Synthetic Asset Portfolio Simulator

This is a Python-based application that simulates asset prices in a portfolio, allowing you to explore correlations, returns, volatility, and portfolio performance. The app is interactive and easy to use for financial simulation purposes.

Features

• Simulate asset prices: Generate asset price paths using random returns based on user-defined or randomized mean returns and volatility.
• Adjustable correlation: Control the average correlation between assets in the portfolio.
• Custom parameters: Set the number of assets, the number of years for the simulation, and return and volatility parameters.
• Advanced options: Randomize mean returns and volatility for each asset.
• Performance metrics: Analyze performance metrics such as Sharpe Ratio, Sortino Ratio, Calmar Ratio, Maximum Drawdown, and more.
• Correlation matrix: View and adjust the correlation matrix of assets.
• Compare portfolios across correlations: Evaluate portfolio performance with different correlation settings.

Installation

1. Clone the repository:

   git clone https://github.com/your-username/PortfolioCorrelationsSimulator.git
   cd PortfolioCorrelationsSimulator

2. Set up a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required dependencies:

   pip install -r requirements.txt

How to Run

1. After installing the dependencies, you can run the app using Streamlit:

   streamlit run src/asset_correlation_app.py

2. This will start a local server. You can access the app by opening the URL provided in the terminal (usually http://localhost:8501/).

Usage

• Number of Assets: Select how many assets you want in your portfolio.
• Correlation: Set the average correlation between assets, or let it vary randomly.
• Simulation Length: Choose how many years to simulate.
• Return Parameters: Customize the expected mean annual return and volatility for the assets.
• Advanced Options: Enable randomization of the mean returns and volatility across different assets.
• Visualizations and Metrics: The app displays the asset prices and calculates performance metrics for each asset and the portfolio.

Dependencies

• Python 3.7+
• Streamlit
• NumPy
• Pandas
• Plotly

Install the dependencies using:

pip install -r requirements.txt

License

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

Acknowledgments

• The application uses financial theories of asset returns, volatility, and correlation. Special thanks to the developers of Streamlit, NumPy, Pandas, and Plotly for the libraries that make this simulation possible.

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Feel free to contribute by submitting issues or pull requests.