Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


2015 | 2 (48) | 100-113

Article title

Dynamika współzależności warszawskiej Giełdy Papierów Wartościowych z innymi rynkami finansowymi

Content

Title variants

EN
Dynamics of interdependence between Warsaw Stock Exchange and other financial markets

Languages of publication

PL

Abstracts

EN
The aim of this article was the search of the dynamic of dependencies between WSE and other countries coming from Europe, America and Asia. The two-dimensional time series has been modeled by multidimensional GARCH process with dynamic condi-tional correlation or by Markov-switching Copula-GARCH model. The analysis confirms the claim that dependences between financial markets are higher in a period of crisis than during the prosperity time. The dynamic of relationships between Polish market and Euro-pean markets is bigger than the dynamic of relationships between Polish market and Ameri-can or Asian markets.

Contributors

References

  • Chollete L., Heinen A., Valdesogo A., 2009, Modeling international financial returns with a multi-variate regime switching copula, Journal of Financial Econometrics, 7(4), s. 437-480.
  • Czapkiewicz A.,. Basiura B., 2014, The position of the WIG index in comparison with selected market indices in boom and bust periods, Statistics in Transition, 15(3), s. 427-436.
  • Diebold F.X., Gunther T.A., Tay A.S., 1989, Evaluating density forecasts with application to finan-cial risk management, International Economic Review 39(4), s. 863-883.
  • Doman M., Doman R., 2013, The Dynamics and Strength of Linkages between the Stock Markets in the Czech Republic, Hungary and Poland after their EU Accession, Dynamic Econometric Models, vol. 13, s. 5-31.
  • Engle R.F., 2002, Dynamic conditional correlation: a simple class of multivariate generalized auto-regressive conditional heteroskedasticity models, Journal of Business and Economic Statistics, 20, s. 339-350.
  • Forbes K., Rigobon R., 2002, No contagion, only interpedence: Measuring Stock Market Comove-ments, The Journal of Finance, 10(5), s. 2223-2261.
  • Grubel H., 1968, Internationally diversified portfolios: Welfare gains and capital Flows, American Economic Review, 58(5), s. 1299-1314.
  • Hamilton J.,1994, Time Series Analysis, Princeton University Press, Princeton.
  • Hołubowicz K., 2014, Korelacja indeksów cen akcji na globalnych rynkach finansowych, Nauki o Finansach, 2(19).
  • Jondeau E., Rockinger M., 2006, The Copula-GARCH model of conditional dependencies: An inter-national stock market application, Journal of International Money and Finance, 25, s. 827-853.
  • Kenourgios D., Samitas A., Paltalidis N., 2011, Financial crises and stock market contagion in a multivariate time-varying asymmetric framework, Journal of International Financial Markets, Institutions & Money, 21(1), s. 92-106.
  • Longin F., Solnik B., 1995,Is the correlation in international equity returns constant: (1960-1990), Journal of International Money and Finance, 14, s. 3-26.
  • Markwat T., Kole E., van Dijk D., 2009, Contagion as a domino effect in financial markets, Journal of Banking & Finance, 33(11), s. 1996-2012.
  • Patton A.J., 2009, Copula-based Models for Financial Time Series, Handbook of financial time se-ries, Springer, Berlin, s. 767-785.
  • Pekota G., 2007, Analiza zależności między indeksami rynków akcji na giełdzie polskiej i amerykań-skiej, Badania Operacyjne i Decyzje, nr 3-4, s. 133-145.
  • Rodriguez J.C., 2007, Measuring Financial Contagion: A Copula Approach, Journal of Empirical Finance, 14(3), s. 401-423.
  • Tse Y.K., Tsui A.K.C., 2002, A Multivariate Generalized Autoregressive Conditional Heteroscedas-ticity Model with Time-Varying Correlations, Journal of Business and Economic Statistics, 20, s. 351-362.
  • Sklar A., 1959, Fonctions de répartition à n Dimensions et Leurs Marges, Publication’s de l’Institut de Statistiques de l’Université de Paris, Paris, s. 229-231.
  • Vuong Q.H., 1989, Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses, Econo-metrica, 57 (2), s. 307-333.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-1f7474ee-a3f0-4bf0-9706-6371883d91d9
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.