Commodity predictability analysis with a permutation information theory approach
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...
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2011
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v390_n5_p876_Zunino http://hdl.handle.net/20.500.12110/paper_03784371_v390_n5_p876_Zunino |
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paper:paper_03784371_v390_n5_p876_Zunino2023-06-08T15:40:14Z Commodity predictability analysis with a permutation information theory approach Bandt and Pompe method Commodity efficiency Complexityentropy causality plane Ordinal time series analysis Permutation entropy Permutation statistical complexity Bandt and Pompe method Commodity efficiency Complexityentropy causality plane Ordinal time series analysis Permutation entropy Statistical complexity Brownian movement Commerce Entropy Finance Information theory Statistical mechanics Time series Time series analysis 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 complexityentropy 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. Prez, O.A. Rosso, Complexityentropy causality plane: a useful approach to quantify the stock market inefficiency, Physica A 389 (2010) 18911901]. By estimating the permutation entropy and permutation statistical complexity of twenty basic commodity future markets over a period of around 20 years (1991.01.022009.09.01), 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 complexityentropy causality plane allows us to identify periods of time where the underlying dynamics is more or less predictable. © 2010 Elsevier B.V. All rights reserved. 2011 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v390_n5_p876_Zunino http://hdl.handle.net/20.500.12110/paper_03784371_v390_n5_p876_Zunino |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Bandt and Pompe method Commodity efficiency Complexityentropy causality plane Ordinal time series analysis Permutation entropy Permutation statistical complexity Bandt and Pompe method Commodity efficiency Complexityentropy causality plane Ordinal time series analysis Permutation entropy Statistical complexity Brownian movement Commerce Entropy Finance Information theory Statistical mechanics Time series Time series analysis |
| spellingShingle |
Bandt and Pompe method Commodity efficiency Complexityentropy causality plane Ordinal time series analysis Permutation entropy Permutation statistical complexity Bandt and Pompe method Commodity efficiency Complexityentropy causality plane Ordinal time series analysis Permutation entropy Statistical complexity Brownian movement Commerce Entropy Finance Information theory Statistical mechanics Time series Time series analysis Commodity predictability analysis with a permutation information theory approach |
| topic_facet |
Bandt and Pompe method Commodity efficiency Complexityentropy causality plane Ordinal time series analysis Permutation entropy Permutation statistical complexity Bandt and Pompe method Commodity efficiency Complexityentropy causality plane Ordinal time series analysis Permutation entropy Statistical complexity Brownian movement Commerce Entropy Finance Information theory Statistical mechanics Time series Time series analysis |
| 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 complexityentropy 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. Prez, O.A. Rosso, Complexityentropy causality plane: a useful approach to quantify the stock market inefficiency, Physica A 389 (2010) 18911901]. By estimating the permutation entropy and permutation statistical complexity of twenty basic commodity future markets over a period of around 20 years (1991.01.022009.09.01), 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 complexityentropy causality plane allows us to identify periods of time where the underlying dynamics is more or less predictable. © 2010 Elsevier B.V. All rights reserved. |
| title |
Commodity predictability analysis with a permutation information theory approach |
| 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 |
| publishDate |
2011 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v390_n5_p876_Zunino http://hdl.handle.net/20.500.12110/paper_03784371_v390_n5_p876_Zunino |
| _version_ |
1768543279603777536 |