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Systemic Risk in Global Volatility Spillover Networks: Evidence from Option-implied Volatility Indices

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  • Yang, Zihui
  • Zhou, Yinggang

Abstract

With option-implied volatility indices, we provide a new tool for event studies in a network setting and document systemic risk in the spillover networks across global financial markets. Network linkages are sufficiently asymmetric because the US stock and bond markets play as dominant volatility suppliers to other countries and markets. Shocks from the US generate systemic risk through intensifying volatility spillovers across countries and asset classes. The findings offer new evidence that asymmetric network linkages can lead to sizable aggregate fluctuations and thus potential systemic risk.

Suggested Citation

  • Yang, Zihui & Zhou, Yinggang, 2018. "Systemic Risk in Global Volatility Spillover Networks: Evidence from Option-implied Volatility Indices," IRTG 1792 Discussion Papers 2018-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  • Handle: RePEc:zbw:irtgdp:2018003
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    References listed on IDEAS

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    10. Packham, Natalie & Woebbeking, Fabian, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," IRTG 1792 Discussion Papers 2018-034, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
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    14. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
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    16. Koziuk, Andzhey & Spokoiny, Vladimir, 2018. "Toolbox: Gaussian comparison on Eucledian balls," IRTG 1792 Discussion Papers 2018-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    17. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    19. Nasekin, Sergey & Chen, Cathy Yi-Hsuan, 2018. "Deep learning-based cryptocurrency sentiment construction," IRTG 1792 Discussion Papers 2018-066, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    20. Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

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    More about this item

    Keywords

    Network; Option-implied Volatility; Spillover; Asymmetric linkage; Systemic risk;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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