Mostrar el registro sencillo del ítem

dc.contributor.author
Zunino, Luciano José  
dc.contributor.author
Tabak, Benjamin M.  
dc.contributor.author
Serinaldi, Francesco  
dc.contributor.author
Zanin, Massimiliano  
dc.contributor.author
Pérez, Darío Gabriel  
dc.contributor.author
Rosso, Osvaldo Aníbal  
dc.date.available
2024-05-31T10:48:11Z  
dc.date.issued
2011-03  
dc.identifier.citation
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  
dc.identifier.issn
0378-4371  
dc.identifier.uri
http://hdl.handle.net/11336/236639  
dc.description.abstract
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.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier Science  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
COMMODITY EFFICIENCY  
dc.subject
COMPLEXITY-ENTROPY CAUSALITY PLANE  
dc.subject
PERMUTATION ENTROPY  
dc.subject
PERMUTATION STATISTICAL COMPLEXITY  
dc.subject
BANDT AND POMPE METHOD  
dc.subject
ORDINAL TIME SERIES ANALYSIS  
dc.subject.classification
Otras Ciencias Físicas  
dc.subject.classification
Ciencias Físicas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Commodity predictability analysis with a permutation information theory approach  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2024-05-31T10:00:00Z  
dc.journal.volume
390  
dc.journal.number
5  
dc.journal.pagination
876-890  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
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  
dc.description.fil
Fil: Tabak, Benjamin M.. Universidade Catolica de Brasilia; Brasil  
dc.description.fil
Fil: Serinaldi, Francesco. Università degli Studi della Tuscia; Italia  
dc.description.fil
Fil: Zanin, Massimiliano. Universidad Autónoma de Madrid; España  
dc.description.fil
Fil: Pérez, Darío Gabriel. Pontificia Universidad Católica de Valparaíso; Chile  
dc.description.fil
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  
dc.journal.title
Physica A: Statistical Mechanics and its Applications  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0378437110009842  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.physa.2010.11.020