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dc.contributor.authorPérez Villarino, Joel
dc.contributor.authorLeitao, Álvaro
dc.contributor.authorGarcía Rodríguez, José Antonio
dc.date.accessioned2023-03-27T12:42:32Z
dc.date.available2023-03-27T12:42:32Z
dc.date.issued2023
dc.identifier.citationJ. P. Villarino, Á. Leitao, & J.A. García Rodríguez, "Boundary-safe PINNs extension: Application to non-linear parabolic PDEs in counterparty credit risk", Journal of Computational and Applied Mathematics, 425, 2023 [Online] doi:10.1016/j.cam.2022.115041, Available: https://doi.org/10.1016/j.cam.2022.115041es_ES
dc.identifier.urihttp://hdl.handle.net/2183/32780
dc.description.abstract[Abstract]: The goal of this work is to develop a novel strategy for the treatment of the boundary conditions for multi-dimension nonlinear parabolic PDEs. The proposed methodology allows to get rid of the heuristic choice of the weights for the different addends that appear in the loss function related to the training process. It is based on defining the losses associated to the boundaries by means of the PDEs that arise from substituting the related conditions into the model equation itself. The approach is applied to challenging problems appearing in quantitative finance, namely, in counterparty credit risk management. Further, automatic differentiation is employed to obtain accurate approximation of the partial derivatives, the so called Greeks, that are very relevant quantities in the field.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2018/33es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.description.sponsorshipA.L and J.A.G.R. acknowledge the support received by the Spanish MINECO under research project number PDI2019-108584RB-I00, and by the Xunta de Galicia, Spain under grant ED431C 2018/33. All the authors thank to the support received from the CITIC research center, funded by Xunta de Galicia and the European Union (European Regional Development Fund - Galicia Program, Spain ), by grant ED431G 2019/01.es_ES
dc.language.isoenges_ES
dc.publisherElsevier B.V.es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/l Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PDI2019-108584RB-I00/ES/METODOS MATEMATICOS Y COMPUTACIONALES PARA NUEVOS RETOS EN FINANZAS CUANTITATIVAS, MEDIAMBIENTE, BIOTECNOLOGIA E INGENIERIAes_ES
dc.relation.urihttps://doi.org/10.1016/j.cam.2022.115041es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 4.0 International (CC BY-NC-ND 4.0)es_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectBoundary conditionses_ES
dc.subjectCouterparty credit riskes_ES
dc.subjectDeep learninges_ES
dc.subjectNonlineares_ES
dc.subjectPDEses_ES
dc.subjectPINNses_ES
dc.titleBoundary-safe PINNs extension: Application to non-linear parabolic PDEs in counterparty credit riskes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleJournal of Computational and Applied Mathematicses_ES
UDC.volume425es_ES
UDC.startPage115041es_ES
dc.identifier.doi10.1016/j.cam.2022.115041


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