Measuring the unmeasurable: an application of uncertainty quantification to Treasury bond portfolios

Jingnan Chen, Mark D. Flood, Richard B. Sowers

Research output: Contribution to journalArticlepeer-review

Abstract

We extract from the yield curve a new measure of fundamental economic uncertainty, based on McDiarmid’s diameter and related methods for optimal uncertainty quantification (OUQ). OUQ seeks analytical bounds on a system’s behaviour, even where aspects of the underlying data-generating process and system response function are not completely known. 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.

Original languageEnglish (US)
Pages (from-to)1491-1507
Number of pages17
JournalQuantitative Finance
Volume17
Issue number10
DOIs
StatePublished - Oct 3 2017

Keywords

  • Model risk
  • Optimal uncertainty quantification
  • Stress testing
  • Uncertainty
  • Yield curve

ASJC Scopus subject areas

  • Finance
  • Economics, Econometrics and Finance(all)

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