IDEAS home Printed from https://ideas.repec.org/p/fau/wpaper/wp2007_02.html
   My bibliography  Save this paper

Dependence Structure and Portfolio Diversification on Central European Stock Markets

Author

Abstract

This paper studies the dependence structure on Central European, German and UK stock markets within the framework of a semiparametric copula model for weekly stock index return pairs. Although the linear correlation is much lower, we find similar degree of lower tail dependence as between returns on stocks indices representing developed markets. We show in a simulation exercise that the implications of the estimated nonlinear dependencies for portfolio selection and risk management may be not only statisticaly but also economicaly important.

Suggested Citation

  • Filip Žikeš, 2007. "Dependence Structure and Portfolio Diversification on Central European Stock Markets," Working Papers IES 2007/02, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jan 2007.
  • Handle: RePEc:fau:wpaper:wp2007_02
    as

    Download full text from publisher

    File URL: http://ies.fsv.cuni.cz/default/file/download/id/4962
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ines Fortin & Christoph Kuzmics, 2002. "Tail‐dependence in stock‐return pairs," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 11(2), pages 89-107, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sancetta, A., 2005. "Copula Based Monte Carlo Integration in Financial Problems," Cambridge Working Papers in Economics 0506, Faculty of Economics, University of Cambridge.
    2. Rubén Loaiza‐Maya & Michael S. Smith & Worapree Maneesoonthorn, 2018. "Time series copulas for heteroskedastic data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 332-354, April.
    3. Abberger, Klaus, 2004. "A simple graphical method to explore tail-dependence in stock-return pairs," CoFE Discussion Papers 04/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
    4. Smith, Michael Stanley, 2015. "Copula modelling of dependence in multivariate time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 815-833.
    5. YiHao Lai, 2008. "Does Asymmetric Dependence Structure Matter? A Value-at-Risk View," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(3), pages 249-268, December.
    6. Magnolia Sosa Castro & Christian Bucio Pacheco & Héctor Eduardo Díaz Rodríguez, 2021. "Extreme Volatility Dependence in Exchange Rate," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 40(82), pages 25-55, February.
    7. Krämer, Walter & van Kampen, Maarten, 2011. "A simple nonparametric test for structural change in joint tail probabilities," Economics Letters, Elsevier, vol. 110(3), pages 245-247, March.
    8. Dobrić, Jadran & Frahm, Gabriel & Schmid, Friedrich, 2007. "Dependence of stock returns in bull and bear markets," Discussion Papers in Econometrics and Statistics 9/07, University of Cologne, Institute of Econometrics and Statistics.
    9. Knyazev, Alexander & Lepekhin, Oleg & Shemyakin, Arkady, 2016. "Joint distribution of stock indices: Methodological aspects of construction and selection of copula models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 42, pages 30-53.
    10. Geraci, Marco Valerio & Garbaravičius, Tomas & Veredas, David, 2018. "Short selling in extreme events," Journal of Financial Stability, Elsevier, vol. 39(C), pages 90-103.
    11. Fischer, Matthias J., 2003. "Tailoring copula-based multivariate generalized hyperbolic secant distributions to financial return data: an empirical investigation," Discussion Papers 47/2003, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    12. Marco Valerio Geraci & Tomas Garbaravicius & David Veredas, 2016. "Short Selling in the Tails," Working Papers ECARES ECARES 2016-30, ULB -- Universite Libre de Bruxelles.
    13. Dobric Jadran & Frahm Gabriel & Schmid Friedrich, 2013. "Dependence of Stock Returns in Bull and Bear Markets," Dependence Modeling, De Gruyter, vol. 1(2013), pages 94-110, December.
    14. Janani Sri S. & Parthajit Kayal & G. Balasubramanian, 2022. "Can Equity be Safe-haven for Investment?," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 21(1), pages 32-63, March.
    15. Lai, YiHao & Tseng, Jen-Ching, 2010. "The role of Chinese stock market in global stock markets: A safe haven or a hedge?," International Review of Economics & Finance, Elsevier, vol. 19(2), pages 211-218, April.
    16. Giovanni De Luca & Giorgia Rivieccio, 2009. "Archimedean copulae for risk measurement," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(8), pages 907-924.
    17. Giovanni De Luca & Paola Zuccolotto, 2011. "A tail dependence-based dissimilarity measure for financial time series clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 323-340, December.
    18. Thomas Fung & Eugene Seneta, 2010. "Modelling and Estimation for Bivariate Financial Returns," International Statistical Review, International Statistical Institute, vol. 78(1), pages 117-133, April.
    19. Dias, Alexandra & Embrechts, Paul, 2010. "Modeling exchange rate dependence dynamics at different time horizons," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1687-1705, December.
    20. Arno Onken & Steffen Grünewälder & Matthias H J Munk & Klaus Obermayer, 2009. "Analyzing Short-Term Noise Dependencies of Spike-Counts in Macaque Prefrontal Cortex Using Copulas and the Flashlight Transformation," PLOS Computational Biology, Public Library of Science, vol. 5(11), pages 1-13, November.

    More about this item

    Keywords

    dependence structure; tail dependence; portfolio selection; risk measures;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

    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:fau:wpaper:wp2007_02. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Natalie Svarcova (email available below). General contact details of provider: https://edirc.repec.org/data/icunicz.html .

    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.