The Dynamics and Strength of Linkages between the Stock Markets in the Czech Republic, Hungary and Poland after Their EU Accession

• Autorzy: Małgorzata Doman , Ryszard Doman

Warianty tytułu

Dynamika i siła zależności pomiędzy rynkami giełdowymi Czech, Węgier i Polski po ich wejściu do Unii Europejskiej

• Języki publikacji: EN

Abstrakty

EN

We analyze the dynamics and strength of linkages between the Czech, Hungarian and Polish stock markets after the EU accession of the corresponding countries. In addition, we examine linkages between each of the markets and developed markets (European and US). The analysis is based on the daily quotations of the main representative stock indices (PX, BUX, WIG20, DAX, S&P 500) and includes the period from May 5, 2004 to July 20, 2012. The dynamics of dependencies is modeled by means of Markov-switching copula models, and the applied measures of the strength of the linkages are dynamic Spearman's rho and tail dependence coefficients. The results show that dependencies between the considered emerging markets are very sensitive on market situation, but the linkages of these markets with the developed ones are stable. (original abstract)

W pracy analizowana jest dynamika i siła powiązań pomiędzy rynkami giełdowymi Czech, Węgier i Polski. Badanie obejmuje okres po wejściu wymienionych krajów do Unii Europejskiej. Ponadto oceniamy powiązania pomiędzy każdym z wymienionych rynków a wybranymi rynkami rozwiniętymi (europejskim i amerykańskim). Analiza oparta jest na dziennych notowaniach głównych indeksów giełdowych (PX, BUX, WIG20, DAX, S&P 500) i obejmuje okres od 5 maja 2004 r. do 20 lipca 2012 r. Dynamika zależności jest opisywana za pomocą modeli kopuli z przełączaniem typu Markowa, a stosowanymi miarami siły powiązań są dynamiczne współczynniki rho Spearmana i dynamiczne współczynniki zależności w ogonach rozkładów. Uzyskane wyniki pokazują, że zależności pomiędzy rozważanymi rynkami wschodzącymi są bardzo wrażliwe na sytuację rynkową, natomiast powiązania z rynkami rozwiniętymi są stabilne. (abstrakt oryginalny)

Słowa kluczowe

EN

Financial markets; Stock markets; Stock market indexes; Spearman's rank correlation coefficient

PL

Rynki finansowe; Rynki giełdowe; Indeks giełdowy; Współczynnik korelacji rang Spearmana

• Czasopismo: Dynamic Econometric Models
• Rocznik: 2013
• Tom: 13
• Strony: 5--31

