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Description

This project demonstrates portfolio optimization using PySpark. It includes data collection, logic explantion, and optimization algorithms to create efficient investment portfolios. The most efficient portfolio is calculated using the Sharpe ratio.

Technologies Used

  • Programming Languages: Python
  • Frameworks: PySpark
  • Libraries: NumPy, pandas, Matplotlib
  • Other Tools: Git, Jupyter Notebook

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