Commodity predictability analysis with a permutation information theory approach

Autores
Zunino, Luciano José; Tabak, Benjamin M.; Serinaldi, Francesco; Zanin, Massimiliano; Pérez, Darío Gabriel; Rosso, Osvaldo Aníbal
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
It is widely known that commodity markets are not totally efficient. Long-range dependence is present, and thus the celebrated Brownian motion of prices can be considered only as a first approximation. In this work we analyzed the predictability in commodity markets by using a novel approach derived from Information Theory. The complexity-entropy causality plane has been recently shown to be a useful statistical tool to distinguish the stage of stock market development because differences between emergent and developed stock markets can be easily discriminated and visualized with this representation space [L. Zunino, M. Zanin, B.M. Tabak, D.G. Pérez, O.A. Rosso, Complexity-entropy causality plane: a useful approach to quantify the stock market inefficiency, Physica A 389 (2010) 1891-1901]. By estimating the permutation entropy and permutation statistical complexity of twenty basic commodity future markets over a period of around 20 years (1991.01.02-2009.09.01), we can define an associated ranking of efficiency. This ranking is quantifying the presence of patterns and hidden structures in these prime markets. Moreover, the temporal evolution of the commodities in the complexity-entropy causality plane allows us to identify periods of time where the underlying dynamics is more or less predictable.
Fil: Zunino, Luciano José. Consejo Superior de Investigaciones Científicas; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Departamento de Ciencias Básicas; Argentina
Fil: Tabak, Benjamin M.. Universidade Catolica de Brasilia; Brasil
Fil: Serinaldi, Francesco. Università degli Studi della Tuscia; Italia
Fil: Zanin, Massimiliano. Universidad Autónoma de Madrid; España
Fil: Pérez, Darío Gabriel. Pontificia Universidad Católica de Valparaíso; Chile
Fil: Rosso, Osvaldo Aníbal. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
COMMODITY EFFICIENCY
COMPLEXITY-ENTROPY CAUSALITY PLANE
PERMUTATION ENTROPY
PERMUTATION STATISTICAL COMPLEXITY
BANDT AND POMPE METHOD
ORDINAL TIME SERIES ANALYSIS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/236639
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/236639
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Commodity predictability analysis with a permutation information theory approachZunino, Luciano JoséTabak, Benjamin M.Serinaldi, FrancescoZanin, MassimilianoPérez, Darío GabrielRosso, Osvaldo AníbalCOMMODITY EFFICIENCYCOMPLEXITY-ENTROPY CAUSALITY PLANEPERMUTATION ENTROPYPERMUTATION STATISTICAL COMPLEXITYBANDT AND POMPE METHODORDINAL TIME SERIES ANALYSIShttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1It is widely known that commodity markets are not totally efficient. Long-range dependence is present, and thus the celebrated Brownian motion of prices can be considered only as a first approximation. In this work we analyzed the predictability in commodity markets by using a novel approach derived from Information Theory. The complexity-entropy causality plane has been recently shown to be a useful statistical tool to distinguish the stage of stock market development because differences between emergent and developed stock markets can be easily discriminated and visualized with this representation space [L. Zunino, M. Zanin, B.M. Tabak, D.G. Pérez, O.A. Rosso, Complexity-entropy causality plane: a useful approach to quantify the stock market inefficiency, Physica A 389 (2010) 1891-1901]. By estimating the permutation entropy and permutation statistical complexity of twenty basic commodity future markets over a period of around 20 years (1991.01.02-2009.09.01), we can define an associated ranking of efficiency. This ranking is quantifying the presence of patterns and hidden structures in these prime markets. Moreover, the temporal evolution of the commodities in the complexity-entropy causality plane allows us to identify periods of time where the underlying dynamics is more or less predictable.Fil: Zunino, Luciano José. Consejo Superior de Investigaciones Científicas; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Departamento de Ciencias Básicas; ArgentinaFil: Tabak, Benjamin M.. Universidade Catolica de Brasilia; BrasilFil: Serinaldi, Francesco. Università degli Studi della Tuscia; ItaliaFil: Zanin, Massimiliano. Universidad Autónoma de Madrid; EspañaFil: Pérez, Darío Gabriel. Pontificia Universidad Católica de Valparaíso; ChileFil: Rosso, Osvaldo Aníbal. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier Science2011-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/236639Zunino, Luciano José; Tabak, Benjamin M.; Serinaldi, Francesco; Zanin, Massimiliano ; Pérez, Darío Gabriel; et al.; Commodity predictability analysis with a permutation information theory approach; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 390; 5; 3-2011; 876-8900378-4371CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378437110009842info:eu-repo/semantics/altIdentifier/doi/10.1016/j.physa.2010.11.020info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-17T11:26:45Zoai:ri.conicet.gov.ar:11336/236639instacron: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:34982025-09-17 11:26:45.569CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Commodity predictability analysis with a permutation information theory approach
title Commodity predictability analysis with a permutation information theory approach
spellingShingle Commodity predictability analysis with a permutation information theory approach
Zunino, Luciano José
COMMODITY EFFICIENCY
COMPLEXITY-ENTROPY CAUSALITY PLANE
PERMUTATION ENTROPY
PERMUTATION STATISTICAL COMPLEXITY
BANDT AND POMPE METHOD
ORDINAL TIME SERIES ANALYSIS
title_short Commodity predictability analysis with a permutation information theory approach
title_full Commodity predictability analysis with a permutation information theory approach
title_fullStr Commodity predictability analysis with a permutation information theory approach
title_full_unstemmed Commodity predictability analysis with a permutation information theory approach
title_sort Commodity predictability analysis with a permutation information theory approach
dc.creator.none.fl_str_mv Zunino, Luciano José
Tabak, Benjamin M.
