Analyzing Stock Market Dynamics for 10 Leading US Companies: A Multi-Dimensional Approach Using Time Series and Correlation Analysis

Abstract

This paper employs detailed time series and correlation analyses to thoroughly explore the stock market dynamics of 10 leading US corporations. Historical stock data from January 2022 to July 2023, on a daily basis, is analyzed with a focus on key indicators such as transaction volumes, price trajectories, and their interactions. The methodology combines data normalization, GARCH modeling, and descriptive statistics to ensure robust and reliable findings. The results reveal strong correlations among price indicators but question the reliability of trading volumes as predictors of price changes. Tesla’s upward price trajectory highlights investor optimism, while Netflix’s volatility underscores sector-specific challenges. These findings emphasize the significance of time series and correlation analysis in forecasting stock market trends and informing strategic decision-making. The study uncovers critical patterns and linkages governing market behavior, offering valuable insights into investor psychology and strategic decision-making processes.