Probabilistic modeling of financial uncertainties

Daneshkhah, A., Hosseinian-Far, A., Chatrabgoun, O., Sedighi, T. and Farsi, M. (2018) Probabilistic modeling of financial uncertainties. International Journal of Organizational and Collective Intelligence (IJOCI). 8(2), pp. 1-11. 1947-9344.

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Item Type:	Article
Abstract:	Since 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 paper, we 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. We demonstrate that the extended model based on minimum information Pair-Copula Construction (PCC) can approximate any non-Gaussian BN to any degree of approximation. Our 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.
Uncontrolled Keywords:	Complex dependencies, financial modeling, heavy-tailed densities, NonGaussian Bayesian Network, Vine Copula Model
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD72 Economic growth, development, planning
Creators:	Daneshkhah, Alireza, Hosseinian-Far, Amin, Chatrabgoun, Omid, Sedighi, Tabassom and Farsi, Maryam
Publisher:	IGI Global
Faculties, Divisions and Institutes:	University Faculties, Divisions and Research Centres - OLD > Faculty of Business & Law > Business Faculties > Faculty of Business & Law > International Strategy & Business
Date:	1 April 2018
Date Type:	Publication
Page Range:	pp. 1-11
Journal or Publication Title:	International Journal of Organizational and Collective Intelligence (IJOCI)
Volume:	8
Number:	2
Language:	English
DOI:	https://doi.org/10.4018/IJOCI.2018040101
ISSN:	1947-9344
Status:	Published / Disseminated
Refereed:	Yes
Related URLs:	Publisher
URI:	http://nectar.northampton.ac.uk/id/eprint/10297

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