This project implements an Interest Sensitivity (IS) Gap framework to assess the impact of interest rate changes on Net Interest Income (NII), aligned with FRM and IRRBB concepts.
- Repricing bucket-based IS Gap analysis
- Asset-sensitive vs liability-sensitive classification
- Cumulative gap tracking
- Scenario-based ΔNII estimation under user-defined rate shocks
- Interactive rate shock input (+/- bps)
- Dynamic management-style risk interpretation
- Clean, auditable tabular output
- Python
- Pandas
- Ensure Python (3.x) is installed on your system.
- Install the required dependency: pandas
- Download or clone the repository.
- Run the script.
This is a simplified educational model built for learning and demonstration purposes.