FinTech-MonteCarlo-Project

A Python-based portfolio optimization tool that leverages Modern Portfolio Theory to analyze S&P 500 sectors and identify optimal asset allocations through Monte Carlo simulation.

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Features

• Fetches real-time S&P 500 sector data.
• Calculates sector-wise average prices and returns.
• Performs Monte Carlo simulation for portfolio optimization.
• Identifies portfolios with the maximum Sharpe ratio and minimum volatility.
• Generates visualization of the efficient frontier.

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Dependencies

To run the project, install the following libraries:

pip install pandas yfinance numpy matplotlib scipy scikit-learn