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dc.contributor.authorArregui, Íñigo
dc.contributor.authorSimonella, Roberta
dc.contributor.authorVázquez, Carlos
dc.date.accessioned2024-04-16T08:24:01Z
dc.date.available2024-04-16T08:24:01Z
dc.date.issued2024-03
dc.identifier.citationÍ. Arregui, R. Simonella, and C. Vázquez, "Models and numerical methods for XVA pricing under mean reversion spreads in a multicurrency framework", Communications in Nonlinear Science and Numerical Simulation, Vol. 130, 107725, Mar. 2024, doi: 10.1016/j.cnsns.2023.107725es_ES
dc.identifier.urihttp://hdl.handle.net/2183/36210
dc.description.abstract[Abstract]: In this article we make some new relevant contributions to the computation of total valuation adjustments (XVA) for financial derivatives involving several currencies. From the modelling point of view, for the credit spreads we consider the more realistic exponential Vasicek and CIR positive mean reversion processes. Moreover, the derivative is partially collateralized in cash in a foreign currency and the collateral value is a percentage of the derivative prices. Under this modelling assumptions and using appropriate dynamic hedging methodologies, we obtain formulations in terms of linear and nonlinear partial differential equations, which are solved with Lagrange-Galerkin methods in low dimension. For higher dimensions, we use the Monte Carlo techniques for the equivalent formulations in terms of expectations. These techniques include a multilevel Picard iteration method for the nonlinear case. Finally, the methodologies are applied to several European options with different payoffs and the numerical results are discussed.es_ES
dc.description.sponsorshipThis work has been funded by EU H2020-MSCA-ITN-2018 (ABC-EU-XVA Grant Agreement 813261), Spanish Ministry of Science and Innovation (Grant PID2019-108584RB-I00 ) and by Galician Government (Grant ED431C2018/033), both including FEDER financial support. Authors also acknowledge the support received from the Centro de Investigación de Galicia (CITIC), funded by Xunta de Galicia and the European Union (European Regional Development Fund, Galicia 2014–2020 Program), by grant ED431G 2019/01.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C2018/033es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.language.isoenges_ES
dc.publisherElsevier B.V.es_ES
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/813261es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108584RB-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.cnsns.2023.107725es_ES
dc.rightsAtribució-NonComercial-SinDerivadas 4.0 International (CC BY-NC-ND)es_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject(non)linear PDEses_ES
dc.subjectFinancial derivativeses_ES
dc.subjectLagrange-Galerkin methodes_ES
dc.subjectMean reversion processeses_ES
dc.subjectMonte Carlo techniqueses_ES
dc.subjectMulticurrency settinges_ES
dc.subjectMultilevel Picard iterationes_ES
dc.subjectXVAes_ES
dc.titleModels and numerical methods for XVA pricing under mean reversion spreads in a multicurrency frameworkes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleCommunications in Nonlinear Science and Numerical Simulationes_ES
UDC.volume130es_ES
UDC.issue107725es_ES
dc.identifier.doi10.1016/j.cnsns.2023.107725


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