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...

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...

Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the  exibility of univariate GARCH models coupled with parsimonious parametric models for the c...

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