TY - JOUR

T1 - Commodity predictability analysis with a permutation information theory approach

AU - Zunino, Luciano

AU - Tabak, Benjamin M.

AU - Serinaldi, Francesco

AU - Zanin, Massimiliano

AU - Pérez, Darío G.

AU - Rosso, Osvaldo A.

N1 - Funding Information:
The authors would like to thank C.G. Turvey (Cornell University, US) and three anonymous reviewers for their useful comments and suggestions. Luciano Zunino and Osvaldo A. Rosso were supported by Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina. Benjamin M. Tabak gratefully acknowledges financial support from CNPq foundation . The opinions expressed in the paper do not necessarily reflect those of the Banco Central do Brasil. Darío G. Pérez was supported by Comisión Nacional de Investigación Científica y Tecnológica (CONICYT, FONDECYT project No. 1100753), Chile, and partially by Pontificia Universidad Católica de Valparaíso (PUCV, Project No. 123.704/2010), Chile. Osvaldo A. Rosso is PVE fellowship, CAPES, Brazil.

PY - 2011/3/1

Y1 - 2011/3/1

N2 - 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.

AB - 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.

KW - Bandt and Pompe method

KW - Commodity efficiency

KW - Complexityentropy causality plane

KW - Ordinal time series analysis

KW - Permutation entropy

KW - Permutation statistical complexity

UR - http://www.scopus.com/inward/record.url?scp=78650932289&partnerID=8YFLogxK

U2 - 10.1016/j.physa.2010.11.020

DO - 10.1016/j.physa.2010.11.020

M3 - Article

AN - SCOPUS:78650932289

SN - 0378-4371

VL - 390

SP - 876

EP - 890

JO - Physica A: Statistical Mechanics and its Applications

JF - Physica A: Statistical Mechanics and its Applications

IS - 5

ER -