Interest Sensitivity (IS) Gap–based IRRBB model to analyze Net Interest Income (NII) impact under upward and downward interest rate shocks, implemented in Python with FRM-aligned methodology.
-
Updated
Jan 3, 2026 - Python
Interest Sensitivity (IS) Gap–based IRRBB model to analyze Net Interest Income (NII) impact under upward and downward interest rate shocks, implemented in Python with FRM-aligned methodology.
Python implementation of the BCBS 368 IRRBB standardised framework — EVE & NII sensitivity across 6 prescribed shock scenarios, 19 repricing buckets, full cash flow discounting, Streamlit dashboard.
Python implementation of a leverage-adjusted Duration Gap model to estimate Economic Value of Equity (EVE) sensitivity under interest rate shocks, aligned with FRM and IRRBB methodology.
A modular Python engine for banking book ALM, integrating IRRBB, liquidity risk (LCR/NSFR), stress testing, and treasury management actions.
Yield curve bootstrap and rates pricing on real market data. USD curve bootstrapped from US Treasury CMT par yields (home.treasury.gov), EUR curve ingested from ECB AAA-govt zeros (Svensson model). Bond/swap pricing, IRRBB scenarios, 22 invariant tests. Reproducible in one command.
Add a description, image, and links to the irrbb topic page so that developers can more easily learn about it.
To associate your repository with the irrbb topic, visit your repo's landing page and select "manage topics."