Efficient simulation for expectations over the union of half-spaces

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dc.contributor.authorAhn, Dohyunko
dc.contributor.authorKim, Kyoung-Kukko
dc.date.accessioned2018-09-18T05:52:53Z-
dc.date.available2018-09-18T05:52:53Z-
dc.date.created2017-11-17-
dc.date.created2017-11-17-
dc.date.created2017-11-17-
dc.date.issued2018-07-
dc.identifier.citationACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION, v.28, no.3-
dc.identifier.issn1049-3301-
dc.identifier.urihttp://hdl.handle.net/10203/245427-
dc.description.abstractWe consider the problem of estimating expectations over the union of half-spaces. Such a problem arises in many applications such as option pricing and stochastic activity networks. More recent applications include systemic risk measurements of financial networks. Assuming that random variables follow a multivariate elliptical distribution, we develop a conditional Monte Carlo method and prove its asymptotic efficiencies. We then demonstrate the numerical performance of the proposed method in three different application areas.-
dc.languageEnglish-
dc.publisherASSOC COMPUTING MACHINERY-
dc.subjectFINANCIAL NETWORKS-
dc.subjectSYSTEMIC RISK-
dc.subjectPROBABILITIES-
dc.titleEfficient simulation for expectations over the union of half-spaces-
dc.typeArticle-
dc.identifier.wosid000444690000007-
dc.identifier.scopusid2-s2.0-85053428319-
dc.type.rimsART-
dc.citation.volume28-
dc.citation.issue3-
dc.citation.publicationnameACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION-
dc.identifier.doi10.1145/3167969-
dc.contributor.localauthorKim, Kyoung-Kuk-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorConditional Monte Carlo-
dc.subject.keywordAuthorrare event simulation-
dc.subject.keywordAuthorelliptical distribution-
dc.subject.keywordAuthorvariance reduction-
dc.subject.keywordPlusFINANCIAL NETWORKS-
dc.subject.keywordPlusSYSTEMIC RISK-
dc.subject.keywordPlusPROBABILITIES-
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