A Method to Find Diverse and Manageable Sets of Plausible Yet Severe Financial Scenarios

48 Pages Posted: 15 Jan 2014

See all articles by Craig A. Friedman

Craig A. Friedman

TIAA-CREF

Yangyong Zhang

Standard & Poor's - Quantitative Analytics

Date Written: January 14, 2014

Abstract

We introduce a new practical data-intensive method to generate/discover consistent finite representative collections of plausible yet severe macroprudential, microprudential, book-specific, and individual obligor/instrument scenarios. These scenarios are conditioned on current information (including current macroeconomic, index, industry and instrument/obligor-specific information), and can be conditioned on partial future scenario specifications as well (to accommodate regulatory stress testing requirements, for example, the CCAR requirements for banks, the projections of economists, or senior management). Our method is scalable, is designed to work with limited training data, can incorporate the fat-tailed and mutually dependent behavior that is characteristic of many financial quantities, and can reflect model misspecification risk.

Keywords: scenario simulation, stress scenarios, copula models, Basel II and Basel III, loss scenarios, mean center methods, large portfolios, financial systems, sector-specific risk, model misspecification risk

Suggested Citation

Friedman, Craig A. and Zhang, Yangyong, A Method to Find Diverse and Manageable Sets of Plausible Yet Severe Financial Scenarios (January 14, 2014). Available at SSRN: https://ssrn.com/abstract=2379083 or http://dx.doi.org/10.2139/ssrn.2379083

Craig A. Friedman (Contact Author)

TIAA-CREF ( email )

730 3rd Ave
New York, NY 10017
United States

Yangyong Zhang

Standard & Poor's - Quantitative Analytics ( email )

55 Water Street
New York, NY 10041
United States

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