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dc.date.accessioned2015-01-26T17:16:54Z
dc.date.available2015-01-26T17:16:54Z
dc.date.created2012-12-27T14:56:46Z
dc.date.issued2012
dc.identifier.citationLempa, Jukka . Optimal Stopping with Information Constraint. Applied mathematics and optimization. 2012, 66(2), 147-173
dc.identifier.urihttp://hdl.handle.net/10852/41919
dc.description.abstractWe study the optimal stopping problem proposed by Dupuis and Wang (Adv. Appl. Probab. 34:141–157, 2002). In this maximization problem of the expected present value of the exercise payoff, the underlying dynamics follow a linear diffusion. The decision maker is not allowed to stop at any time she chooses but rather on the jump times of an independent Poisson process. Dupuis and Wang (Adv. Appl. Probab. 34:141–157, 2002), solve this problem in the case where the underlying is a geometric Brownian motion and the payoff function is of American call option type. In the current study, we propose a mild set of conditions (covering the setup of Dupuis and Wang in Adv. Appl. Probab. 34:141–157, 2002) on both the underlying and the payoff and build and use a Markovian apparatus based on the Bellman principle of optimality to solve the problem under these conditions. We also discuss the interpretation of this model as optimal timing of an irreversible investment decision under an exogenous information constraint. The definitive version is available at springerlink.comen_US
dc.languageEN
dc.language.isoenen_US
dc.publisherSpringer-Verlag New York
dc.titleOptimal Stopping with Information Constrainten_US
dc.typeJournal articleen_US
dc.creator.authorLempa, Jukka
cristin.unitcode185,15,26,0
cristin.unitnameSenter for matematikk for anvendelser
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2
dc.identifier.cristin977933
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Applied mathematics and optimization&rft.volume=66&rft.spage=147&rft.date=2012
dc.identifier.jtitleApplied mathematics and optimization
dc.identifier.volume66
dc.identifier.issue2
dc.identifier.startpage147
dc.identifier.endpage173
dc.identifier.doihttp://dx.doi.org/10.1007/s00245-012-9166-0
dc.identifier.urnURN:NBN:no-46319
dc.type.documentTidsskriftartikkelen_US
dc.type.peerreviewedPeer reviewed
dc.source.issn0095-4616
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/41919/2/RndIntr.pdf
dc.type.versionAcceptedVersion


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