This application evaluates four new investment options for inclusion in a client portfolios. It determines the the fund with the most investment potential based on key risk-management metrics: the daily returns, standard deviations, Sharpe ratios, and betas.
- Python interpreter v3.9.12
- Pandas library: Data analysis and manipulation tools
- Matplotlib library: Creating static, animated, and interactive visualizations
- Python sys library: Support for system-specific parameters and functions
- Python pathlib library: Support for Object-oriented filesystem paths
- Python csv library: Support for CSV file reading and writing
To use this risk analysis application simply clone the repository and open the risk_return_analysis.ipynb script in the Jupyter Lab application.
risk_return_analysis.ipynb
The source code for the application is licensed under the MIT license, which you can find in the LICENSE file in this repo.