Spectral risk measures: the risk quadrangle and optimal approximation

Kouri, Drew P.

doi:10.1007/s10107-018-1267-3

Title: Spectral risk measures: the risk quadrangle and optimal approximation

Journal Article · Thu May 24 00:00:00 EDT 2018 · Mathematical Programming

DOI:https://doi.org/10.1007/s10107-018-1267-3· OSTI ID:1441457

Kouri, Drew P. ^[1]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

We develop a general risk quadrangle that gives rise to a large class of spectral risk measures. The statistic of this new risk quadrangle is the average value-at-risk at a specific confidence level. As such, this risk quadrangle generates a continuum of error measures that can be used for superquantile regression. For risk-averse optimization, we introduce an optimal approximation of spectral risk measures using quadrature. Lastly, we prove the consistency of this approximation and demonstrate our results through numerical examples.

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Research Organization:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC04-94AL85000; NA0003525

OSTI ID:: 1441457

Report Number(s):: SAND-2018-5344J; 663229

Journal Information:: Mathematical Programming, Vol. 174; ISSN 0025-5610

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 1 work

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