Scope: App NIMo contains Princeton Bank Consortium (PBC) research and development links and references for Net Interest Margin Optimization applications. The PBC will be the production side links and references with applications oriented to Treasury and Federal Reserve users. Here and in the subsequent website tabs we include additional technical publications and presentations on topics ranging over: Net Interest Margin Optimization, proto data layout, market and macro variables, external source and packages used in PBC infrastructure, and applications for Net Interest Model optimization.
Documents: Note “NIMo” is short hand for Net Interest Margin Optimization.
Finding NIMo v10 – short paper describing the NIMo single period model and demonstrating a one basis point increase in NIM for a plausible capital plan scenario with the native Excel LP Optimizer.
Funding NIMo v1 – Apr 2015 presentation of Net Interest Margin Optimization to Cray.
NIMo Reference Server -These are plans for a generic open source –o2 gcc dev server with a fully AVX2 optimized option for full balance sheet simulation. This generic simulation code will be a reference for a Consortium of banks and financial service firms to promote standards development, competitive performance, and computational stability in CCAR balance sheet simulation.
- Comparison of Transfer Pricing vs NIMo on existing data.
- NIMo Explanatory Model
- Compare Aggregate vs Security-by-Security NIMo
We present basic references and data for the Princeton Bank Consortium related to the numerical optimization of Net Interest Margin in the capital plan of systemically important US Banks. The short report (Covas, Rezende, & Vojtech, 2015) defines Net Interest Margin and outlines the recent behavior of NIM in the margin compression following the 2007-8 Credit Crisis. The McKinsey report (Buehler, Noteboom, & Williams, 2013) discusses the mechanisms for managing NIM at systematically important banking institutions (Financial Stabilty Board, 2016). The literature typically refers to the optimization of Net Interest Margin as an informal management process as in (Buehler, Noteboom, & Williams, 2013) rather than the numerical optimization of Net Interest Margin as outlined in the paper (Sandberg, 2015). The Fed’s CCAR documentation (US Federal Reserve, 2017) and (Buehler, Noteboom, & Williams, 2013) explain parts of the capital planning process for U. S. banks and the surrounding capital constraints. The Speeches & Testimony in (Gruenberg, 2017) summarize the post Credit Crisis U.S. regulatory environment. The opportunity for the PBC applications developed as (1) the regulators mandated that banks track their accrual portfolios at the security level and (2) the cost of floating point modeling and forecasting dropped precipitously with technology advances in commodity microprocessors.
Accuity. (2017). Top Banks in the World. Retrieved from Bank Rankings: https://accuity.com/resources/bank-rankings/
Buehler, K., Noteboom, P., & Williams, D. (2013). Between deluge and drought: The future of US bank liquidity and funding. McKinsey, Working Papers on Risk. McKinsey.
Covas, F. B., Rezende, M., & Vojtech, C. M. (2015). Why Are Net Interest Margins of Large Banks So Compressed? Federal Reserve System, Board of Governers. FEDS Notes.
Federal Reserve Bank of St. Louis. (2017). Net Interest Marging for U.S. Banks. (FRED, Producer) Retrieved from FRED – Economic Data: https://fred.stlouisfed.org/series/USNIM/
Financial Stabilty Board. (2016). 2016 list of global systemically important banks (G-SIBs). FSB.
Gruenberg, M. J. (2017). Speeches & Testimony. (Chairman, Producer, & FDIC) Retrieved from fdic.gov: https://www.fdic.gov/news/news/speeches/
Sandberg, J. (2015). Finding NIMo. Princeton: Princeton Bank Consortium.
US Federal Reserve. (2017). Comprehensive Capital Analysis and Review 2017: Assessment Framework and Results. Federal Reserve System, Board of Governers.