IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v158y2020ics0167715219302627.html
   My bibliography  Save this article

Decomposing correlated random walks on common and counter movements

Author

Listed:
  • Chen, Tianyao
  • Cheng, Xue
  • Yang, Jingping

Abstract

Random walk is one of the most classical models in probability theory which has got extensive applications in many areas and is still of great interest in practice. For those problems that require modelling two random walks on lattice, correlation of the random walks is non-ignorable. This paper presents a new method to study the dependency structure of two generally correlated random walks. By introducing a change-of-time process, two correlated random walks can be decomposed into sum/difference of two independent random walks with time change, where the two independent random walks present respectively the common movements and counter movements of the original random walks. A sufficient and necessary condition is given for the mutual independence of the change-of-time process and the two independent random walks. For the prospective applications of the decomposition method in theory and practice, we consider the calculations of the characteristic functions for Markovian and non-Markovian random walks and an empirical example in futures trading is given.

Suggested Citation

  • Chen, Tianyao & Cheng, Xue & Yang, Jingping, 2020. "Decomposing correlated random walks on common and counter movements," Statistics & Probability Letters, Elsevier, vol. 158(C).
  • Handle: RePEc:eee:stapro:v:158:y:2020:i:c:s0167715219302627
    DOI: 10.1016/j.spl.2019.108616
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715219302627
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spl.2019.108616?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:stapro:v:158:y:2020:i:c:s0167715219302627. 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/622892/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.