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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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    6. 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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    9. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    10. Marinela Adriana Finta & Bart Frijns & Alireza Tourani-Rad, 2019. "Time-varying contemporaneous spillovers during the European Debt Crisis," Empirical Economics, Springer, vol. 57(2), pages 423-448, August.
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    13. 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.
    14. Kundan Mukhia & Anish Rai & SR Luwang & Md Nurujjaman & Sushovan Majhi & Chittaranjan Hens, 2024. "Complex network analysis of cryptocurrency market during crashes," Papers 2405.05642, arXiv.org.
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    17. 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.

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