Systematic Scenario Selection: Stress Testing and the Nature of Uncertainty

Quantitative Finance, 15(1), 2015, January, 43-59.

48 Pages Posted: 4 Sep 2008 Last revised: 31 Jul 2015

See all articles by Mark D. Flood

Mark D. Flood

R. H. Smith School of Business, U. of Maryland

George Korenko

U.S. Federal Housing Finance Agency

Date Written: February 7, 2013

Abstract

We present a technique for selecting multidimensional shock scenarios for use in financial stress testing. The methodology systematically enforces internal consistency among the shock dimensions by sampling points of arbitrary severity from a plausible joint probability distribution. The approach involves a grid search of sparse, well distributed, stress-test scenarios, which we regard as a middle ground between traditional stress testing and reverse stress testing. Choosing scenarios in this way reduces the danger of "blind spots" in stress testing. We suggest extensions to address the issues of non-monotonic loss functions and univariate shocks. We provide tested and commented source code in Matlab®.

Keywords: quasi-Monte Carlo, risk management, stress testing, maximum portfolio loss, elliptical distribution, value at risk

JEL Classification: C15, C63, G1

Suggested Citation

Flood, Mark D. and Korenko, George, Systematic Scenario Selection: Stress Testing and the Nature of Uncertainty (February 7, 2013). Quantitative Finance, 15(1), 2015, January, 43-59.. Available at SSRN: https://ssrn.com/abstract=1262896 or http://dx.doi.org/10.2139/ssrn.1262896

Mark D. Flood (Contact Author)

R. H. Smith School of Business, U. of Maryland ( email )

College Park
College Park, MD 20742
United States

George Korenko

U.S. Federal Housing Finance Agency ( email )

1700 G St., NW
Washington, DC 20006
United States

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