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

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  • Christos S. Savva
  • Denise R. Osborn
  • Len Gill
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.

Suggested Citation

  • Christos S. Savva & Denise R. Osborn & Len Gill, 2006. "Periodic Dynamic Conditional Correlations between Stock Markets in Europe and the US," Centre for Growth and Business Cycle Research Discussion Paper Series 77, Economics, The University of Manchester.
    • Handle: RePEc:man:cgbcrp:77
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    3. Aknouche Abdelhakim & Demmouche Nacer & Dimitrakopoulos Stefanos & Touche Nassim, 2020. "Bayesian analysis of periodic asymmetric power GARCH models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-24, September.
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    5. Aknouche, Abdelhakim & Demmouche, Nacer & Touche, Nassim, 2018. "Bayesian MCMC analysis of periodic asymmetric power GARCH models," MPRA Paper 91136, University Library of Munich, Germany.
    6. Aknouche, Abdelhakim, 2013. "Periodic autoregressive stochastic volatility," MPRA Paper 69571, University Library of Munich, Germany, revised 2015.
    7. Iglesias, Emma M., 2015. "Value at Risk and expected shortfall of firms in the main European Union stock market indexes: A detailed analysis by economic sectors and geographical situation," Economic Modelling, Elsevier, vol. 50(C), pages 1-8.
    8. Georgios Bampinas & Stilianos Fountas & Theodore Panagiotidis, 2015. "The day-of-the-week effect is weak: Evidence from the European Real Estate Sector," Discussion Paper Series 2015_02, Department of Economics, University of Macedonia, revised May 2015.
    9. Aknouche, Abdelhakim & Al-Eid, Eid & Demouche, Nacer, 2016. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," MPRA Paper 75770, University Library of Munich, Germany, revised 19 Dec 2016.
    10. Regnard, Nazim & Zakoïan, Jean-Michel, 2011. "A conditionally heteroskedastic model with time-varying coefficients for daily gas spot prices," Energy Economics, Elsevier, vol. 33(6), pages 1240-1251.
    11. Aslanidis, Nektarios & Fernández Bariviera, Aurelio & Savva, Christos S., 2020. "Weekly dynamic conditional correlations among cryptocurrencies and traditional assets," Working Papers 2072/417680, Universitat Rovira i Virgili, Department of Economics.
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    13. Abdelhakim Aknouche & Eid Al-Eid & Nacer Demouche, 2018. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," Statistical Inference for Stochastic Processes, Springer, vol. 21(3), pages 485-511, October.

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