IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/49898.html
   My bibliography  Save this paper

Volatility and dynamic conditional correlations of European emerging stock markets

Author

Listed:
  • Baumohl, Eduard
  • Lyocsa, Stefan

Abstract

This study examines the relationship between time-varying correlations and conditional volatility among eight European emerging stock markets and the MSCI World stock market index from January 2000 to December 2012. Correlations are estimated in the standard and asymmetric dynamic conditional correlation (DCC) model frameworks. The results can be summarized by three main findings: (1) asymmetry in volatility is not a common phenomenon in emerging markets; (2) asymmetry in correlations is found only with respect to the Hungarian stock market; and (3) the relationship between volatility and correlations is positive and significant in all countries included in the study. Thus, diversification benefits decrease during periods of higher volatility.

Suggested Citation

  • Baumohl, Eduard & Lyocsa, Stefan, 2013. "Volatility and dynamic conditional correlations of European emerging stock markets," MPRA Paper 49898, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:49898
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/49898/1/MPRA_paper_49898.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    3. Gjika, Dritan & Horváth, Roman, 2013. "Stock market comovements in Central Europe: Evidence from the asymmetric DCC model," Economic Modelling, Elsevier, vol. 33(C), pages 55-64.
    4. Horvath, Roman & Petrovski, Dragan, 2013. "International stock market integration: Central and South Eastern Europe compared," Economic Systems, Elsevier, vol. 37(1), pages 81-91.
    5. Meric, Ilhan & Meric, Gulser, 1989. "Potential gains from international portfolio diversification and inter-temporal stability and seasonality in international stock market relationships," Journal of Banking & Finance, Elsevier, vol. 13(4-5), pages 627-640, September.
    6. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572.
    7. Durai, S. Raja Sethu & Bhaduri, Saumitra N., 2011. "Correlation dynamics in equity markets: evidence from India," Research in International Business and Finance, Elsevier, vol. 25(1), pages 64-74, January.
    8. Kenourgios, Dimitris & Samitas, Aristeidis, 2011. "Equity market integration in emerging Balkan markets," Research in International Business and Finance, Elsevier, vol. 25(3), pages 296-307, September.
    9. Jen-Je Su, 2008. "A note on spurious regressions between stationary series," Applied Economics Letters, Taylor & Francis Journals, vol. 15(15), pages 1225-1230.
    10. Syllignakis, Manolis N. & Kouretas, Georgios P., 2011. "Dynamic correlation analysis of financial contagion: Evidence from the Central and Eastern European markets," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 717-732, October.
    11. Clive Granger & Namwon Hyung & Yongil Jeon, 2001. "Spurious regressions with stationary series," Applied Economics, Taylor & Francis Journals, vol. 33(7), pages 899-904.
    12. Arshanapalli, Bala & Doukas, John, 1993. "International stock market linkages: Evidence from the pre- and post-October 1987 period," Journal of Banking & Finance, Elsevier, vol. 17(1), pages 193-208, February.
    13. Guesmi, Khaled & Nguyen, Duc Khuong, 2011. "How strong is the global integration of emerging market regions? An empirical assessment," Economic Modelling, Elsevier, vol. 28(6), pages 2517-2527.
    14. Jeffrey Jaffe & R. Westerfield, "undated". "The Week-End Effect in Common Stock Returns: The International Evidence," Rodney L. White Center for Financial Research Working Papers 3-85, Wharton School Rodney L. White Center for Financial Research.
    15. Büttner, David & Hayo, Bernd, 2011. "Determinants of European stock market integration," Economic Systems, Elsevier, vol. 35(4), pages 574-585.
    16. Jaffe, Jeffrey F & Westerfield, Randolph, 1985. "The Week-End Effect in Common Stock Returns: The International Evidence," Journal of Finance, American Finance Association, vol. 40(2), pages 433-454, June.
    17. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    18. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    19. Samarakoon, Lalith P., 2011. "Stock market interdependence, contagion, and the U.S. financial crisis: The case of emerging and frontier markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(5), pages 724-742.
    20. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    21. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    22. Eduard Baumöhl & Tomáš Výrost, 2010. "Stock Market Integration: Granger Causality Testing with Respect to Nonsynchronous Trading Effects," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(5), pages 414-425, December.
    23. F. Cribari-Neto & S. G. Zarkos, 1999. "Bootstrap methods for heteroskedastic regression models: evidence on estimation and testing," Econometric Reviews, Taylor & Francis Journals, vol. 18(2), pages 211-228.
    24. Jeffrey Jaffe & R. Westerfield, "undated". "The Week-End Effect in Common Stock Returns: The International Evidence," Rodney L. White Center for Financial Research Working Papers 03-85, Wharton School Rodney L. White Center for Financial Research.
    25. Ping Wang & Tomoe Moore, 2008. "Stock Market Integration For The Transition Economies: Time‐Varying Conditional Correlation Approach," Manchester School, University of Manchester, vol. 76(s1), pages 116-133, September.
    26. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    27. Kenourgios, Dimitris & Samitas, Aristeidis & Paltalidis, Nikos, 2011. "Financial crises and stock market contagion in a multivariate time-varying asymmetric framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 92-106, February.
    28. Engle, Robert F. & White (the late), Halbert (ed.), 1999. "Cointegration, Causality, and Forecasting: Festschrift in Honour of Clive W. J. Granger," OUP Catalogue, Oxford University Press, number 9780198296836.
    29. E. Baumohl & S. Lyocsa & T. Vyrost, 2011. "Shift contagion with endogenously detected volatility breaks: the case of CEE stock markets," Applied Economics Letters, Taylor & Francis Journals, vol. 18(12), pages 1103-1109.
    30. Lahrech, Abdelmounaim & Sylwester, Kevin, 2011. "U.S. and Latin American stock market linkages," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1341-1357.
    31. Hafner, Christian M. & Reznikova, Olga, 2012. "On the estimation of dynamic conditional correlation models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3533-3545.
    32. MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.
    33. Ripley, Duncan M, 1973. "Systematic Elements in the Linkage of National Stock Market Indices," The Review of Economics and Statistics, MIT Press, vol. 55(3), pages 356-361, August.
    34. Lessard, Donald R, 1974. "World, National, and Industry Factors in Equity Returns," Journal of Finance, American Finance Association, vol. 29(2), pages 379-391, May.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.

