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Reconstruction of the local volatility function using the Black–Scholes model

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dc.contributor.authorKim, S.-
dc.contributor.authorHan, H.-
dc.contributor.authorJang, H.-
dc.contributor.authorJeong, D.-
dc.contributor.authorLee, C.-
dc.contributor.authorLee, W.-
dc.contributor.authorKim, J.-
dc.date.accessioned2021-12-03T00:41:32Z-
dc.date.available2021-12-03T00:41:32Z-
dc.date.created2021-08-31-
dc.date.issued2021-04-
dc.identifier.issn1877-7503-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/129000-
dc.description.abstractIn this paper, we propose a robust and accurate numerical algorithm to reconstruct a local volatility function using the Black–Scholes (BS) partial differential equation (PDE). Using the BS PDE and given market data, option prices at strike prices and expiry times, a time-dependent local volatility function is computed. The proposed algorithm consists of the following steps: (1) The time-dependent volatility function is computed using a recently developed method; (2) A Monte Carlo simulation technique is used to find the effective region which has a strong influence on option prices; and we partition the effective domain into several sub-regions and define a local volatility function based on the time-dependent volatility function on the sub-regions; and (3) Finally, we calibrate the local volatility function using the fully implicit finite difference method and the conjugate gradient optimization algorithm. We demonstrate the robustness and accuracy of the proposed local volatility reconstruction algorithm using manufactured volatility surface and real market data. © 2021 Elsevier B.V.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherElsevier B.V.-
dc.subjectCommerce-
dc.subjectConjugate gradient method-
dc.subjectCosts-
dc.subjectFinite difference method-
dc.subjectAccurate numerical algorithms-
dc.subjectConjugate gradient optimization-
dc.subjectEffective domains-
dc.subjectFully implicit finite differences-
dc.subjectMonte carlo simulation technique-
dc.subjectPartial differential equations (PDE)-
dc.subjectReconstruction algorithms-
dc.subjectTime-dependent volatility function-
dc.subjectMonte Carlo methods-
dc.titleReconstruction of the local volatility function using the Black–Scholes model-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, J.-
dc.identifier.doi10.1016/j.jocs.2021.101341-
dc.identifier.scopusid2-s2.0-85102292911-
dc.identifier.wosid000649742800004-
dc.identifier.bibliographicCitationJournal of Computational Science, v.51-
dc.relation.isPartOfJournal of Computational Science-
dc.citation.titleJournal of Computational Science-
dc.citation.volume51-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.subject.keywordPlusCommerce-
dc.subject.keywordPlusConjugate gradient method-
dc.subject.keywordPlusCosts-
dc.subject.keywordPlusFinite difference method-
dc.subject.keywordPlusAccurate numerical algorithms-
dc.subject.keywordPlusConjugate gradient optimization-
dc.subject.keywordPlusEffective domains-
dc.subject.keywordPlusFully implicit finite differences-
dc.subject.keywordPlusMonte carlo simulation technique-
dc.subject.keywordPlusPartial differential equations (PDE)-
dc.subject.keywordPlusReconstruction algorithms-
dc.subject.keywordPlusTime-dependent volatility function-
dc.subject.keywordPlusMonte Carlo methods-
dc.subject.keywordAuthorBlack–Scholes equation-
dc.subject.keywordAuthorFinite difference method-
dc.subject.keywordAuthorLocal volatility-
dc.subject.keywordAuthorMonte Carlo simulation-
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