Portfolio Pulse is an intuitive and comprehensive portfolio analysis tool designed for investors to analyze and optimize their stock portfolios. Leveraging modern portfolio theory, it provides insights into historical performance, risk metrics, correlations, and optimized asset allocation to help you make informed investment decisions.
- Stock Selection: Easily add stocks from the S&P 500 to your portfolio for analysis.
- Historical Data Analysis: Visualize historical closing prices, daily returns, and cumulative returns.
- Correlation Matrix: Examine the correlation between the stocks in your portfolio for effective diversification.
- Risk and Return Metrics: Analyze daily returns, annualized volatility, and return per unit of risk.
- Portfolio Optimization: Use the efficient frontier to optimize your portfolio for the maximum Sharpe ratio.
- Visualizations: Generate interactive charts and plots for better understanding and presentation of data.
- Performance Metrics: Get key performance indicators like expected annual return, annual volatility, and Sharpe ratio.
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Clone the repository:
git clone https://github.com/yourusername/portfolio-pulse.git cd portfolio-pulse -
Install the required packages:
pip install -r requirements.txt
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Run the Streamlit app:
streamlit run app.py
- Open the app in your web browser.
- Enter the stock symbols in your portfolio from the S&P 500.
- Select the desired date range for analysis.
- Click on "Analyze" to generate detailed insights and visualizations of your portfolio.
Contributions are welcome! Please fork the repository and submit a pull request for any enhancements or bug fixes.
This project is licensed under the MIT License. See the LICENSE file for more details.