Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/5128
Title: International stock markets interactions and conditional correlations
International stock markets interactions and conditional correlations
Authors: Savva, Christos S. 
Keywords: Asymmetric volatility
Multivariate GARCH models
News impact surfaces
Asymmetric volatility
Multivariate GARCH models
News impact surfaces
Issue Date: 2009
Publisher: Elsevier
Elsevier
Source: Journal of International Financial Markets, Institutions and Money, 2009, Volume 19, Issue 4, Pages 645-661
Journal of International Financial Markets, Institutions and Money, 2009, Volume 19, Issue 4, Pages 645-661
Abstract: This paper investigates the transmission of price and volatility spillovers across the US and European stock markets in bivariate combinations. The framework used encompasses the most popular multivariate GARCH models, with News Impact Surfaces employed for interpretation. By using synchronous data the dynamic conditional correlation model (Engle, R., 2002. Dynamic conditional correlation: a simple class of multivariate GARCH models. Journal of Business and Economic Statistics 20, 339-350) is found to best capture the relationships for over half of the bivariate combinations of markets. Other findings include volatility spillovers from the US to European markets, and a reverse spillover. In addition, the magnitude of the correlation between markets is higher not only for negative shocks in both markets, but also when a combination of shocks of opposite signs occurs.
This paper investigates the transmission of price and volatility spillovers across the US and European stock markets in bivariate combinations. The framework used encompasses the most popular multivariate GARCH models, with News Impact Surfaces employed for interpretation. By using synchronous data the dynamic conditional correlation model (Engle, R., 2002. Dynamic conditional correlation: a simple class of multivariate GARCH models. Journal of Business and Economic Statistics 20, 339-350) is found to best capture the relationships for over half of the bivariate combinations of markets. Other findings include volatility spillovers from the US to European markets, and a reverse spillover. In addition, the magnitude of the correlation between markets is higher not only for negative shocks in both markets, but also when a combination of shocks of opposite signs occurs.
URI: http://ktisis.cut.ac.cy/handle/10488/5128
http://ktisis.cut.ac.cy/handle/10488/5128
ISSN: 10424431
10424431
DOI: 10.1016/j.intfin.2008.11.001
10.1016/j.intfin.2008.11.001
Rights: © 2008 Elsevier B.V. All rights reserved.
� 2008 Elsevier B.V. All rights reserved.
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