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Macroeconomic determinants of European stock and government bond correlations: A tale of two regions

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  • Erica R. PEREGO

    (University of Luxembourg, CREA and UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES))

  • Wessel N. VERMEULEN

    (University of Luxembourg, CREA)

Abstract

This paper studies the dynamic correlation between stocks, between government bonds and between stocks and bonds within the Euro-zone in the last decade. In order to better understand the development of the financial market we argue that it is necessary to analyse all such relations simultaneously rather than focus at one. We firstly calculate the dynamic correlation for the previous asset classes. Results presented at the asset-region level, i.e. north-stock, north-bonds, south-stocks and south-bonds, visualise the divergence in integration in Europe and highlight the heterogeneity in these markets. Secondly, we study the macroeconomic factors that determine these correlations. We find that, when we allow for regional division, not only cross-asset correlations within regions behave differently from each other, but also cross-assets cross-regions dynamic correlations can be explained with macroeconomic factors such as the relative market uncertainty between countries and balance of payments dynamics.

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  • Erica R. PEREGO & Wessel N. VERMEULEN, 2013. "Macroeconomic determinants of European stock and government bond correlations: A tale of two regions," LIDAM Discussion Papers IRES 2013013, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  • Handle: RePEc:ctl:louvir:2013013
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    4. Jammazi, Rania & Tiwari, Aviral Kr. & Ferrer, Román & Moya, Pablo, 2015. "Time-varying dependence between stock and government bond returns: International evidence with dynamic copulas," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 74-93.
    5. Honghai Yu & Wencong Sun & Xiangting Ye & Libing Fang, 2019. "Measuring the increasing connectedness of Chinese assets with global assets: using a variance decompositions method," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1261-1290, March.
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    8. Fang, Libing & Yu, Honghai & Huang, Yingbo, 2018. "The role of investor sentiment in the long-term correlation between U.S. stock and bond markets," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 127-139.
    9. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Hammoudeh, Shawkat M., 2017. "Main driving factors of the interest rate-stock market Granger causality," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 260-280.
    10. Fang, Libing & Yu, Honghai & Li, Lei, 2017. "The effect of economic policy uncertainty on the long-term correlation between U.S. stock and bond markets," Economic Modelling, Elsevier, vol. 66(C), pages 139-145.
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    13. Jiang, Cuixia & Ding, Xiaoyi & Xu, Qifa & Tong, Yongbo, 2020. "A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    14. Priyanshi Gupta & Sanjay Sehgal, 2020. "Convergence of retail banking interest rates to households in euro area: time-varying measurement and determinants," International Economics and Economic Policy, Springer, vol. 17(1), pages 25-65, February.
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    16. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    17. Mohammad Alomari & Abdel Razzaq Al rababa’a & Ghaith El-Nader & Ahmad Alkhataybeh, 2021. "Who’s behind the wheel? The role of social and media news in driving the stock–bond correlation," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 959-1007, October.
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    More about this item

    Keywords

    Currency union; financial markets; time-varying correlation;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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