Probabilistic modeling of financial uncertainties

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dc.contributor.authorDaneshkhah, Alireza
dc.contributor.authorHosseinian-Far, Amin
dc.contributor.authorChatrabgoun, Omid
dc.contributor.authorSedighi, Tabassom
dc.contributor.authorFarsi, Maryam
dc.date.accessioned2018-11-01T17:54:24Z
dc.date.available2018-11-01T17:54:24Z
dc.date.issued2018-04-30
dc.description.abstractSince the global financial crash, one of the main trends in the financial engineering discipline has been to enhance the efficiency and flexibility of financial probabilistic risk assessments. Creditors could immensely benefit from such improvements in analysis hoping to minimise potential monetary losses. Analysis of real world financial scenarios require modeling of multiple uncertain quantities with a view to present more accurate, near future probabilistic predictions. Such predictions are essential for an informed decision making. In this article, the authors extend Bayesian Networks Pair-Copula Construction (BN-PCC) further using the minimum information vine model which results in a more flexible and efficient approach in modeling multivariate dependencies of heavy-tailed distribution and tail dependence as observed in the financial data. The authors demonstrate that the extended model based on minimum information Pair-Copula Construction (PCC) can approximate any non-Gaussian BN to any degree of approximation. The proposed method has been applied to the portfolio data derived from a Brazilian case study. The results show that the fitting of the multivariate distribution approximated using the proposed model has been improved compared to other previously published approaches.en_UK
dc.identifier.citationAlireza Daneshkhah, Amin Hosseinian-Far, Omid Chatrabgoun, et al., Probabilistic modeling of financial uncertainties. International Journal of Organizational and Collective Intelligence, Volume 8, Issue 2, Article number 1en_UK
dc.identifier.issn1947-9344
dc.identifier.urihttps//doi.org/10.4018/IJOCI.2018040101
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/13602
dc.language.isoenen_UK
dc.publisherIGI Globalen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectComplex Dependenciesen_UK
dc.subjectFinancial Modelingen_UK
dc.subjectHeavy-Tailed Densitiesen_UK
dc.subjectNon-Gaussian Bayesian Networken_UK
dc.subjectVine Copula Modelen_UK
dc.titleProbabilistic modeling of financial uncertaintiesen_UK
dc.typeArticleen_UK

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