IDEAS home Printed from https://ideas.repec.org/a/agh/journl/v8y2010p21-39.html
   My bibliography  Save this article

Polish stock market and some foreign markets - dependence analysis by regime-switching copulas

Author

Listed:
  • Henryk Gurgul

    () (AGH University of Science and Technology in Cracow, Department of Applications of Mathematics in Economics)

  • Robert Syrek

Abstract

The aim of this paper is investigation of DJIA, DAX, ATX and WIG20 interdependence based on weekly returns. In order to capture asymmetry of dependence structure Archimedean copulas were applied and symmetric structures are modelled with elliptical copulas. The strength of dependence between extreme events is examined by tail dependence coefficients. Changes in dependence patterns and parameter values are obtained by the application of the regime-switching model based on the first order Markov chain. We are using a two-step maximum likelihood estimation method which separates marginal distributions from the dependence structure. Parameters of copulas are estimated using Hamilton filter adopted to copulas. The copula based on regime-switching model allows us to model time varying dependence structure in a very flexible way. Empirical results confirm dynamic and asymmetric structure of dependence represented by stock markets under study, especially they verify strong and dynamic lower tail dependence.

Suggested Citation

  • Henryk Gurgul & Robert Syrek, 2010. "Polish stock market and some foreign markets - dependence analysis by regime-switching copulas," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 8, pages 21-39.
  • Handle: RePEc:agh:journl:v:8:y:2010:p:21-39
    as

    Download full text from publisher

    File URL: http://www.managerial.zarz.agh.edu.pl/old/Managerial%20Economics%20%208%20%282010%29.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lorán Chollete & Andréas Heinen & Alfonso Valdesogo, 2009. "Modeling International Financial Returns with a Multivariate Regime-switching Copula," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(4), pages 437-480, Fall.
    2. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    3. Kim, Sang W. & Rogers, John H., 1995. "International stock price spillovers and market liberalization: Evidence from Korea, Japan, and the United States," Journal of Empirical Finance, Elsevier, vol. 2(2), pages 117-133, June.
    4. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    5. John M. Abowd & David S. Kaplan, 1999. "Executive Compensation: Six Questions That Need Answering," Journal of Economic Perspectives, American Economic Association, vol. 13(4), pages 145-168, Fall.
    6. Ng, Angela, 2000. "Volatility spillover effects from Japan and the US to the Pacific-Basin," Journal of International Money and Finance, Elsevier, vol. 19(2), pages 207-233, April.
    7. Booth, G. Geoffrey & Martikainen, Teppo & Tse, Yiuman, 1997. "Price and volatility spillovers in Scandinavian stock markets," Journal of Banking & Finance, Elsevier, vol. 21(6), pages 811-823, June.
    8. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    9. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
    10. Eun, Cheol S. & Shim, Sangdal, 1989. "International Transmission of Stock Market Movements," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(02), pages 241-256, June.
    11. Shapiro, Carl & Stiglitz, Joseph E, 1984. "Equilibrium Unemployment as a Worker Discipline Device," American Economic Review, American Economic Association, vol. 74(3), pages 433-444, June.
    12. Jean-François Nivet, 1997. "Stock markets in transition: the Warsaw experiment," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 5(1), pages 171-183, May.
    13. repec:ebl:ecbull:v:7:y:2005:i:1:p:1-6 is not listed on IDEAS
    14. Lin, Wen-Ling & Engle, Robert F & Ito, Takatoshi, 1994. "Do Bulls and Bears Move across Borders? International Transmission of Stock Returns and Volatility," Review of Financial Studies, Society for Financial Studies, vol. 7(3), pages 507-538.
    15. Ammermann, Peter A. & Patterson, Douglas M., 2003. "The cross-sectional and cross-temporal universality of nonlinear serial dependencies: Evidence from world stock indices and the Taiwan Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 11(2), pages 175-195, April.
    16. Chen, Yi-Ting, 2007. "Moment-Based Copula Tests for Financial Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 377-397, October.
    17. Okimoto, Tatsuyoshi, 2008. "New Evidence of Asymmetric Dependence Structures in International Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(03), pages 787-815, September.
    18. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    19. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 130-168.
    20. Claudio Bonilla & Rafael Romero-Meza & Melvin Hinich, 2006. "Episodic nonlinearity in Latin American stock market indices," Applied Economics Letters, Taylor & Francis Journals, vol. 13(3), pages 195-199.
    21. Alexandru Todea & Adrian Zoicas-Ienciu, 2008. "Episodic dependencies in Central and Eastern Europe stock markets," Applied Economics Letters, Taylor & Francis Journals, vol. 15(14), pages 1123-1126.
    22. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    23. Kian-Ping Lim & Melvin J. Hinich, 2005. "Cross-temporal universality of non-linear dependencies in Asian stock markets," Economics Bulletin, AccessEcon, vol. 7(1), pages 1-6.
    24. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 717-729.
    25. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 401-423, June.
    26. Bessler, David A. & Yang, Jian, 2003. "The structure of interdependence in international stock markets," Journal of International Money and Finance, Elsevier, vol. 22(2), pages 261-287, April.
    27. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    28. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    29. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    30. Ramchand, Latha & Susmel, Raul, 1998. "Volatility and cross correlation across major stock markets," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 397-416, October.
    31. François Longin, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    32. Paola Palmitesta & Corrado Provasi, 2005. "Aggregation of Dependent Risks Using the Koehler–Symanowski Copula Function," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 189-205, February.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    copula; switching model; tail dependence coefficients;

    JEL classification:

    • G0 - Financial Economics - - General
    • G00 - Financial Economics - - General - - - General

    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:agh:journl:v:8:y:2010:p:21-39. 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: (Lukasz Lach). General contact details of provider: http://edirc.repec.org/data/wzaghpl.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.

    If CitEc recognized a 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.

    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.