Modeling right-skewed financial data stream : a likelihood inference based on the generalized Birnbaum–Saunders mixture model

dc.contributor.authorNaderi, Mehrdad
dc.contributor.authorHashemi, Farzane
dc.contributor.authorBekker, Andriette, 1958-
dc.contributor.authorJamalizadeh, Ahad
dc.contributor.emailm.naderi@up.ac.zaen_ZA
dc.date.accessioned2020-10-29T07:01:47Z
dc.date.available2020-10-29T07:01:47Z
dc.date.issued2020-07
dc.description.abstractFinite mixture models have recently been considered for analyzing positive support economical data streams with non-normal features. In this paper, a new mixture model based on the novel class of generalized Birnbaum–Saunders distributions is proposed to enhance strength and flexibility in modeling heterogeneous lifetime data. Some characteristics and properties of this mixture model are outlined. By presenting a convenient hierarchical representation, a mathematically elegant and computationally tractable EM-type algorithm is adopted for computing maximum likelihood estimates. Theoretical formulae of well-known risk measures referring to the class of generalized Birnbaum–Saunders distributions are derived. Finally, the utility of the postulated methodology is illustrated with some real-world data examples.en_ZA
dc.description.departmentStatisticsen_ZA
dc.description.librarianhj2020en_ZA
dc.description.sponsorshipThe National Research Foundation, South Africaen_ZA
dc.description.urihttp://www.elsevier.com/ locate/amcen_ZA
dc.identifier.citationNaderi, M., Hashemi, F., Bekker, A. et al. 2020, 'Modeling right-skewed financial data stream : a likelihood inference based on the generalized Birnbaum–Saunders mixture model', Applied Mathematics and Computation, vol. 376, art. 125109, pp. 1-16.en_ZA
dc.identifier.issn0096-3003 (print)
dc.identifier.issn1873-5649 (online)
dc.identifier.other10.1016/j.amc.2020.125109
dc.identifier.urihttp://hdl.handle.net/2263/76650
dc.language.isoenen_ZA
dc.publisherElsevieren_ZA
dc.rights© 2020 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Applied Mathematics and Computation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Applied Mathematics and Computation, vol. 376, art. 125109, pp. 1-16, 2020. doi : 10.1016/j.amc.2020.125109.en_ZA
dc.subjectBirnbaum–Saunders distributionen_ZA
dc.subjectFinite mixture modelen_ZA
dc.subjectNormal mean-variance modelen_ZA
dc.subjectRisk measurementen_ZA
dc.subjectTail-value-at-Risk (TVaR)en_ZA
dc.subjectValue-at-risk (VaR)en_ZA
dc.titleModeling right-skewed financial data stream : a likelihood inference based on the generalized Birnbaum–Saunders mixture modelen_ZA
dc.typePreprint Articleen_ZA

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