IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v41y2025i2p763-780.html
   My bibliography  Save this article

Skew–Brownian processes for estimating the volatility of crude oil Brent

Author

Listed:
  • Bufalo, Michele
  • Liseo, Brunero
  • Orlando, Giuseppe

Abstract

To predict the volatility of crude oil Brent price, we propose a novel econometric model 11The numerical results presented in this manuscript were reproduced by the Editor-in-Chief on 30 June 2024. where the explanatory variables are a combination of macroeconomic variables (i.e. price pressure), trade data (freight shipment index), and market sentiment (gold volatility). The model is proposed in two alternative variants: first, we assume Gaussian distributed quantities; alternatively, we consider the potential presence of skewness and adopt a Skew–Brownian process. We show that the suggested approach outperforms the selected baseline model as well as other models proposed in the literature, especially when turbulent periods occur.

Suggested Citation

  • Bufalo, Michele & Liseo, Brunero & Orlando, Giuseppe, 2025. "Skew–Brownian processes for estimating the volatility of crude oil Brent," International Journal of Forecasting, Elsevier, vol. 41(2), pages 763-780.
    • Handle: RePEc:eee:intfor:v:41:y:2025:i:2:p:763-780
    DOI: 10.1016/j.ijforecast.2024.06.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207024000633
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijforecast.2024.06.009?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.

    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:eee:intfor:v:41:y:2025:i:2:p:763-780. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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.