IDEAS home Printed from https://ideas.repec.org/a/taf/reroxx/v30y2017i1p1865-1881.html
   My bibliography  Save this article

The impact of regime-switching behaviour of price volatility on efficiency of the US sovereign debt market

Author

Listed:
  • Omar Masood
  • Bora Aktan
  • Beata Gavurová
  • Bachar Fakhry
  • Manuela Tvaronavičienė
  • Raimonda Martinkutė-Kaulienė

Abstract

This article focuses on the asset price volatility at the stock exchange that result from the regime switching behaviour in the market. This study is devoted to the question about how the asset price volatility affects the US sovereign debt market. The efficient market hypothesis has been a base for the asset pricing. This hypothesis is discussed in this study. The review of the literature reveals nuances of behavioural finance theory, and allows us to better understand the regime switching behaviour in the market. The object of empirical study is the US sovereign debt market. We use the Markov Regime-Switching ARCH (SWARCH) model to analyse data. The results show that there is high volatility regime in both the 2012 and 2017 bonds US market, which significantly affects bond prices.

Suggested Citation

  • Omar Masood & Bora Aktan & Beata Gavurová & Bachar Fakhry & Manuela Tvaronavičienė & Raimonda Martinkutė-Kaulienė, 2017. "The impact of regime-switching behaviour of price volatility on efficiency of the US sovereign debt market," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 30(1), pages 1865-1881, January.
  • Handle: RePEc:taf:reroxx:v:30:y:2017:i:1:p:1865-1881
    DOI: 10.1080/1331677X.2017.1394896
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1331677X.2017.1394896
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/1331677X.2017.1394896?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. Dejan Živkov & Boris Kuzman & Jonel Subić, 2020. "What Bayesian quantiles can tell about volatility transmission between the major agricultural futures?," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(5), pages 215-225.

    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:reroxx:v:30:y:2017:i:1:p:1865-1881. 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/rero .

    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.