Financial Dependence Analysis: Applications of Vine Copulae

This paper features the application of a novel and recently developed method of statistical and mathematical analysis to the assessment of financial risk: namely Regular Vine copulas. Dependence modeling using copulas is a popular tool in financial applications, but is usually applied to pairs of se...

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Detalles Bibliográficos
Autores: Allen, David E., Ashraf, Mohammad.A., McAleer, Michael, Powell, Robert J., Singh, Abhay K.
Tipo de recurso: informe técnico
Fecha de publicación:2013
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/41450
Acceso en línea:https://hdl.handle.net/20.500.14352/41450
Access Level:acceso abierto
Palabra clave:C02
G11
Regular Vine Copulas
Tree structures
Co-dependence modelling
Finanzas
Econometría (Economía)
5302 Econometría
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spelling Financial Dependence Analysis: Applications of Vine CopulaeAllen, David E.Ashraf, Mohammad.A.McAleer, MichaelPowell, Robert J.Singh, Abhay K.C02G11Regular Vine CopulasTree structuresCo-dependence modellingFinanzasEconometría (Economía)5302 EconometríaThis paper features the application of a novel and recently developed method of statistical and mathematical analysis to the assessment of financial risk: namely Regular Vine copulas. Dependence modeling using copulas is a popular tool in financial applications, but is usually applied to pairs of securities. Vine copulas offer greater flexibility and permit the modelling of complex dependency patterns using the rich variety of bivariate copulas which can be arranged and analysed in a tree structure to facilitate the analysis of multiple dependencies. We apply Regular Vine copula analysis to a sample of stocks comprising the Dow Jones Index to assess their interdependencies and to assess how their correlations change in different economic circumstances using three different sample periods: pre-GFC (Jan 2005- July 2007), GFC (July 2007-Sep 2009), and post-GFC periods (Sep 2009 - Dec 2011). The empirical results suggest that the dependencies change in a complex manner, and there is evidence of greater reliance on the Student t copula in the copula choice within the tree structures for the GFC period, which is consistent with the existence of larger tails in the distributions of returns for this period. One of the attractions of this approach to risk modelling is the flexibility in the choice of distributions used to model co-dependencies.Universidad Complutense de Madrid20132013-01-0120132013-01-01technical reporthttp://purl.org/coar/resource_type/c_18ghinfo:eu-repo/semantics/reportapplication/pdfhttps://hdl.handle.net/20.500.14352/41450reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Atribución-NoComercial 3.0 Españahttps://creativecommons.org/licenses/by-nc/3.0/es/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/414502026-06-02T12:44:21Z
dc.title.none.fl_str_mv Financial Dependence Analysis: Applications of Vine Copulae
title Financial Dependence Analysis: Applications of Vine Copulae
spellingShingle Financial Dependence Analysis: Applications of Vine Copulae
Allen, David E.
C02
G11
Regular Vine Copulas
Tree structures
Co-dependence modelling
Finanzas
Econometría (Economía)
5302 Econometría
title_short Financial Dependence Analysis: Applications of Vine Copulae
title_full Financial Dependence Analysis: Applications of Vine Copulae
title_fullStr Financial Dependence Analysis: Applications of Vine Copulae
title_full_unstemmed Financial Dependence Analysis: Applications of Vine Copulae
title_sort Financial Dependence Analysis: Applications of Vine Copulae
dc.creator.none.fl_str_mv Allen, David E.
Ashraf, Mohammad.A.
McAleer, Michael
Powell, Robert J.
Singh, Abhay K.
author Allen, David E.
author_facet Allen, David E.
Ashraf, Mohammad.A.
McAleer, Michael
Powell, Robert J.
Singh, Abhay K.
author_role author
author2 Ashraf, Mohammad.A.
McAleer, Michael
Powell, Robert J.
Singh, Abhay K.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv C02
G11
Regular Vine Copulas
Tree structures
Co-dependence modelling
Finanzas
Econometría (Economía)
5302 Econometría
topic C02
G11
Regular Vine Copulas
Tree structures
Co-dependence modelling
Finanzas
Econometría (Economía)
5302 Econometría
description This paper features the application of a novel and recently developed method of statistical and mathematical analysis to the assessment of financial risk: namely Regular Vine copulas. Dependence modeling using copulas is a popular tool in financial applications, but is usually applied to pairs of securities. Vine copulas offer greater flexibility and permit the modelling of complex dependency patterns using the rich variety of bivariate copulas which can be arranged and analysed in a tree structure to facilitate the analysis of multiple dependencies. We apply Regular Vine copula analysis to a sample of stocks comprising the Dow Jones Index to assess their interdependencies and to assess how their correlations change in different economic circumstances using three different sample periods: pre-GFC (Jan 2005- July 2007), GFC (July 2007-Sep 2009), and post-GFC periods (Sep 2009 - Dec 2011). The empirical results suggest that the dependencies change in a complex manner, and there is evidence of greater reliance on the Student t copula in the copula choice within the tree structures for the GFC period, which is consistent with the existence of larger tails in the distributions of returns for this period. One of the attractions of this approach to risk modelling is the flexibility in the choice of distributions used to model co-dependencies.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01
2013
2013-01-01
dc.type.none.fl_str_mv technical report
http://purl.org/coar/resource_type/c_18gh
dc.type.openaire.fl_str_mv info:eu-repo/semantics/report
format report
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/41450
url https://hdl.handle.net/20.500.14352/41450
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial 3.0 España
https://creativecommons.org/licenses/by-nc/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial 3.0 España
https://creativecommons.org/licenses/by-nc/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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