DC FieldValueLanguage
dc.contributorDepartment of Applied Mathematicsen_US
dc.creatorHuang, YJen_US
dc.creatorYu, Xen_US
dc.date.accessioned2021-06-23T07:38:20Z-
dc.date.available2021-06-23T07:38:20Z-
dc.identifier.issn0960-1627en_US
dc.identifier.urihttp://hdl.handle.net/10397/90357-
dc.language.isoenen_US
dc.publisherWiley-Blackwellen_US
dc.subjectAmbiguity attitudeen_US
dc.subjectEquilibrium stopping policiesen_US
dc.subjectGeneralized measurable projection theoremen_US
dc.subjectModel ambiguityen_US
dc.subjectOptimal stoppingen_US
dc.subjectReal options valuationen_US
dc.subjectTime inconsistencyen_US
dc.titleOptimal stopping under model ambiguity : a time-consistent equilibrium approachen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage979en_US
dc.identifier.epage1012en_US
dc.identifier.volume31en_US
dc.identifier.issue3en_US
dc.identifier.doi10.1111/mafi.12312en_US
dcterms.abstractAn unconventional approach for optimal stopping under model ambiguity is introduced. Besides ambiguity itself, we take into account how ambiguity-averse an agent is. This inclusion of ambiguity attitude, via an (Formula presented.) -maxmin nonlinear expectation, renders the stopping problem time-inconsistent. We look for subgame perfect equilibrium stopping policies, formulated as fixed points of an operator. For a one-dimensional diffusion with drift and volatility uncertainty, we show that any initial stopping policy will converge to an equilibrium through a fixed-point iteration. This allows us to capture much more diverse behavior, depending on an agent's ambiguity attitude, beyond the standard worst-case (or best-case) analysis. In a concrete example of real options valuation under model ambiguity, all equilibrium stopping policies, as well as the best one among them, are fully characterized under appropriate conditions. It demonstrates explicitly the effect of ambiguity attitude on decision making: the more ambiguity-averse, the more eager to stop—so as to withdraw from the uncertain environment. The main result hinges on a delicate analysis of continuous sample paths in the canonical space and the capacity theory. To resolve measurability issues, a generalized measurable projection theorem, new to the literature, is also established.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationMathematical finance, July 2021, v. 31, no. 3, p. 979-1012en_US
dcterms.isPartOfMathematical financeen_US
dcterms.issued2021-07-
dc.identifier.scopus2-s2.0-85104406162-
dc.description.validate202106 bchyen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera0937-n01-
dc.identifier.SubFormID2178-
dc.description.fundingSourceRGCen_US
dc.description.fundingText25202719en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2023.07.31en_US
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