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dc.contributor.authorBalajewicz, Maciej
dc.contributor.authorToivanen, Jari
dc.date.accessioned2016-08-26T10:02:40Z
dc.date.available2016-08-26T10:02:40Z
dc.date.issued2016
dc.identifier.citationBalajewicz, M., & Toivanen, J. (2016). Reduced order models for pricing American options under stochastic volatility and Jump-diffusion models. In <i>ICCS 2016 : International Conference on Computational Science 2016, 6-8 June 2016, San Diego, California, USA</i> (pp. 734-743). Elsevier BV. Procedia Computer Science, 80. <a href="https://doi.org/10.1016/j.procs.2016.05.360" target="_blank">https://doi.org/10.1016/j.procs.2016.05.360</a>
dc.identifier.otherCONVID_26169990
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/51085
dc.description.abstractAmerican options can be priced by solving linear complementary problems (LCPs) with parabolic partial(-integro) differential operators under stochastic volatility and jump-diffusion models like Heston, Merton, and Bates models. These operators are discretized using finite difference methods leading to a so-called full order model (FOM). Here reduced order models (ROMs) are derived employing proper orthogonal decomposition (POD) and non negative matrix factorization (NNMF) in order to make pricing much faster within a given model parameter variation range. The numerical experiments demonstrate orders of magnitude faster pricing with ROMs.
dc.language.isoeng
dc.publisherElsevier BV
dc.relation.ispartofICCS 2016 : International Conference on Computational Science 2016, 6-8 June 2016, San Diego, California, USA
dc.relation.ispartofseriesProcedia Computer Science
dc.subject.otherreduced order model
dc.subject.otheroption pricing
dc.subject.otherAmerican option
dc.subject.otherlinear complementary problem
dc.titleReduced order models for pricing American options under stochastic volatility and Jump-diffusion models
dc.typeconference paper
dc.identifier.urnURN:NBN:fi:jyu-201608173811
dc.contributor.laitosTietotekniikan laitosfi
dc.contributor.laitosDepartment of Mathematical Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2016-08-17T09:15:04Z
dc.type.coarhttp://purl.org/coar/resource_type/c_5794
dc.description.reviewstatuspeerReviewed
dc.format.pagerange734-743
dc.relation.issn1877-0509
dc.type.versionpublishedVersion
dc.rights.copyright© The Authors. Published by Elsevier B.V. This is an open access article distributed under the terms of a Creative Commons License.
dc.rights.accesslevelopenAccessfi
dc.type.publicationconferenceObject
dc.relation.conferenceInternational Conference on Computational Science
dc.rights.urlhttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.relation.doi10.1016/j.procs.2016.05.360
dc.type.okmA4


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© The Authors. Published by Elsevier B.V. This is an open access article distributed under the terms of a Creative Commons License.
Ellei muuten mainita, aineiston lisenssi on © The Authors. Published by Elsevier B.V. This is an open access article distributed under the terms of a Creative Commons License.