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Networks of volatility spillovers among stock markets

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  • 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)

Abstract

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.

Suggested Citation

  • Eduard Baumohl & Evzen Kocenda & Stefan Lyocsa & Tomas Vyrost, 2016. "Networks of volatility spillovers among stock markets," KIER Working Papers 941, Kyoto University, Institute of Economic Research.
  • Handle: RePEc:kyo:wpaper:941
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    1. repec:eee:phsmap:v:490:y:2018:i:c:p:1555-1574 is not listed on IDEAS
    2. Baumöhl, Eduard & Kočenda, Evžen & Lyócsa, Štefan & Výrost, Tomáš, 2018. "Networks of volatility spillovers among stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1555-1574.
    3. repec:eee:phsmap:v:505:y:2018:i:c:p:931-940 is not listed on IDEAS

    More about this item

    Keywords

    volatility spillovers; stock markets; shock transmission; Granger causality network; spatial regression; financial crisis;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F01 - International Economics - - General - - - Global Outlook
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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