Periodic Dynamic Conditional Correlations between Stock Markets in Europe and the US

Christos Savva (), Denise Osborn and Len Gill

Centre for Growth and Business Cycle Research Discussion Paper Series from Economics, The University of Manchester

Abstract: This study extends the dynamic conditional correlation model to allow day-specific correlations of shocks across international stock markets. The properties of the resulting periodic dynamic conditional correlation (PDCC) model are examined, with the model then applied to study the intra-week interactions between six developed European stock markets and the US over the period 1993 - 2005. We find very strong evidence of periodic effects in the conditional correlations of the shocks. The highest correlations are generally observed on Thursdays, with these Thursday correlations in some cases being twice those on Monday or Tuesday. Prior to estimating the PDCC model, periodic mean and volatility effects are removed using a PAR model for returns combined with a periodic EGARCH specification for the variance equation. Strong periodic mean effects are found for returns in the French, Italian and Spanish stock markets, whereas such effects are present in volatility for all stock markets except Italy.

Pages: 34 pages
Date: 2006
New Economics Papers: this item is included in nep-eec, nep-ets and nep-mac
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Journal Article: Periodic Dynamic Conditional Correlations between Stock Markets in Europe and the US (2008)
Working Paper: Periodic Dynamic Conditional Correlations between Stock Markets in Europe and the US (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:man:cgbcrp:77

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