نمایش مختصر رکورد

dc.contributor.authorNauef Al-Qazaz, Qutaibaen_US
dc.contributor.authorAli, Ahmeden_US
dc.date.accessioned1400-12-14T14:23:31Zfa_IR
dc.date.accessioned2022-03-05T14:23:31Z
dc.date.available1400-12-14T14:23:31Zfa_IR
dc.date.available2022-03-05T14:23:31Z
dc.date.issued2022-01-01en_US
dc.date.issued1400-10-11fa_IR
dc.date.submitted2021-12-11en_US
dc.date.submitted1400-09-20fa_IR
dc.identifier.citationNauef Al-Qazaz, Qutaiba, Ali, Ahmed. (2022). Bayesian inference of fractional brownian motion of multivariate stochastic differential equations. International Journal of Nonlinear Analysis and Applications, 13(1), 2425-2454. doi: 10.22075/ijnaa.2022.5944en_US
dc.identifier.issn2008-6822
dc.identifier.urihttps://dx.doi.org/10.22075/ijnaa.2022.5944
dc.identifier.urihttps://ijnaa.semnan.ac.ir/article_5944.html
dc.identifier.urihttps://iranjournals.nlai.ir/handle/123456789/879784
dc.description.abstractThere have been much interest in analysis of stochastic differential equation with long memory, represented by fractional diffusion process, this property have been proved itself in financial mathematic  as intrinsic character of financial time series, so finding an appropriate method for estimate and analyze stochastic differential equations with long memory is a very important contemporary topic, in this paper we suggest a method for a system of stochastic differential equations with long memory, also we use the Bayesian methodology to incorporate the advanced knowledge , in addition we apply renormalized integral known in literature as Wick-It\^{o}-Skorohod to solve problem of arbitrage in stochastic models (which yield inefficient mathematical stochastic models for financial market), some of conventional methods like quasi maximum likelihood , Separable Integral-Matching for Ordinary Differential Equations, and multivariate Brownian method are used to be compared with the suggested method. The suggested method has been proved to be very accurate. The estimated model used to calculate the portfolio of assets quantities allocation.en_US
dc.format.extent1353
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoen_US
dc.publisherSemnan Universityen_US
dc.relation.ispartofInternational Journal of Nonlinear Analysis and Applicationsen_US
dc.relation.isversionofhttps://dx.doi.org/10.22075/ijnaa.2022.5944
dc.subjectFractional Brownian motionen_US
dc.subjectStochastic Differential Equationsen_US
dc.subjectMaximum likelihooden_US
dc.subjectPrior distributionen_US
dc.subjectMetropolis Hasting methoden_US
dc.subjectHurst indexen_US
dc.subjectLangevin methoden_US
dc.titleBayesian inference of fractional brownian motion of multivariate stochastic differential equationsen_US
dc.typeTexten_US
dc.typeResearch Paperen_US
dc.contributor.departmentDepartment of Statistics, University of Baghdad, Iraqen_US
dc.contributor.departmentDepartment of Statistics, University of Baghdad, Iraqen_US
dc.citation.volume13
dc.citation.issue1
dc.citation.spage2425
dc.citation.epage2454


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