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Conducted in-depth time series analysis on stock market data for major tech companies like Amazon, Google, Apple, and Microsoft. Utilized multivariable analysis to explore the inter-relationship between stock closing prices and daily % return, visualized findings using Seaborn library, and performed value at risk calculations for each company.

  • Updated Sep 9, 2024
  • Jupyter Notebook

Time Series Analysis This repository contains codes for performing time series analysis. The main focus is on data manipulation, visualization, and modeling techniques using libraries such as pandas, numpy, matplotlib, and statsmodels. Key topics include data cleaning, removing duplicates, trend and seasonality decomposition, and forecasting

  • Updated Jul 6, 2024
  • Jupyter Notebook

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