    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. Baumöhl, Eduard & Lyócsa, Štefan, 2014. "Volatility and dynamic conditional correlations of worldwide emerging and frontier markets," Economic Modelling, Elsevier, vol. 38(C), pages 175-183.
    2. Baumöhl, Eduard, 2013. "Stock market integration between the CEE-4 and the G7 markets: Asymmetric DCC and smooth transition approach," MPRA Paper 43834, University Library of Munich, Germany.
    3. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    4. Eduard Baum??hl & ??tefan Ly??csa, 2014. "How smooth is the stock market integration of CEE-3?," William Davidson Institute Working Papers Series wp1079, William Davidson Institute at the University of Michigan.
    5. Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Similarity of emerging market returns under changing market conditions: Markets in the ASEAN-4, Latin America, Middle East, and BRICs," Economic Systems, Elsevier, vol. 39(2), pages 253-268.
    6. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    7. Vyrost, Tomas & Baumöhl, Eduard & Lyocsa, Stefan, 2013. "What Drives the Stock Market Integration in the CEE-3?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 61(1), pages 67-81.
    8. Eduard Baumöhl & Štefan Lyócsa, 2014. "Risk-Return Convergence in CEE Stock Markets: Structural Breaks and Market Volatility," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(5), pages 352-373, November.
    9. Gjika, Dritan & Horváth, Roman, 2013. "Stock market comovements in Central Europe: Evidence from the asymmetric DCC model," Economic Modelling, Elsevier, vol. 33(C), pages 55-64.
    10. Roman Horváth & Štefan Lyócsa & Eduard Baumöhl, 2018. "Stock market contagion in Central and Eastern Europe: unexpected volatility and extreme co-exceedance," The European Journal of Finance, Taylor & Francis Journals, vol. 24(5), pages 391-412, March.
    11. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    12. Eduard Baumöhl, 2014. "Determinanty integrácie akciových trhov krajín V4 [Determinants of CEE-4 Stock Market Integration]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(3), pages 347-365.
    13. Khalfaoui, R & Boutahar, M, 2012. "Portfolio risk evaluation: An approach based on dynamic conditional correlations models and wavelet multiresolution analysis," MPRA Paper 41624, University Library of Munich, Germany.
    14. Wang, Xinya & Liu, Huifang & Huang, Shupei, 2019. "Identification of the daily seasonality in gold returns and volatilities: Evidence from Shanghai and London," Resources Policy, Elsevier, vol. 61(C), pages 522-531.
    15. Ercan Balaban & Asli Bayar & Ozgur Berk Kan, 2001. "Stock returns, seasonality and asymmetric conditional volatility in world equity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 8(4), pages 263-268.
    16. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    17. Caldeira, João F & Moura, Guilherme Valle & Santos, André Alves Portela, 2013. "Seleção de carteiras utilizando o modelo Fama-French-Carhart," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
    18. Baumöhl, Eduard & Kočenda, Evžen & Lyócsa, Štefan & Výrost, Tomáš, 2018. "Networks of volatility spillovers among stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1555-1574.
    19. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    20. Ø. Gjerde & F. Sættem, 1995. "Linkages among European and world stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 1(2), pages 165-179.

    More about this item

    Keywords

    conditional volatility; time-varying correlations; emerging markets;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:pra:mprapa:49898. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.