Efficiency and credit ratings: A permutation-information-theory analysis

Autores
Fernández Bariviera, Aurelio; Zunino, Luciano José; Guercio, María Belén; Martinez, Lisana Belén; Rosso, Osvaldo Anibal
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The role of credit rating agencies has been under severe scrutiny after the subprime crisis. In this paper we explore the relationship between credit ratings and informational efficiency of a sample of thirty nine corporate bonds of US oil and energy companies from April 2008 to November 2012. For this purpose we use a powerful statistical tool, relatively new in the financial literature: the complexity–entropy causality plane. This representation space allows us to graphically classify the different bonds according to their degree of informational efficiency. We find that this classification agrees with the credit ratings assigned by Moody's. In particular, we detect the formation of two clusters, which correspond to the global categories of investment and speculative grades. Regarding the latter cluster, two subgroups reflect distinct levels of efficiency. Additionally, we also find an intriguing absence of correlation between informational efficiency and firm characteristics. This allows us to conclude that the proposed permutation-information-theory approach provides an alternative practical way to justify bond classification.
Fil: Fernández Bariviera, Aurelio. Universitat Rovira I Virgili; España; . Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Computación. Laboratorio de Sistemas Complejos; Argentina
Fil: Zunino, Luciano José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - La Plata. Centro de Investigaciones Opticas (i); Argentina. Universidad Nacional de la Plata. Facultad de Ingeniería. Departamento de Ciencias Básicas; Argentina
Fil: Guercio, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Bahia Blanca. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Universidad Nacional del Sur; Argentina
Fil: Martinez, Lisana Belén. Universitat Rovira I Virgili; España; . Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Bahia Blanca. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
Fil: Rosso, Osvaldo Anibal. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Computación. Laboratorio de Sistemas Complejos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Bahia Blanca; Argentina. Universidade Federal de Alagoas; Brasil;
Materia
MODELS OF FINANCIAL MARKETS
NONLINEAR DYNAMICS
RISK MEASURE AND MANAGEMENT
STOCHASTIC PROCESSES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/2007
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/2007
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Efficiency and credit ratings: A permutation-information-theory analysisFernández Bariviera, AurelioZunino, Luciano JoséGuercio, María BelénMartinez, Lisana BelénRosso, Osvaldo AnibalMODELS OF FINANCIAL MARKETSNONLINEAR DYNAMICSRISK MEASURE AND MANAGEMENTSTOCHASTIC PROCESSEShttps://purl.org/becyt/ford/5.2https://purl.org/becyt/ford/5The role of credit rating agencies has been under severe scrutiny after the subprime crisis. In this paper we explore the relationship between credit ratings and informational efficiency of a sample of thirty nine corporate bonds of US oil and energy companies from April 2008 to November 2012. For this purpose we use a powerful statistical tool, relatively new in the financial literature: the complexity–entropy causality plane. This representation space allows us to graphically classify the different bonds according to their degree of informational efficiency. We find that this classification agrees with the credit ratings assigned by Moody's. In particular, we detect the formation of two clusters, which correspond to the global categories of investment and speculative grades. Regarding the latter cluster, two subgroups reflect distinct levels of efficiency. Additionally, we also find an intriguing absence of correlation between informational efficiency and firm characteristics. This allows us to conclude that the proposed permutation-information-theory approach provides an alternative practical way to justify bond classification.Fil: Fernández Bariviera, Aurelio. Universitat Rovira I Virgili; España; . Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Computación. Laboratorio de Sistemas Complejos; ArgentinaFil: Zunino, Luciano José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - La Plata. Centro de Investigaciones Opticas (i); Argentina. Universidad Nacional de la Plata. Facultad de Ingeniería. Departamento de Ciencias Básicas; ArgentinaFil: Guercio, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Bahia Blanca. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Universidad Nacional del Sur; ArgentinaFil: Martinez, Lisana Belén. Universitat Rovira I Virgili; España; . Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Bahia Blanca. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaFil: Rosso, Osvaldo Anibal. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Computación. Laboratorio de Sistemas Complejos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Bahia Blanca; Argentina. Universidade Federal de Alagoas; Brasil;IOP Publishing2013-08-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/2007Fernández Bariviera, Aurelio; Zunino, Luciano José; Guercio, María Belén; Martinez, Lisana Belén; Rosso, Osvaldo Anibal; Efficiency and credit ratings: A permutation-information-theory analysis; IOP Publishing; Journal of Statistical Mechanics: Theory and Experiment; 2013; 8; 21-8-2013; 1-231742-5468enginfo:eu-repo/semantics/altIdentifier/doi/10.1088/1742-5468/2013/08/P08007info:eu-repo/semantics/altIdentifier/url/http://arxiv.org/abs/1509.01839info:eu-repo/semantics/altIdentifier/url/http://iopscience.iop.org/article/10.1088/1742-5468/2013/08/P08007info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:14:53Zoai:ri.conicet.gov.ar:11336/2007instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:14:53.854CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Efficiency and credit ratings: A permutation-information-theory analysis
