Portfolio Optimization with Sharpe Ratio

This project implements a portfolio optimization framework using Python, focusing on maximizing the Sharpe Ratio. The framework evaluates asset allocation strategies and compares the performance of the optimized portfolio against the S&P 500 (SPY).

Features

• Portfolio Optimization: Utilizes scipy.optimize to find the optimal asset weights for maximizing the Sharpe Ratio.
• Data Retrieval: Fetches historical price data and Federal Reserve risk-free rates using yfinance and fredapi.
• Financial Analysis: Calculates annualized returns, covariance matrix, and portfolio metrics.
• Performance Visualization: Uses matplotlib to plot cumulative returns and compare the optimized portfolio against SPY.

Dependencies

• numpy: Numerical computations and matrix operations.
• pandas: Data manipulation and time-series analysis.
• scipy: Optimization and numerical methods.
• yfinance: Fetching historical asset prices.
• fredapi: Retrieving Federal Reserve risk-free rates.
• matplotlib: Visualizing financial data.

Installation

1. Clone the repository:

   git clone <repository-url>

2. Navigate to the project directory:

   cd <project-directory>

3. Install the required packages:

   pip install numpy pandas scipy yfinance fredapi matplotlib

4. Set up environment variables for the Federal Reserve API key:

   • Create a .env file in the project directory with the following content:

     FREDAPI_KEY=your_fred_api_key
     

   • Alternatively, use a generic value eg. 0.20

Usage

1. Update the tickers list with the assets you want to include in the portfolio.

2. Specify the start_date for the historical data analysis in the script.

3. Run the portfolio_optimization.py script:

   python portfolio_optimization.py

4. The script will:

   • Fetch historical price data starting from the specified start_date.
   • Calculate log returns and covariance matrix.
   • Optimize portfolio weights to maximize the Sharpe Ratio.
   • Compare the optimized portfolio against SPY.
   • Plot the cumulative returns of the optimized portfolio and SPY.

Results

• Optimal Weights: Displays the asset allocation that maximizes the Sharpe Ratio.
• Performance Metrics: Shows the expected return, volatility, and Sharpe Ratio of the optimized portfolio.
• Comparison Plot: Visualizes the cumulative returns of the optimized portfolio versus SPY.