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Journal of Financial Econometrics Advance Access published online on May 8, 2008
Journal of Financial Econometrics, doi:10.1093/jjfinec/nbn005
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oupjournals.org

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

Denise R. Osborn
     University of Manchester

Christos S. Savva
     Economics Research Centre, University of Cyprus

Len Gill
     University of Manchester

Address correspondence to Denise Osborn, Economics, School of Social Sciences, University of Manchester, UK. Tel.: +44-161-275-4861; e-mail: denise.osborn{at}manchester.ac.uk

JEL Classification: G10, G12, G22


  Abstract

This study extends the dynamic conditional correlation model of Engle (2002, Journal of Business and Economic Statistics 20, 339–350) to allow periodic (day-specific) conditional correlations of shocks across international stock markets. The properties of the resulting periodic dynamic conditional correlation (PDCC) model are examined, focusing particularly on stationarity and the implications for unconditional shock correlations. When applied to the intraweek interactions between six developed European stock markets and the United States over 1993–2005, we find very strong evidence of periodic conditional correlations for the shocks. The highest correlations are generally observed on Thursdays, with these sometimes being twice those on Monday or Tuesday. In addition to these PDCC effects, strong day-of-the-week effects are found in mean returns for the French, Italian, and Spanish stock markets, while periodic effects are also present in volatility for all stock markets except Italy.

KEYWORDS: Day-of-the-week-effect, dynamic conditional correlations, periodic models, volatility

The authors would like to thank Ralf Becker, Mardi Dungey, Dick van Dijk, together with two anonymous referees and the editor of the journal, for their constructive comments on this work. We are also grateful to Richard Paap for providing us with Gauss routines, which were modified and used for the estimations of the periodic AR-EGARCH model. An earlier version of this paper constituted a chapter of the second author's PhD thesis at the University of Manchester, and he would like to acknowledge financial support from the University of Manchester. The second author would also like to thank Alexandra Petridou.

Received April 24, 2007; revised February 18, 2008; accepted February 29, 2008


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