the dynamics of Vietnamese stock prices using time series models. By integrating econometric models such as Multiple Regression, GARCH, and VAR, alongside technical indicators (MA, MACD, RSI), the re search identifies market patterns, volatility clustering, and cyclical sectoral rotations across the period 2020–2025. Empirical experiments conducted on HOSE data demonstrate that combining financial indicators (P/E, P/B, ROE, ROA) with stochastic modeling significantly enhances predictive accuracy and provides practical insights for both academic research and investment strategy optimization.

Time Series, Stock Market, GARCH, VAR, Regression, Quantitative Finance.