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Networks of volatility spillovers among stock markets

Listed author(s):
  • Eduard Baumohl

    (Institute of Economics and Management, University of Economics in Bratislava)

  • Evzen Kocenda

    ()

    (Institute of Economic Studies, Charles University)

  • Stefan Lyocsa

    ()

    (Institute of Economics and Management, University of Economics in Bratislava)

  • Tomas Vyrost

    (Institute of Economics and Management, University of Economics in Bratislava)

In our network analysis of 40 developed, emerging and frontier stock markets during the 2006?2014 period, we describe and model volatility spillovers during both the global financial crisis and tranquil periods. The resulting market interconnectedness is depicted by fitting a spatial model incorporating several exogenous characteristics. We confirm the presence of significant temporal proximity effects between markets and somewhat weaker temporal effects with regard to the US equity market ? volatility spillovers decrease when markets are characterized by greater temporal proximity. Volatility spillovers also present a high degree of interconnectedness, which is measured by high spatial autocorrelation. This finding is confirmed by spatial regression models showing that indirect effects are much stronger than direct effects, i.e., market-related changes in “neighboring” markets (within a network) affect volatility spillovers more than changes in the given market alone. Our results also link spillovers of escalating magnitude with increasing market size, market liquidity and economic openness.

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File URL: http://www.kier.kyoto-u.ac.jp/DP/DP941.pdf
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Paper provided by Kyoto University, Institute of Economic Research in its series KIER Working Papers with number 941.

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Length: 46pages
Date of creation: May 2016
Handle: RePEc:kyo:wpaper:941
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