Modern Portfolio Theory - ETF Asset Allocation

This project implements a Modern Portfolio Theory (MPT) application using Python and Streamlit. The application allows users to visualize the efficient frontier, explore ETF allocations, and optimize portfolios based on Sharpe ratios. Portfolio Stress Testing Monte Carlo Simulation.

Features

• Efficient Frontier Visualization: See the trade-off between risk and return for different portfolios.
• Portfolio Optimization: Adjust allocations using a slider to find the optimal portfolio for your risk tolerance.
• Detailed Allocation Analysis: View detailed breakdowns of ETF allocations, expected returns, variances, and Sharpe ratios.
• Correlation Matrix: Analyze the correlation between selected ETFs.
• ETF Links: Direct links to ETF information for further research.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/mpt-etf-allocation.git

2. Navigate to the project directory:

   cd mpt-etf-allocation

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Run the Streamlit application:

   streamlit run ef.py

2. Open the provided URL in your web browser.

ETF List

• Cash Equivalents: BIL
• Crypto: IBIT
• Fixed Income: LQD, TLT, HYG
• Equities: SPY, QQQ, IWM, EFA, SCZ
• Commodities: DBC, IAU
• Real Estate: XLRE

License

This project is licensed under the MIT License - see the LICENSE file for details.