IDEAS home Printed from https://ideas.repec.org/a/eme/jadeep/jadee-11-2022-0252.html
   My bibliography  Save this article

Multifractal cross-correlation analysis between crude oil and agricultural futures markets: evidence from Russia–Ukraine conflict

Author

Listed:
  • Luiz Eduardo Gaio
  • Daniel Henrique Dario Capitani

Abstract

Purpose - This study investigates the impacts of the Russia–Ukraine conflict on the cross-correlation between agricultural commodity prices and crude oil prices. Design/methodology/approach - The authors used MultiFractal Detrended Fluctuation Cross-Correlation Analysis (MF-X-DFA) to explore the correlation behavior before and during conflict. The authors analyzed the price connections between future prices for crude oil and agricultural commodities. Data consists of daily futures price returns for agricultural commodities (Corn, Soybean and Wheat) and Crude Oil (Brent) traded on the Chicago Mercantile Exchange from Aug 3, 2020, to July 29, 2022. Findings - The results suggest that cross-correlation behavior changed after the conflict. The multifractal behavior was observed in the cross correlations. The Russia–Ukraine conflict caused an increase in the series' fractal strength. The study findings showed that the correlations involving the wheat market were higher and anti-persistent behavior was observed. Research limitations/implications - The study was limited by the number of observations after the Russia–Ukraine conflict. Originality/value - This study contributes to the literature that investigates the impact of the Russia–Ukraine conflict on the financial market. As this is a recent event, as far as we know, we did not find another study that investigated cross-correlation in agricultural commodities using multifractal analysis.

Suggested Citation

  • Luiz Eduardo Gaio & Daniel Henrique Dario Capitani, 2023. "Multifractal cross-correlation analysis between crude oil and agricultural futures markets: evidence from Russia–Ukraine conflict," Journal of Agribusiness in Developing and Emerging Economies, Emerald Group Publishing Limited, vol. 15(1), pages 19-42, May.
    • Handle: RePEc:eme:jadeep:jadee-11-2022-0252
    DOI: 10.1108/JADEE-11-2022-0252
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/JADEE-11-2022-0252/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://www.emerald.com/insight/content/doi/10.1108/JADEE-11-2022-0252/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1108/JADEE-11-2022-0252?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Commodity markets; Agricultural; Russian–Ukraine conflict; Cross-correlation; Volatility; C10; C22; C49; G13; Q02; Q11;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

    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:eme:jadeep:jadee-11-2022-0252. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Emerald Support (email available below). General contact details of provider: .

    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.