title Efficiency and credit ratings: A permutation-information-theory analysis
spellingShingle Efficiency and credit ratings: A permutation-information-theory analysis
Fernández Bariviera, Aurelio
MODELS OF FINANCIAL MARKETS
NONLINEAR DYNAMICS
RISK MEASURE AND MANAGEMENT
STOCHASTIC PROCESSES
title_short Efficiency and credit ratings: A permutation-information-theory analysis
title_full Efficiency and credit ratings: A permutation-information-theory analysis
title_fullStr Efficiency and credit ratings: A permutation-information-theory analysis
title_full_unstemmed Efficiency and credit ratings: A permutation-information-theory analysis
title_sort Efficiency and credit ratings: A permutation-information-theory analysis
dc.creator.none.fl_str_mv Fernández Bariviera, Aurelio
Zunino, Luciano José
Guercio, María Belén
Martinez, Lisana Belén
Rosso, Osvaldo Anibal
author Fernández Bariviera, Aurelio
author_facet Fernández Bariviera, Aurelio
Zunino, Luciano José
Guercio, María Belén
Martinez, Lisana Belén
Rosso, Osvaldo Anibal
author_role author
author2 Zunino, Luciano José
Guercio, María Belén
Martinez, Lisana Belén
Rosso, Osvaldo Anibal
author2_role author
author
author
author
dc.subject.none.fl_str_mv MODELS OF FINANCIAL MARKETS
NONLINEAR DYNAMICS
RISK MEASURE AND MANAGEMENT
STOCHASTIC PROCESSES
topic MODELS OF FINANCIAL MARKETS
NONLINEAR DYNAMICS
RISK MEASURE AND MANAGEMENT
STOCHASTIC PROCESSES
purl_subject.fl_str_mv https://purl.org/becyt/ford/5.2
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv The role of credit rating agencies has been under severe scrutiny after the subprime crisis. In this paper we explore the relationship between credit ratings and informational efficiency of a sample of thirty nine corporate bonds of US oil and energy companies from April 2008 to November 2012. For this purpose we use a powerful statistical tool, relatively new in the financial literature: the complexity–entropy causality plane. This representation space allows us to graphically classify the different bonds according to their degree of informational efficiency. We find that this classification agrees with the credit ratings assigned by Moody's. In particular, we detect the formation of two clusters, which correspond to the global categories of investment and speculative grades. Regarding the latter cluster, two subgroups reflect distinct levels of efficiency. Additionally, we also find an intriguing absence of correlation between informational efficiency and firm characteristics. This allows us to conclude that the proposed permutation-information-theory approach provides an alternative practical way to justify bond classification.
Fil: Fernández Bariviera, Aurelio. Universitat Rovira I Virgili; España; . Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Computación. Laboratorio de Sistemas Complejos; Argentina
Fil: Zunino, Luciano José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - La Plata. Centro de Investigaciones Opticas (i); Argentina. Universidad Nacional de la Plata. Facultad de Ingeniería. Departamento de Ciencias Básicas; Argentina
Fil: Guercio, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Bahia Blanca. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Universidad Nacional del Sur; Argentina
Fil: Martinez, Lisana Belén. Universitat Rovira I Virgili; España; . Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Bahia Blanca. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
Fil: Rosso, Osvaldo Anibal. Universidad de Buenos Aires. Facultad de Ingeniería. Departamento de Computación. Laboratorio de Sistemas Complejos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Bahia Blanca; Argentina. Universidade Federal de Alagoas; Brasil;
description The role of credit rating agencies has been under severe scrutiny after the subprime crisis. In this paper we explore the relationship between credit ratings and informational efficiency of a sample of thirty nine corporate bonds of US oil and energy companies from April 2008 to November 2012. For this purpose we use a powerful statistical tool, relatively new in the financial literature: the complexity–entropy causality plane. This representation space allows us to graphically classify the different bonds according to their degree of informational efficiency. We find that this classification agrees with the credit ratings assigned by Moody's. In particular, we detect the formation of two clusters, which correspond to the global categories of investment and speculative grades. Regarding the latter cluster, two subgroups reflect distinct levels of efficiency. Additionally, we also find an intriguing absence of correlation between informational efficiency and firm characteristics. This allows us to conclude that the proposed permutation-information-theory approach provides an alternative practical way to justify bond classification.
publishDate 2013
dc.date.none.fl_str_mv 2013-08-21
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/2007
Fernández Bariviera, Aurelio; Zunino, Luciano José; Guercio, María Belén; Martinez, Lisana Belén; Rosso, Osvaldo Anibal; Efficiency and credit ratings: A permutation-information-theory analysis; IOP Publishing; Journal of Statistical Mechanics: Theory and Experiment; 2013; 8; 21-8-2013; 1-23
1742-5468
url http://hdl.handle.net/11336/2007
identifier_str_mv Fernández Bariviera, Aurelio; Zunino, Luciano José; Guercio, María Belén; Martinez, Lisana Belén; Rosso, Osvaldo Anibal; Efficiency and credit ratings: A permutation-information-theory analysis; IOP Publishing; Journal of Statistical Mechanics: Theory and Experiment; 2013; 8; 21-8-2013; 1-23
1742-5468
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1088/1742-5468/2013/08/P08007
info:eu-repo/semantics/altIdentifier/url/http://arxiv.org/abs/1509.01839
info:eu-repo/semantics/altIdentifier/url/http://iopscience.iop.org/article/10.1088/1742-5468/2013/08/P08007
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv IOP Publishing
publisher.none.fl_str_mv IOP Publishing
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846083296464732160
score 13.22299

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