IDEAS home Printed from
   My bibliography  Save this paper

Markov-switching GARCH models in finance: a unifying framework with an application to the German stock market


  • Gerrit Reher
  • Bernd Wilfling


In this paper we develop a unifying Markov-switching GARCH model which enables us (1) to specify complex GARCH equations in two distinct Markov-regimes, and (2) to model GARCH equations of different functional forms across the two Markov-regimes. To give a simple example, our flexible Markov-switching approach is capable of estimating an exponential GARCH (EGARCH) specification in the first and a standard GARCH specification in the second Markov-regime. We derive a maximum likelihood estimation framework and apply our general Markov-switching GARCH model to daily excess returns of the German stock market index DAX. Our empirical study has two major findings. First, our estimation results unambiguously indicate that our general model outperforms all conventional Markov-switching GARCH models hitherto estimated in the financial literature. Second, we find significant Markov-switching in the German stock market with substantially differing volatility structures across the regimes.

Suggested Citation

  • Gerrit Reher & Bernd Wilfling, 2011. "Markov-switching GARCH models in finance: a unifying framework with an application to the German stock market," CQE Working Papers 1711, Center for Quantitative Economics (CQE), University of Muenster.
  • Handle: RePEc:cqe:wpaper:1711

    Download full text from publisher

    File URL:
    File Function: Version of January, 2011
    Download Restriction: no


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

    Cited by:

    1. Zieling, Daniel & Mahayni, Antje & Balder, Sven, 2014. "Performance evaluation of optimized portfolio insurance strategies," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 212-225.

    More about this item


    Markov-switching models; GARCH models; Dynamics of stock index returns;

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:cqe:wpaper:1711. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Susanne Deckwitz). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.