Measuring the Unmeasurable: An Application of Uncertainty Quantification to Financial Portfolios

24 Pages Posted: 3 Oct 2015

See all articles by Jingnan Chen

Jingnan Chen

University of Illinois at Urbana-Champaign

Mark D. Flood

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

Richard Sowers

University of Illinois at Urbana-Champaign - Department of Mathematics

Date Written: October 1, 2015

Abstract

We extract from the yield curve a new measure of fundamental economic uncertainty, based on McDiarmid's distance and related methods for optimal uncertainty quantification (OUQ). OUQ seeks analytical bounds on a system's behavior, even where the underlying data-generating process and system response function are incompletely specified. We use OUQ to stress test a simple fixed-income portfolio, certifying its safety i.e., that potential losses will be "small" in an appropriate sense. The results give explicit tradeoffs between: scenario count, maximum loss, test horizon, and confidence level. Unfortunately, uncertainty peaks in late 2008, weakening certification assurances just when they are needed most.

Suggested Citation

Chen, Jingnan and Flood, Mark D. and Sowers, Richard, Measuring the Unmeasurable: An Application of Uncertainty Quantification to Financial Portfolios (October 1, 2015). Office of Financial Research Working Paper No. 15-19, Available at SSRN: https://ssrn.com/abstract=2668365 or http://dx.doi.org/10.2139/ssrn.2668365

Jingnan Chen

University of Illinois at Urbana-Champaign ( email )

601 E John St
Champaign, IL Champaign 61820
United States

Mark D. Flood (Contact Author)

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

College Park
College Park, MD 20742
United States

Richard Sowers

University of Illinois at Urbana-Champaign - Department of Mathematics ( email )

1409 W. Green St.
Urbana, IL 61801
United States

HOME PAGE: http://www.math.uiuc.edu/~r-sowers/

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