Serinaldi, Francesco
Zanin, Massimiliano
Pérez, Darío Gabriel
Rosso, Osvaldo Aníbal
author Zunino, Luciano José
author_facet Zunino, Luciano José
Tabak, Benjamin M.
Serinaldi, Francesco
Zanin, Massimiliano
Pérez, Darío Gabriel
Rosso, Osvaldo Aníbal
author_role author
author2 Tabak, Benjamin M.
Serinaldi, Francesco
Zanin, Massimiliano
Pérez, Darío Gabriel
Rosso, Osvaldo Aníbal
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv COMMODITY EFFICIENCY
COMPLEXITY-ENTROPY CAUSALITY PLANE
PERMUTATION ENTROPY
PERMUTATION STATISTICAL COMPLEXITY
BANDT AND POMPE METHOD
ORDINAL TIME SERIES ANALYSIS
topic COMMODITY EFFICIENCY
COMPLEXITY-ENTROPY CAUSALITY PLANE
PERMUTATION ENTROPY
PERMUTATION STATISTICAL COMPLEXITY
BANDT AND POMPE METHOD
ORDINAL TIME SERIES ANALYSIS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv It is widely known that commodity markets are not totally efficient. Long-range dependence is present, and thus the celebrated Brownian motion of prices can be considered only as a first approximation. In this work we analyzed the predictability in commodity markets by using a novel approach derived from Information Theory. The complexity-entropy causality plane has been recently shown to be a useful statistical tool to distinguish the stage of stock market development because differences between emergent and developed stock markets can be easily discriminated and visualized with this representation space [L. Zunino, M. Zanin, B.M. Tabak, D.G. Pérez, O.A. Rosso, Complexity-entropy causality plane: a useful approach to quantify the stock market inefficiency, Physica A 389 (2010) 1891-1901]. By estimating the permutation entropy and permutation statistical complexity of twenty basic commodity future markets over a period of around 20 years (1991.01.02-2009.09.01), we can define an associated ranking of efficiency. This ranking is quantifying the presence of patterns and hidden structures in these prime markets. Moreover, the temporal evolution of the commodities in the complexity-entropy causality plane allows us to identify periods of time where the underlying dynamics is more or less predictable.
Fil: Zunino, Luciano José. Consejo Superior de Investigaciones Científicas; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Departamento de Ciencias Básicas; Argentina
Fil: Tabak, Benjamin M.. Universidade Catolica de Brasilia; Brasil
Fil: Serinaldi, Francesco. Università degli Studi della Tuscia; Italia
Fil: Zanin, Massimiliano. Universidad Autónoma de Madrid; España
Fil: Pérez, Darío Gabriel. Pontificia Universidad Católica de Valparaíso; Chile
Fil: Rosso, Osvaldo Aníbal. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description It is widely known that commodity markets are not totally efficient. Long-range dependence is present, and thus the celebrated Brownian motion of prices can be considered only as a first approximation. In this work we analyzed the predictability in commodity markets by using a novel approach derived from Information Theory. The complexity-entropy causality plane has been recently shown to be a useful statistical tool to distinguish the stage of stock market development because differences between emergent and developed stock markets can be easily discriminated and visualized with this representation space [L. Zunino, M. Zanin, B.M. Tabak, D.G. Pérez, O.A. Rosso, Complexity-entropy causality plane: a useful approach to quantify the stock market inefficiency, Physica A 389 (2010) 1891-1901]. By estimating the permutation entropy and permutation statistical complexity of twenty basic commodity future markets over a period of around 20 years (1991.01.02-2009.09.01), we can define an associated ranking of efficiency. This ranking is quantifying the presence of patterns and hidden structures in these prime markets. Moreover, the temporal evolution of the commodities in the complexity-entropy causality plane allows us to identify periods of time where the underlying dynamics is more or less predictable.
publishDate 2011
dc.date.none.fl_str_mv 2011-03
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/11336/236639
Zunino, Luciano José; Tabak, Benjamin M.; Serinaldi, Francesco; Zanin, Massimiliano ; Pérez, Darío Gabriel; et al.; Commodity predictability analysis with a permutation information theory approach; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 390; 5; 3-2011; 876-890
0378-4371
CONICET Digital
CONICET
url http://hdl.handle.net/11336/236639
identifier_str_mv Zunino, Luciano José; Tabak, Benjamin M.; Serinaldi, Francesco; Zanin, Massimiliano ; Pérez, Darío Gabriel; et al.; Commodity predictability analysis with a permutation information theory approach; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 390; 5; 3-2011; 876-890
0378-4371
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378437110009842
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.physa.2010.11.020
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
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
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score 13.001348

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