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

Author

Listed:
  • Jingnan Chen

    (Singapore University of Technology and Design)

  • Mark D. Flood

    (Office of Financial Research)

  • Richard B. Sowers

    (University of Illinois at Urbana-Champaign)

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

  • Jingnan Chen & Mark D. Flood & Richard B. Sowers, 2015. "Measuring the Unmeasurable: An Application of Uncertainty Quantification to Financial Portfolios," Working Papers 15-19, Office of Financial Research, US Department of the Treasury.
    • Handle: RePEc:ofr:wpaper:15-19
    as

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    References listed on IDEAS

    as
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