IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v65y2024i4d10.1007_s00362-023-01484-3.html
   My bibliography  Save this article

Detection of multiple change-points in high-dimensional panel data with cross-sectional and temporal dependence

Author

Listed:
  • Marie-Christine Düker

    (Cornell University)

  • Seok-Oh Jeong

    (Hankuk University of Foreign Studies)

  • Taewook Lee

    (Hankuk University of Foreign Studies)

  • Changryong Baek

    (Sungkyunkwan University)

Abstract

We consider the detection of multiple change-points in a high-dimensional time series exhibiting both cross-sectional and temporal dependence. Several test statistics based on the celebrated CUSUM statistic are used and discussed. In particular, we propose a novel block wild bootstrap method to address the presence of cross-sectional and temporal dependence. Furthermore, binary segmentation and the moving sum algorithm are considered to detect and locate multiple change-points. We also give some theoretical justifications for the moving sum method. An extensive numerical study provides insights on the performance of the proposed methods. Finally, our proposed procedures are used to analyze financial stock data in Korea.

Suggested Citation

  • Marie-Christine Düker & Seok-Oh Jeong & Taewook Lee & Changryong Baek, 2024. "Detection of multiple change-points in high-dimensional panel data with cross-sectional and temporal dependence," Statistical Papers, Springer, vol. 65(4), pages 2327-2359, June.
    • Handle: RePEc:spr:stpapr:v:65:y:2024:i:4:d:10.1007_s00362-023-01484-3
    DOI: 10.1007/s00362-023-01484-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-023-01484-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00362-023-01484-3?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:spr:stpapr:v:65:y:2024:i:4:d:10.1007_s00362-023-01484-3. 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.