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Correlation evidence in the dynamics of agricultural commodity prices

Author

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  • Raphael Homayoun Boroumand
  • Stéphane Goutte

    (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique)

  • Simon Porcher

    (IAE Paris - Sorbonne Business School)

  • Thomas Porcher

    (ESG Research Lab - ESG Management School)

Abstract

The article studies the correlation structures of a large panel of agricultural commodities prices between January 1990 and February 2014. We use a various collection of mathematical and statistical methodologies (estimated correlation matrix and principal component analysis) to capture these correlations. Our results show that there exist different degrees of correlation between commodities. We also demonstrate, through data mining analysis, that there are hidden correlations between some commodities. Indeed, some commodities' price behaviours are very similar in trend. Our results contribute to a better understanding of agricultural prices' behaviours by producers, investors and market intermediaries. The results contribute to a more efficient strategic asset allocation process within agricultural markets.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Raphael Homayoun Boroumand & Stéphane Goutte & Simon Porcher & Thomas Porcher, 2014. "Correlation evidence in the dynamics of agricultural commodity prices," Post-Print hal-02145832, HAL.
    • Handle: RePEc:hal:journl:hal-02145832
    DOI: 10.1080/13504851.2014.922742
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    Cited by:

    1. Dai, Yun-Shi & Huynh, Ngoc Quang Anh & Zheng, Qing-Huan & Zhou, Wei-Xing, 2022. "Correlation structure analysis of the global agricultural futures market," Research in International Business and Finance, Elsevier, vol. 61(C).

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