IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v170y2024ics0304414923002612.html
   My bibliography  Save this article

Long-range dependent completely correlated mixed fractional Brownian motion

Author

Listed:
  • Dufitinema, Josephine
  • Shokrollahi, Foad
  • Sottinen, Tommi
  • Viitasaari, Lauri

Abstract

In this paper we introduce the long-range dependent completely correlated mixed fractional Brownian motion (ccmfBm). This is a process that is driven by a mixture of Brownian motion (Bm) and a long-range dependent completely correlated fractional Brownian motion (fBm, ccfBm) that is constructed from the Brownian motion via the Molchan–Golosov representation. Thus, there is a single Bm driving the mixed process. In the short time-scales the ccmfBm behaves like the Bm (it has Brownian Hölder index and quadratic variation). However, in the long time-scales it behaves like the fBm (it has long-range dependence governed by the fBms Hurst index). We provide a transfer principle for the ccmfBm and use it to construct the Cameron–Martin–Girsanov–Hitsuda theorem and prediction formulas. Finally, we illustrate the ccmfBm by simulations.

Suggested Citation

  • Dufitinema, Josephine & Shokrollahi, Foad & Sottinen, Tommi & Viitasaari, Lauri, 2024. "Long-range dependent completely correlated mixed fractional Brownian motion," Stochastic Processes and their Applications, Elsevier, vol. 170(C).
  • Handle: RePEc:eee:spapps:v:170:y:2024:i:c:s0304414923002612
    DOI: 10.1016/j.spa.2023.104289
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304414923002612
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spa.2023.104289?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:spapps:v:170:y:2024:i:c:s0304414923002612. 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/wps/find/journaldescription.cws_home/505572/description#description .

    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.