IDEAS home Printed from https://ideas.repec.org/h/eme/csefzz/s1569-375920200000104005.html
   My bibliography  Save this book chapter

Volatility spillover from oil prices to precious metals under different regimes

In: Contemporary Issues in Business Economics and Finance

Author

Listed:
  • Ayşegül Kirkpınar

Abstract

Introduction– Increases in prices of commodity markets may be associated with increased volatility in financial markets. That is why analysing time-varying co-movements of commodity prices can be of great importance for investors who take into consideration optimal asset allocation. Purpose– The aim of this study is to investigate the volatility spillover from oil to precious metals under high-volatility and low-volatility regimes. Methodology –The data covered daily closing prices of assets such as oil, palladium, and platinum for the period January 2010–December 2018. GARCH models were analysed in order to determine the most appropriate volatility structure, and it was determined that GARCH (1,1) model was the most suitable model for all commodities. Markov Switching model was used to analyse the volatility spillover from oil to precious metals. Findings– According to the analyses, the results showed that there were volatility spillovers from oil to palladium and platinum in low-volatility regimes and from oil to platinum in high-volatility regimes. On the other hand, there was no volatility spillover from oil to palladium in high-volatility regimes. Investing into oil and palladium in the same portfolio can provide diversification benefits for investors in high-volatility regimes. On the other hand, investing into oil and palladium in the same portfolio may not provide diversification benefits for investors in low-volatility regimes. The findings of the analyses can be beneficial for investors, market participants, and portfolio managers to make an accurate portfolio management.

Suggested Citation

  • Ayşegül Kirkpınar, 2020. "Volatility spillover from oil prices to precious metals under different regimes," Contemporary Studies in Economic and Financial Analysis, in: Contemporary Issues in Business Economics and Finance, volume 104, pages 45-56, Emerald Group Publishing Limited.
  • Handle: RePEc:eme:csefzz:s1569-375920200000104005
    DOI: 10.1108/S1569-375920200000104005
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/S1569-375920200000104005/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/S1569-375920200000104005/full/epub?utm_source=repec&utm_medium=feed&utm_campaign=repec&title=10.1108/S1569-375920200000104005
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://www.emerald.com/insight/content/doi/10.1108/S1569-375920200000104005/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/S1569-375920200000104005?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

    Volatility spillover; Markov switching model; commodity markets; precious metals; oil; portfolio management; G11; G15; C22;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:csefzz:s1569-375920200000104005. 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.