Commodity predictability analysis with a permutation information theory approach

Luciano Zunino, Benjamin M. Tabak, Francesco Serinaldi, Massimiliano Zanin, DARIO GABRIEL PEREZ , Osvaldo A. Rosso

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

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 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.

Original languageEnglish
Pages (from-to)876-890
Number of pages15
JournalPhysica A: Statistical Mechanics and its Applications
Volume390
Issue number5
DOIs
StatePublished - 1 Mar 2011

Keywords

  • Bandt and Pompe method
  • Commodity efficiency
  • Complexityentropy causality plane
  • Ordinal time series analysis
  • Permutation entropy
  • Permutation statistical complexity

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