Twórcy

autor

Małgorzata Doman

• Poznań University of Economics, Poland

autor

Ryszard Doman

• Adam Mickiewicz University in Poznań, Poland

Bibliografia

• Ang, A., Bekaert, G. (2002), International Asset Allocation with Regime Shifts, Review of Financial Studies, 15, 1137-1187.
• Ang, A., Chen, J. (2002), Asymmetric Correlations of Equity Portfolios, Journal of Financial Economics 63, 443-494, DOI: http://dx.doi.org/10.1016/S0304-405X(02)00068-5.
• Bauwens, E., Laurent S., Rombouts, J.V.K. (2006), Multivariate GARCH Models: A Survey, Journal of Applied Econometrics, 21, 79-109, DOI: http://dx.doi.org/10.1002/jae.842.
• Caporale, G.M., Spagnolo, N. (2011), Stock Market Integration Between Three CEECs, Russia, and the UK, Review of International Economics, 19, 158-169, DOI: http://dx.doi.org/10.1111/j.1467-9396.2010.00938.x.
• Doman, M., Doman, R. (2012), Dependencies Between Stock Markets During the Period Including the Late-2000s Financial Crisis, Procedia Economics and Finance, 1, 108-117, DOI: http://dx.doi.org/10.1016/S2212-5671(12)00014-7.
• Doman, M., Doman, R. (2013), Dynamika powiązań polskiego rynku kapitałowego z rynkami Czech i Węgier oraz głównymi rynkami światowymi (The Dynamics of Linkages Between the Polish Stock Market and the Markets of Czech Republic, Hungary and Major World Markets), Studia Oeconomica Posnaniensia, 9.
• Doornik, J.A. (2006), An Object-oriented Matrix Programming Language - Ox™, Timberlake Consultants Ltd, London.
• Embrechts, P., McNeil, A., Straumann, D. (2002), Correlation and Dependence in Risk Management: Properties and Pitfalls, in Dempster M. (ed.) Risk Management: Value at Risk and Beyond, 176-223, Cambridge, Cambridge University Press.
• Federation of European Securities Exchanges (2013), Statistics & Market Research, Brussels (available at http://fese.eu, 16.06.2013).
• Forbes, K., Rigobon, R. (2002), No Contagion, Only Interdependence: Measuring Stock Market Comovements, Journal of Finance, 57, 2223-2261, DOI: http://dx.doi.org/10.1111/0022-1082.00494.
• Garcia R., Tsafack G. (2011), Dependence Structure and Extreme Comovements in International Equity and Bond Markets, Journal of Banking and Finance, 35, 1954-1970, DOI: http://dx.doi.org/10.1016/j.jbankfin.2011.01.003.
• Gilmore, C.G., Lucey, B. M., McManus, G.M. (2008), The Dynamics of Central European Equity Market Comovements, The Quarterly Review of Economics and Finance, 48, 605-622, DOI: http://dx.doi.org/10.1016/j.qref.2006.06.005.
• Hamilton, J.D. (1994), Time Series Analysis, Princeton University Press, Princeton.
• Hansen, P.R., Lunde, A., Nason, J.M. (2003), Choosing the Best Volatility Models: The Model Confidence Set Approach, Oxford Bulletin of Economics and Statistics, 65, 839-861.
• Hansen, P.R., Lunde, A. (2010), MulCom 2.00, an Ox™ Software Package for Multiple Comparisons, http://mit.econ.au.dk/vip_htm/alunde/mulcom/mulcom.htm.
• Hansen, P.R., Lunde, A., Nason, J.M. (2011), The Model Confidence Set, Econometrica, 79, 453-497.
• Joe, H., Xu, J.J. (1996), The Estimation Method of Inference Functions for Margins for Multivariate Models, Technical Report no. 166, Department of Statistics, University of British Columbia.
• Joe, H. (1997), Multivariate Models and Dependence Concepts, Chapman and Hall: London.
• Kiss, G.D. (2011), The Impact of Financial Interdependence on the Czech, Hungarian and Polish Interbank, Stock and Currency Market, International Journal of Management Cases 13, 555-565.
• Lambert, P., Laurent, S. (2001), Modelling Financial Time Series Using GARCH-type Models with a Skewed Student Distribution for the Innovations, Discussion Paper 0125, Institut de Statistique, Université Catholique de Louvain.
• Laurent, S. (2009), Estimating and Forecasting ARCH Models Using G@RCH™ 6, Timberlake Consultants Ltd: London.
• Nelsen, R.B. (2006), An Introduction to Copulas, New York, Springer.
• Okimoto, T. (2008), New Evidence of Asymmetric Dependence Structures in International Equity Markets, Journal of Financial and Quantitative Analysis, 43, 787-815, DOI: http://dx.doi.org/10.1017/S0022109000004294.
• Patton, A.J. (2004), On the Out-of-sample Importance of Skewness and Asymmetric Dependence for Asset Allocation, Journal of Financial Econometrics, 2, 130-168, DOI: http://dx.doi.org/10.1093/jjfinec/nbh006.
• Patton, A.J. (2006), Modelling Asymmetric Exchange Rate Dependence, International Economic Review 47, 527-556, DOI: http://dx.doi.org/10.1111/j.1468-2354.2006.00387.x.
• Patton, A.J. (2009), Copula-based Models for Financial Time Series, in T. G. Andersen, R. A. Davies, J.-P. Kreiss, and T. Mikosch (ed.) Handbook of Financial Time Series, 767-785, Berlin: Springer.
• Scheicher, M. (2001), The Comovements of Stock Markets in Hungary, Poland and the Czech Republic, International Journal of Finance & Economics, 6, 27-39, DOI: http://dx.doi.org/10.1002/ijfe.141.
• Sklar, A. (1959), Fonctions de répartition à n dimensions et leurs marges, Publications de l'Institut Statistique de l'Université de Paris, 8, 229-231.
• Trading Economic (2013), Indicators, New York. (available at http://tradingeconomics.com, 16.06.2013).
• Ülkü, N., Demirci, E. (2012), Joint Dynamics of Foreign Exchange and Stock Markets in Emerging Europe, Journal of International Financial Markets, Institutions & Money, 22, 55-86.

Identyfikatory

DOI

10.12775/DEM.2013.001