IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02145832.html
   My bibliography  Save this paper

Correlation evidence in the dynamics of agricultural commodity prices

Author

Listed:
  • 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
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.
    2. Natanelov, Valeri & Alam, Mohammad J. & McKenzie, Andrew M. & Van Huylenbroeck, Guido, 2011. "Is there co-movement of agricultural commodities futures prices and crude oil?," Energy Policy, Elsevier, vol. 39(9), pages 4971-4984, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yun-Shi Dai & Ngoc Quang Anh Huynh & Qing-Huan Zheng & Wei-Xing Zhou, 2023. "Correlation structure analysis of the global agricultural futures market," Papers 2310.16849, arXiv.org.
    2. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohcine Bakhat & Klaas WŸrzburg, 2013. "Co-integration of Oil and Commodity Prices: A Comprehensive ApproachAbstract," Working Papers fa05-2013, Economics for Energy.
    2. Karakotsios, Achillefs & Katrakilidis, Constantinos & Kroupis, Nikolaos, 2021. "The dynamic linkages between food prices and oil prices. Does asymmetry matter?," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    3. Nowotarski, Jakub & Tomczyk, Jakub & Weron, Rafał, 2013. "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices," Energy Economics, Elsevier, vol. 39(C), pages 13-27.
    4. Natanelov, Valeri & McKenzie, Andrew M. & Van Huylenbroeck, Guido, 2013. "Crude oil–corn–ethanol – nexus: A contextual approach," Energy Policy, Elsevier, vol. 63(C), pages 504-513.
    5. Matteo Manera & Marcella Nicolini & Ilaria Vignati, 2012. "Returns in commodities futures markets and financial speculation: a multivariate GARCH approach," Quaderni di Dipartimento 170, University of Pavia, Department of Economics and Quantitative Methods.
    6. Samuel Asante Gyamerah & Philip Ngare & Dennis Ikpe, 2018. "Regime-Switching Temperature Dynamics Model for Weather Derivatives," International Journal of Stochastic Analysis, Hindawi, vol. 2018, pages 1-15, July.
    7. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    8. Ordu, Beyza Mina & Oran, Adil & Soytas, Ugur, 2018. "Is food financialized? Yes, but only when liquidity is abundant," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 82-96.
    9. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    10. Andreas Gerster, 2016. "Negative price spikes at power markets: the role of energy policy," Journal of Regulatory Economics, Springer, vol. 50(3), pages 271-289, December.
    11. Asche, Frank & Oglend, Atle, 2016. "The relationship between input-factor and output prices in commodity industries: The case of Norwegian salmon aquaculture," Journal of Commodity Markets, Elsevier, vol. 1(1), pages 35-47.
    12. Gbadebo Oladosu & Siwa Msangi, 2013. "Biofuel-Food Market Interactions: A Review of Modeling Approaches and Findings," Agriculture, MDPI, vol. 3(1), pages 1-19, February.
    13. Zachmann, Georg, 2013. "A stochastic fuel switching model for electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 5-13.
    14. Carl-Henrik Dahlqvist, 2018. "Cross-country information transmissions and the role of commodity markets: A multichannel Markov switching approach," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-22, August.
    15. Cai, Guixin & Zhang, Hao & Chen, Ziyue, 2019. "Comovement between commodity sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1247-1258.
    16. Fasanya, Ismail & Akinbowale, Seun, 2019. "Modelling the return and volatility spillovers of crude oil and food prices in Nigeria," Energy, Elsevier, vol. 169(C), pages 186-205.
    17. Shadi Tehrani & Jesús Juan & Eduardo Caro, 2022. "Electricity Spot Price Modeling and Forecasting in European Markets," Energies, MDPI, vol. 15(16), pages 1-23, August.
    18. Bartosz Uniejewski & Rafal Weron & Florian Ziel, 2017. "Variance stabilizing transformations for electricity spot price forecasting," HSC Research Reports HSC/17/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    19. Ángel López-Oriona & José A. Vilar, 2021. "F4: An All-Purpose Tool for Multivariate Time Series Classification," Mathematics, MDPI, vol. 9(23), pages 1-26, November.
    20. Jingye Li, 2021. "The Effect of Oil Price on China’s Grain Prices: a VAR model," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(1), pages 1-5.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-02145832. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.