IDEAS home Printed from https://ideas.repec.org/h/spr/oprchp/978-3-319-89920-6_12.html
   My bibliography  Save this book chapter

Long-Term Projections for Commodity Prices—The Crude Oil Price Using Dynamic Bayesian Networks

In: Operations Research Proceedings 2017

Author

Listed:
  • Thomas Schwarz

    (Technische Universität Berlin)

  • Hans-Joachim Lenz

    (Freie Universität Berlin)

  • Wilhelm Dominik

    (Technische Universität Berlin)

Abstract

Long-term projections for commodity prices are a key challenge in science as well as in business environment. This paper proposes a new mathematical approach for future projections of prices for time horizons larger than 10 years using a Dynamic Bayesian Network (DBN). The DBN approach is verified at the crude oil price example.

Suggested Citation

  • Thomas Schwarz & Hans-Joachim Lenz & Wilhelm Dominik, 2018. "Long-Term Projections for Commodity Prices—The Crude Oil Price Using Dynamic Bayesian Networks," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 81-87, Springer.
  • Handle: RePEc:spr:oprchp:978-3-319-89920-6_12
    DOI: 10.1007/978-3-319-89920-6_12
    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:oprchp:978-3-319-89920-6_12. 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.