Commonalities in Returns in the Stock Markets of the Visegrad Group: A Quantile Coherency Approach


The aim of this paper is to investigate the dependence structure in the frequency domain for the joint distribution of returns from the stock markets in the countries belonging to the V4 countries. We analyze twenty-years of historical daily prices of four main stock indices from the Czech Republic, Hungary, Poland, and Slovakia. Using a quantile coherency measure we found, that linkages between Czech, Hungarian, and Polish stock markets are significantly positive for all considered quantiles and frequencies. These three markets are more strongly dependent during the long downturns and the effect is permanent after the European Union accession. The Slovak stock market is the least connected with other countries in the group. Results of the paper revealed, that Czech, Hungarian and Polish stock market is subject to similar trends in terms of returns for different investment horizons. International market participants should incorporate interdependencies between these markets during the portfolio building process.

quantile coherency; frequency domain; Visegrad Group; stock market

Baruník, J. and Kley T. (2019). Quantile coherency: a general measure for dependence between cyclical economic variables. Econometrics Journal, 22, pp. 131-152.

Baumöhl, E. (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. Retrieved from:

Boţoc, C. (2017). Univariate and bivariate volatility in Central European stock markets. Prague Economic Papers, 26(2), pp. 127–141.

Boţoc, C. and Anton, S.G. (2020). New empirical evidence on CEE's stock markets integration. The World Economy, 2020, 00, pp. 1– 18.

Gjika, D. and Horváth, R. (2013). Stock Market Comovements in Central Europe: Evidence from the Asymmetric DCC Model. Economic Modelling, 33, pp. 55–64,

Horváth, R. et al. (2018). Stock market contagion in Central and Eastern Europe: unexpected volatility and extreme co-exceedance. The European Journal of Finance, 24(5), pp. 391-412.

Hung, N.T. (2019). An analysis of CEE equity market integration and their volatility spillover effects. European Journal of Management and Business Economics, 29(1), pp. 23-40.

Longin, F. and Solnik, B. (2001). Extreme correlation of international equity markets. Journal of Finance, 56(2), pp. 649–676.

Moagăr-Poladian, S. et al. (2019). The Comovement of Exchange Rates and Stock Markets in Central and Eastern Europe. Sustainability, 11, 3985.

Reboredo J. C. et al. (2015). An analysis of dependence between Central and Eastern European stock markets. Economic Systems, 39(3), pp. 474-490.

Syllignakis, M. N. and Kouretas, G. P. (2011). Dynamic Correlation Analysis of Financial Contagion: Evidence from the Central and Eastern European Markets. International Review of Economics & Finance, 20(4), pp. 717–732.

Tilfani O. et al. (2020). Revisiting stock market integration in Central and Eastern European stock markets with a dynamic analysis. Post-Communist Economies, 32(5), pp. 643-674.

Visegrad Group (1991): Declaration on Cooperation between the Czech and Slovak Federal Republic, the Republic of Poland and the Republic of Hungary in Striving for European Integration. Retrieved from:

Vychytilova, J. (2018). Stock market development beyond the GFC: the case of V4 countries. Journal of Competitiveness, 10, pp. 149-163.

Wang P. and Moore, T. (2008). Stock market integration for the transition economies: time‐varying conditional correlation approach. The Manchester School, 76: 116-133.

Živkov D. et al. (2019). Time-frequency nexus between the eastern European and the developed stock markets – the case of Visegrad Group. School of Business, 1, pp. 15-31.






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