IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/202068.html

Spillovers in Higher-Order Moments of Crude Oil, Gold, and Bitcoin

Author

Listed:
  • Konstantinos Gkillas

    (Department of Business Administration, University of Patras, Patras, Greece)

  • Elie Bouri

    (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • David Roubaud

    (Montpellier Business School, Montpellier, France)

Abstract

We extend existing studies by considering the higher-order moments relationships among crude oil, gold, and Bitcoin markets. Using high-frequency data from December 2, 2014 to June 10, 2018, we analyze spillovers in volatility jumps and realized second, third, and fourth moments among crude oil, gold, and Bitcoin markets via Granger causality and generalized impulse response analyses. Results suggest evidence of predictability and emphasize, among others, the need of jointly modeling linkages across those three markets with higher-order moments; otherwise, inaccurate risk assessment and investment inferences may arise. In fact, the responses of realized volatility shocks and volatility jump are generally positive. Further analyses indicate evidence of a weaker relationship between gold-crude oil, and Bitcoin-crude oil compared to the case of Bitcoin-gold. Practical implications are discussed.

Suggested Citation

  • Konstantinos Gkillas & Elie Bouri & Rangan Gupta & David Roubaud, 2020. "Spillovers in Higher-Order Moments of Crude Oil, Gold, and Bitcoin," Working Papers 202068, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202068
    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
    for a similarly titled item that would be available.

    Other versions of this item:

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    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:pre:wpaper:202068. 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: Rangan Gupta (email available below). General contact details of provider: https://edirc.repec.org/data/decupza.html .

    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.