IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v44y2025i9p1275-1320.html
   My bibliography  Save this article

Time series quantile regression kink with an unknown threshold

Author

Listed:
  • Feipeng Zhang
  • Rui Xie
  • Zhijie Xiao

Abstract

This article studies a time series quantile regression kink model with an unknown threshold over certain quantile levels in the distribution. We propose to estimate the threshold parameter and regression parameters using a two-stage method. We also propose a weighted CUSUM test for threshold effect at both a given quantile level and multiple quantile levels based on the subgradient of the quantile loss function. In addition, we consider a likelihood-ratio-type test for the presence of a common threshold value across different quantile levels. Excellent finite sample performance of the proposed method is demonstrated by simulation studies. We further apply our proposed method to the S & P500 index data to explore the possible nonlinearity and heteroscedasticity of the return autocorrelations in the S & P500 index.

Suggested Citation

  • Feipeng Zhang & Rui Xie & Zhijie Xiao, 2025. "Time series quantile regression kink with an unknown threshold," Econometric Reviews, Taylor & Francis Journals, vol. 44(9), pages 1275-1320, October.
    • Handle: RePEc:taf:emetrv:v:44:y:2025:i:9:p:1275-1320
    DOI: 10.1080/07474938.2025.2504110
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07474938.2025.2504110
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07474938.2025.2504110?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

    for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    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:taf:emetrv:v:44:y:2025:i:9:p:1275-1320. 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: the person in charge (email available below). General contact details of provider: http://www.tandfonline.com/LECR20 .

    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.