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Dynamic Stock Market Covariances in the Eurozone

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  • Gregory Connor

    (Department of Economics Finance and Accounting, National University of Ireland, Maynooth)

  • Anita Suurlaht

    (Department of Economics Finance and Accounting, National University of Ireland, Maynooth)

Abstract

This paper examines the short-term dynamics, macroeconomic sensitivities, and longer-term trends in the variances and covariances of national equity market index daily returns for eleven countries in the Euro currency zone. We modify Colacito, Engle and Ghysel?s Mixed Data Sampling Dynamic Conditional Correlation Garch model to include a new scalar measure for the degree of correlatedness in time-varying correlation matrices. We also explore the robustness of the fi?ndings with a less model-dependent realized covariance estimator. We fi?nd a secular trend toward higher correlation during our sample period, and signi?cant linkages between macroeconomic and market-wide variables and dynamic correlation. One notable fi?nding is that average correlation between these markets is lower when their average GDP growth rate is lower or when more of them have negative GDP growth.

Suggested Citation

  • Gregory Connor & Anita Suurlaht, 2012. "Dynamic Stock Market Covariances in the Eurozone," Economics Department Working Paper Series n222-12.pdf, Department of Economics, National University of Ireland - Maynooth.
  • Handle: RePEc:may:mayecw:n222-12.pdf
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    Cited by:

    1. Tiwari, Aviral Kumar & Mutascu, Mihai Ioan & Albulescu, Claudiu Tiberiu, 2016. "Continuous wavelet transform and rolling correlation of European stock markets," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 237-256.
    2. Turhan, M. Ibrahim & Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2014. "A view to the long-run dynamic relationship between crude oil and the major asset classes," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 286-299.
    3. Cristina Amado & Annastiina Silvennoinen & Timo Ter¨asvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," NIPE Working Papers 07/2018, NIPE - Universidade do Minho.
    4. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.
    5. Mohamed Ali Trabelsi & Salma Hmida, 2019. "Impact of the Credit Rating Revision on the Eurozone Stock Markets," Journal Transition Studies Review, Transition Academia Press, vol. 26(1), pages 3-14.
    6. Bartram, Söhnke M. & Wang, Yaw-Huei, 2015. "European financial market dependence: An industry analysis," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 146-163.
    7. Virk, Nader & Javed, Farrukh, 2017. "European equity market integration and joint relationship of conditional volatility and correlations," Journal of International Money and Finance, Elsevier, vol. 71(C), pages 53-77.
    8. Qifa Xu & Junqing Zuo & Cuixia Jiang & Yaoyao He, 2021. "A large constrained time‐varying portfolio selection model with DCC‐MIDAS: Evidence from Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3417-3435, July.
    9. Claudiu Tiberiu Albulescu & Daniel Goyeau & Aviral Kumar Tiwari, 2017. "Co-movements and contagion between international stock index futures markets," Empirical Economics, Springer, vol. 52(4), pages 1529-1568, June.
    10. Claudiu Tiberiu Albulescu & Daniel Goyeau & Aviral Kumar Tiwari, 2015. "Contagion and Dynamic Correlation of the Main European Stock Index Futures Markets: A Time-frequency Approach," Post-Print hal-01376756, HAL.
    11. Connor, Gregory & Suurlaht, Anita, 2013. "Dynamic stock market covariances in the Eurozone," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 353-370.
    12. Tsukuda, Yoshihiko & Shimada, Junji & Miyakoshi, Tatsuyoshi, 2017. "Bond market integration in East Asia: Multivariate GARCH with dynamic conditional correlations approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 193-213.
    13. Trabelsi, Mohamed Ali & Hmida, Salma, 2017. "A Dynamic Correlation Analysis of Financial Contagion: Evidence from the Eurozone Stock Markets," MPRA Paper 83718, University Library of Munich, Germany, revised 2017.
    14. Elena, Radu (Grigorie), 2022. "Financial Stability, The Objective Of Development Financial Markets," Management Strategies Journal, Constantin Brancoveanu University, vol. 55(1), pages 144-149.
    15. Xiao Jing Cai & Shuairu Tian & Shigeyuki Hamori, 2016. "Dynamic correlation and equicorrelation analysis of global financial turmoil: evidence from emerging East Asian stock markets," Applied Economics, Taylor & Francis Journals, vol. 48(40), pages 3789-3803, August.
    16. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yuan, Jing, 2018. "Measuring systemic risk of the banking industry in China: A DCC-MIDAS-t approach," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 13-31.
    17. Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.

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    More about this item

    Keywords

    : dynamic conditional correlation; multivariate GARCH; international stock market integration; European Monetary Union.;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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