A Multi-Dimensional Analysis of Stock Market Dynamics for 10 Leading US Companies: 2022-2023

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 integrates data normalization, GARCH modeling, and descriptive statistics, ensuring robust findings. Skewness, Kurtosis, and Jarque-Bera tests assess data normality. 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 statistical results, including mean values and correlation coefficients, are explicitly presented to enhance clarity. The study uncovers critical patterns and linkages governing market behavior, offering valuable insights into investor psychology and strategic decision-making processes.