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International stock markets interactions and conditional correlations

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Author Info
Savva, Christos S.

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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.

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File URL: http://www.sciencedirect.com/science/article/B6VGT-4TX794C-1/2/88df8fd473a50e392d537397acd6a8ff
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Publisher Info
Article provided by Elsevier in its journal Journal of International Financial Markets, Institutions and Money.

Volume (Year): 19 (2009)
Issue (Month): 4 (October)
Pages: 645-661
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Handle: RePEc:eee:intfin:v:19:y:2009:i:4:p:645-661

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Web page: http://www.elsevier.com/locate/intfin

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Related research
Keywords: Multivariate GARCH models News impact surfaces Asymmetric volatility;

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This page was last updated on 2009-12-30.


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