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

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 t...

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Autores principales:	Fernández Bariviera, Aurelio, Zunino, Luciano José, Guercio, María Belén, Martinez, Lisana Belén, Rosso, Osvaldo Anibal
Formato:	Articulo Preprint
Lenguaje:	Inglés
Publicado:	2013
Materias:	Matemática Corporate bonds Oil and energy sectors Market efficiency Complexity-entropy causality plane Permutation entropy Permutation complexity
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/98418 https://ri.conicet.gov.ar/11336/2007 http://arxiv.org/abs/1509.01839 http://iopscience.iop.org/article/10.1088/1742-5468/2013/08/P08007
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-98418
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Matemática Corporate bonds Oil and energy sectors Market efficiency Complexity-entropy causality plane Permutation entropy Permutation complexity
spellingShingle	Matemática Corporate bonds Oil and energy sectors Market efficiency Complexity-entropy causality plane Permutation entropy Permutation complexity Fernández Bariviera, Aurelio Zunino, Luciano José Guercio, María Belén Martinez, Lisana Belén Rosso, Osvaldo Anibal Efficiency and credit ratings: a permutation-information-theory analysis
topic_facet	Matemática Corporate bonds Oil and energy sectors Market efficiency Complexity-entropy causality plane Permutation entropy Permutation complexity
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.
format	Articulo Preprint
author	Fernández Bariviera, Aurelio Zunino, Luciano José Guercio, María Belén Martinez, Lisana Belén Rosso, Osvaldo Anibal
author_facet	Fernández Bariviera, Aurelio Zunino, Luciano José Guercio, María Belén Martinez, Lisana Belén Rosso, Osvaldo Anibal
author_sort	Fernández Bariviera, Aurelio
title	Efficiency and credit ratings: a permutation-information-theory analysis
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
publishDate	2013
url	http://sedici.unlp.edu.ar/handle/10915/98418 https://ri.conicet.gov.ar/11336/2007 http://arxiv.org/abs/1509.01839 http://iopscience.iop.org/article/10.1088/1742-5468/2013/08/P08007
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Efficiency and credit ratings: a permutation-information-theory analysis

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