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dc.contributor.author
Embrechts, Paul
dc.contributor.author
Schied, Alexander
dc.contributor.author
Wang, Ruodu
dc.date.accessioned
2022-04-20T11:33:57Z
dc.date.available
2021-12-28T03:58:37Z
dc.date.available
2022-04-20T11:33:57Z
dc.date.issued
2022-01
dc.identifier.issn
0030-364X
dc.identifier.issn
0096-3984
dc.identifier.issn
1526-5463
dc.identifier.other
10.1287/opre.2021.2147
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/522373
dc.description.abstract
We study issues of robustness in the context of Quantitative Risk Management and Optimization. We develop a general methodology for determining whether a given risk-measurement-related optimization problem is robust, which we call "robustness against optimization." The new notion is studied for various classes of risk measures and expected utility and loss functions. Motivated by practical issues from financial regulation, special attention is given to the two most widely used risk measures in the industry, Value-at-Risk (VaR) and Expected Shortfall (ES). We establish that for a class of general optimization problems, VaR leads to nonrobust optimizers, whereas convex risk measures generally lead to robust ones. Our results offer extra insight on the ongoing discussion about the comparative advantages of VaR and ES in banking and insurance regulation. Our notion of robustness is conceptually different from the field of robust optimization, to which some interesting links are derived.
en_US
dc.language.iso
en
en_US
dc.publisher
Institute for Operations Research and the Management Sciences
en_US
dc.subject
robustness
en_US
dc.subject
value-at-risk
en_US
dc.subject
expected shortfall
en_US
dc.subject
optimization
en_US
dc.subject
financial regulation
en_US
dc.title
Robustness in the Optimization of Risk Measures
en_US
dc.type
Journal Article
dc.date.published
2021-11-15
ethz.journal.title
Operations Research
ethz.journal.volume
70
en_US
ethz.journal.issue
1
en_US
ethz.journal.abbreviated
Oper. res.
ethz.pages.start
95
en_US
ethz.pages.end
110
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Catonsville, MD
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02003 - Mathematik Selbständige Professuren::03288 - Embrechts, Paul (emeritus) / Embrechts, Paul (emeritus)
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02204 - RiskLab / RiskLab
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02000 - Dep. Mathematik / Dep. of Mathematics::02204 - RiskLab / RiskLab
ethz.date.deposited
2021-12-28T03:59:22Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2022-04-20T11:34:05Z
ethz.rosetta.lastUpdated
2022-04-20T11:34:05Z
ethz.rosetta.versionExported
true
ethz.COinS
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