IDEAS home Printed from https://ideas.repec.org/p/cab/wpaefr/40.html
   My bibliography  Save this paper

Exploring Dual Long Memory in Returns and Volatility Across Central and Eastern Europe Stock Markets

Author

Listed:
  • Mihaela Sandu

Abstract

We investigate the presence of long memory in emerging CEE stock markets using the nonparametric, semiparametric and parametric approaches. We consider the methodology of Bai and Peron to test for structural breaks in the return series and we perform tests of fractionally integrated process on subsamples in order to identify potential evidence of spurious long memory. We test for long memory in both conditional mean and conditional variance by combining a fractionally integrated regression function and a fractionally integrated skedastic function.We estimate ARFIMA-GARCH and ARFIMA-FIGARCH models under two proposed distributions. The skewed Student-t distribution is found to better describe the data comparing to Gaussian distribution. We conclude that the Romanian, Hungarian and Czech Republic capital markets show evidence of dual long memory in returns and volatility, while the Bulgarian and Poland markets show strong features of long memory in volatility, but no long memory in the return series.

Suggested Citation

  • Mihaela Sandu, 2009. "Exploring Dual Long Memory in Returns and Volatility Across Central and Eastern Europe Stock Markets," Advances in Economic and Financial Research - DOFIN Working Paper Series 40, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
  • Handle: RePEc:cab:wpaefr:40
    as

    Download full text from publisher

    File URL: http://www.dofin.ase.ro/Working%20papers/Sandu%20Mihaela/sandu.mihaela.dissertation.pdf
    File Function: First version, 2009
    Download Restriction: no

    References listed on IDEAS

    as
    1. Martin Cihak & Klaus Schaeck, 2007. "How Well Do Aggregate Bank Ratios Identify Banking Problems?," IMF Working Papers 07/275, International Monetary Fund.
    2. Engelmann, Bernd & Hayden, Evelyn & Tasche, Dirk, 2003. "Measuring the Discriminative Power of Rating Systems," Discussion Paper Series 2: Banking and Financial Studies 2003,01, Deutsche Bundesbank, Research Centre.
    3. Rupert D Worrell, 2004. "Quantitative Assessment of the Financial Sector; An Integrated Approach," IMF Working Papers 04/153, International Monetary Fund.
    4. Allen N. Berger & Margaret K. Kyle & Joseph M. Scalise, 2001. "Did U.S. Bank Supervisors Get Tougher during the Credit Crunch? Did They Get Easier during the Banking Boom? Did It Matter to Bank Lending?," NBER Chapters,in: Prudential Supervision: What Works and What Doesn't, pages 301-356 National Bureau of Economic Research, Inc.
    5. repec:bla:joares:v:4:y:1966:i::p:71-111 is not listed on IDEAS
    6. Alexis Derviz & JiÅí Podpiera, 2008. "Predicting Bank CAMELS and S&P Ratings: The Case of the Czech Republic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 44(1), pages 117-130, January.
    7. repec:bla:joares:v:18:y:1980:i:1:p:109-131 is not listed on IDEAS
    8. Kolari, James & Glennon, Dennis & Shin, Hwan & Caputo, Michele, 2002. "Predicting large US commercial bank failures," Journal of Economics and Business, Elsevier, pages 361-387.
    9. Julapa Jagtiani & James Kolari & Catharine Lemieux & G. Hwan Shin, 2003. "Early warning models for bank supervision: Simpler could be better," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q III, pages 49-60.
    10. Rupa Duttagupta & Paul Cashin, 2008. "The Anatomy of Banking Crises," IMF Working Papers 08/93, International Monetary Fund.
    11. Tigran Poghosyan & Martin Cihak, 2009. "Distress in European Banks; An Analysis Basedon a New Dataset," IMF Working Papers 09/9, International Monetary Fund.
    12. FFF1Jitka NNN1Rychtarikova, 2004. "The case of the Czech Republic," Demographic Research Special Collections, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 2(5), pages 105-138, April.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    long memory; stock market; ARFIMA; FIGARCH;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cab:wpaefr:40. 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: (Ciprian Necula). General contact details of provider: http://edirc.repec.org/data/caasero.html .

    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.