IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v22y2015i4p318-323.html
   My bibliography  Save this article

Can we distinguish regime switching from long memory? A simulation evidence

Author

Listed:
  • Yanlin Shi

Abstract

It is well known that long memory can be caused by regime switching and is easily confused with it. However, recent study suggests that if the cause of confusion was properly controlled for, long memory and regime switching could be distinguished. Motivated by this idea, our study aims to distinguish regime switching from long memory for the financial time series. In this article, we model long memory and regime switching via the ARFIMA and Markov regime-switching (MRS) frameworks, respectively. A theoretical proof is provided to show that the time-varying smoothing probability series can induce the presence of significant long memory in the regime-switching process. We then propose a two-stage two-state-ARFIMA (2S-ARFIMA) model to control for the effect of the smoothing probability and use a simulation study to demonstrate that it can effectively distinguish the pure MRS process from the pure ARFIMA process.

Suggested Citation

  • Yanlin Shi, 2015. "Can we distinguish regime switching from long memory? A simulation evidence," Applied Economics Letters, Taylor & Francis Journals, vol. 22(4), pages 318-323, March.
    • Handle: RePEc:taf:apeclt:v:22:y:2015:i:4:p:318-323
    DOI: 10.1080/13504851.2014.941526
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13504851.2014.941526
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13504851.2014.941526?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shi, Yanlin & Ho, Kin-Yip, 2015. "Long memory and regime switching: A simulation study on the Markov regime-switching ARFIMA model," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 189-204.

    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:apeclt:v:22:y:2015:i:4:p:318-323. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    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.