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Measuring spillover effects in Euro area financial markets: a disaggregate approach

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  • Dimitrios Louzis

Abstract

This study examines the return (price) and volatility (uncertainty) spillovers among the money, stock, foreign exchange and bond markets in the Euro area. The analysis is conducted in a disaggregated manner with respect to the bond and stock indices and utilizes the generalized forecast error variance decomposition framework of a VAR model proposed by Diebold and Yilmaz (Int J Forecast 23:57–66, 2012 ). The asymptotic distribution of the generalized forecast error variance decomposition components and the corresponding standard errors are also derived. Our empirical results, based on a data set covering a twelve-year period (2000–2012), suggest a high level of total return and volatility spillover effects throughout the sample period. Stock markets across the Euro area countries are identified as the main transmitters of price spillovers, with the periphery countries transmitting the largest amount of spillovers during the crisis periods. Stock markets also play a key role in uncertainty transmission, but now, the propagation mechanism includes the core Euro area countries, which transmit volatility spillovers diachronically. The money, FX and bond markets are constant receivers of spillovers, with the exception of the Greek bonds, which transmitted spillovers during the peak of the Greek sovereign debt crisis in 2011–2012. Copyright Springer-Verlag Berlin Heidelberg 2015

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  • Dimitrios Louzis, 2015. "Measuring spillover effects in Euro area financial markets: a disaggregate approach," Empirical Economics, Springer, vol. 49(4), pages 1367-1400, December.
  • Handle: RePEc:spr:empeco:v:49:y:2015:i:4:p:1367-1400
    DOI: 10.1007/s00181-014-0911-x
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    2. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying – the case of multivariate GARCH models," Economics Working Paper Series 1517, University of St. Gallen, School of Economics and Political Science.
    3. Tom Pak Wing FongAuthor-Workplace-Name: Research Department, Hong Kong Monetary Authority & Ka Fai LiAuthor-Workplace-Name: Research Department, Hong Kong Monetary Authority & Angela Kin Wan Sze, 2016. "Measuring Spillovers between the US and Emerging Markets," Working Papers 082016, Hong Kong Institute for Monetary Research.
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    7. Aristeidis Samitas & Elias Kampouris & Zaghum Umar, 2022. "Financial contagion in real economy: The key role of policy uncertainty," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1633-1682, April.
    8. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
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    10. Sawsen Bouker & Faysal Mansouri, 2022. "Sovereign contagion risk measure across financial markets in the eurozone: a bivariate copulas and Markov Regime Switching ARMA based approaches," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 158(2), pages 615-711, May.
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    13. Prasad, Nalin & Grant, Andrew & Kim, Suk-Joong, 2018. "Time varying volatility indices and their determinants: Evidence from developed and emerging stock markets," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 115-126.
    14. Jose Arreola Hernandez & Sang Hoon Kang & Ron P. McIver & Seong-Min Yoon, 2021. "Network Interdependence and Optimization of Bank Portfolios from Developed and Emerging Asia Pacific Countries," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 613-647, December.
    15. Jose Arreola Hernandez & Sang Hoon Kang & Seong‐Min Yoon, 2022. "Interdependence and portfolio optimisation of bank equity returns from developed and emerging Europe," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 678-696, January.
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