IDEAS home Printed from https://ideas.repec.org/h/spr/lnopch/978-3-031-68974-1_6.html
   My bibliography  Save this book chapter

Forecasting Realised Volatility: Implied and GARCH Volatility in Bitcoin, Gold, Oil Markets

Author

Listed:
  • Toshiko Matsui

    (Imperial College)

  • William J. Knottenbelt

    (Imperial College)

Abstract

This paper investigates the predictive accuracy of implied and GARCH volatility models for bitcoin, gold and oil to determine whether (i) implied volatility is a reliable proxy for investors and (ii) bitcoin behaves differently from other commodities in terms of its volatility behaviour. Data analysis from January 2019 to December 2023 reveals that implied volatility underperforms GARCH (1,1) in all assets in terms of predictive accuracy. The difference between the estimated errors given by the implied volatility and by GARCH (1, 1) is the lowest in gold, showing that implied volatility predictions are more suitable in less volatile markets. The results are consistent with the yearly split sample data—aside from the additional fact that in times of turmoil, the predictive accuracy of both volatility models deteriorates significantly. The results further suggest that after a financial crisis, the predictive accuracy of the implied volatility falls while that of GARCH (1, 1) rises, particularly in the bitcoin market. Further analysis confirms that implied volatility (followed by GARCH volatility) is generally higher than realised volatility in all the three assets, except when the market is extremely volatile, which is consistent with previous findings for other assets. Taken together, these results can support investors in two key aspects. The first is that despite being widely used by investors, implied volatility is not the most accurate proxy available particularly when applied in volatile market conditions. The second is that implied volatility exhibits a further diminished level of predictive accuracy post financial crisis, specifically in bitcoin market.

Suggested Citation

  • Toshiko Matsui & William J. Knottenbelt, 2024. "Forecasting Realised Volatility: Implied and GARCH Volatility in Bitcoin, Gold, Oil Markets," Lecture Notes in Operations Research,, Springer.
  • Handle: RePEc:spr:lnopch:978-3-031-68974-1_6
    DOI: 10.1007/978-3-031-68974-1_6
    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.

    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:spr:lnopch:978-3-031-68974-1_6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.