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The dynamic volatility transmission in the multiscale spillover network of the international stock market

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  • Liu, Xueyong
  • Jiang, Cheng

Abstract

Describing the characteristics of volatility contagion in the financial market is beneficial to market participants and regulators capturing market information and preventing a wide range of financial crises. We proposed a novel propagation model by introducing a dimension of intensity to the traditional discrete virus propagation model. Several indexes are constructed to describe the simulation results. The main contribution of this paper is a novel research framework proposed for studying the nonlinear dynamics process of volatility contagion among directed weighted spillover networks; this framework can enrich the research on the prevention and control of volatility transmission in financial networks. The results show the heterogeneity of volatility propagation at the microscopic level at different scales, and the risk of volatility diffusion is high in the early steps and then decreases rapidly. The results can provide a reference for investors with heterogeneous strategies at different time scales.

Suggested Citation

  • Liu, Xueyong & Jiang, Cheng, 2020. "The dynamic volatility transmission in the multiscale spillover network of the international stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
  • Handle: RePEc:eee:phsmap:v:560:y:2020:i:c:s0378437120305987
    DOI: 10.1016/j.physa.2020.125144
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    as
    1. Jiang, Yonghong & Lao, Jiashun & Mo, Bin & Nie, He, 2018. "Dynamic linkages among global oil market, agricultural raw material markets and metal markets: An application of wavelet and copula approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 265-279.
    2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    3. Bashir, Usman & Yu, Yugang & Hussain, Muntazir & Zebende, Gilney F., 2016. "Do foreign exchange and equity markets co-move in Latin American region? Detrended cross-correlation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 889-897.
    4. Cao, Guangxi & Zhang, Qi & Li, Qingchen, 2017. "Causal relationship between the global foreign exchange market based on complex networks and entropy theory," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 36-44.
    5. Shahzad, Syed Jawad Hussain & Mensi, Walid & Hammoudeh, Shawkat & Rehman, Mobeen Ur & Al-Yahyaee, Khamis H., 2018. "Extreme dependence and risk spillovers between oil and Islamic stock markets," Emerging Markets Review, Elsevier, vol. 34(C), pages 42-63.
    6. Santiago Gamba-Santamaria & Jose Eduardo Gomez-Gonzalez & Jorge Luis Hurtado-Guarin & Luis Fernando Melo-Velandia, 2019. "Volatility spillovers among global stock markets: measuring total and directional effects," Empirical Economics, Springer, vol. 56(5), pages 1581-1599, May.
    7. Liu, Qian & Li, Huajiao & Liu, Xueyong & Jiang, Meihui, 2018. "Information networks in the stock market based on the distance of the multi-attribute dimensions between listed companies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 505-513.
    8. Silva, Thiago Christiano & de Souza, Sergio Rubens Stancato & Tabak, Benjamin Miranda, 2016. "Structure and dynamics of the global financial network," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 218-234.
    9. Zhang, Weiping & Zhuang, Xintian, 2019. "The stability of Chinese stock network and its mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 748-761.
    10. Liu, Xueyong & An, Haizhong & Huang, Shupei & Wen, Shaobo, 2017. "The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 374-383.
    11. Shupei Huang & Haizhong An & Xiangyun Gao & Meihui Jiang, 2016. "The Multiscale Fluctuations of the Correlation between Oil Price and Wind Energy Stock," Sustainability, MDPI, vol. 8(6), pages 1-14, June.
    12. Li, Xun & Cao, Lang, 2016. "Diffusion processes of fragmentary information on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 624-634.
    13. Alexander Haluszczynski & Ingo Laut & Heike Modest & Christoph Rath, 2017. "Linear and nonlinear market correlations: characterizing financial crises and portfolio optimization," Papers 1712.02661, arXiv.org.
    14. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    15. Zhou, Qi & Sun, Shaolong & Liu, Qian, 2019. "The capital flow of stock market studies based on epidemic model with double delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    16. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang & Uryasev, Stan, 2016. "A financial network perspective of financial institutions’ systemic risk contributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 183-196.
    17. Jaroslaw Kwapien & Pawel Oswiecimka & Stanislaw Drozdz, 2015. "Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations," Papers 1506.08692, arXiv.org, revised Nov 2015.
    18. An, Pengli & Zhou, Jinsheng & Li, Huajiao & Sun, Bowen & Shi, Yanli, 2018. "The evolutionary similarity of the co-shareholder relationship network from institutional and non-institutional shareholder perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 439-450.
    19. Pawe{l} Fiedor, 2014. "Mutual Information Rate-Based Networks in Financial Markets," Papers 1401.2548, arXiv.org.
    20. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    21. Feng, Sida & Huang, Shupei & Qi, Yabin & Liu, Xueyong & Sun, Qingru & Wen, Shaobo, 2018. "Network features of sector indexes spillover effects in China: A multi-scale view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 461-473.
    22. Michele Starnini & Mari'an Bogu~n'a & M. 'Angeles Serrano, 2019. "The interconnected wealth of nations: Shock propagation on global trade-investment multiplex networks," Papers 1901.01976, arXiv.org.
    23. Yue-Jun Zhang & Shu-Hui Li, 2019. "The impact of investor sentiment on crude oil market risks: evidence from the wavelet approach," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1357-1371, August.
    24. Sun, Edward W. & Chen, Yi-Ting & Yu, Min-Teh, 2015. "Generalized optimal wavelet decomposing algorithm for big financial data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 194-214.
    25. Shammugam, Shivenes & Rathgeber, Andreas & Schlegl, Thomas, 2019. "Causality between metal prices: Is joint consumption a more important determinant than joint production of main and by-product metals?," Resources Policy, Elsevier, vol. 61(C), pages 49-66.
    26. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    27. Li, Xiafei & Wei, Yu, 2018. "The dependence and risk spillover between crude oil market and China stock market: New evidence from a variational mode decomposition-based copula method," Energy Economics, Elsevier, vol. 74(C), pages 565-581.
    28. Qiuhong Zheng & Liangrong Song, 2018. "Dynamic Contagion of Systemic Risks on Global Main Equity Markets Based on Granger Causality Networks," Discrete Dynamics in Nature and Society, Hindawi, vol. 2018, pages 1-13, August.
    29. Binghui Wu & Tingting Duan, 2019. "Nonlinear Dynamics Characteristic of Risk Contagion in Financial Market Based on Agent Modeling and Complex Network," Complexity, Hindawi, vol. 2019, pages 1-12, June.
    30. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    31. Wang, Ze & Gao, Xiangyun & Tang, Renwu & Liu, Xueyong & Sun, Qingru & Chen, Zhihua, 2019. "Identifying influential nodes based on fluctuation conduction network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 355-369.
    32. Huang, Wei-Qiang & Wang, Dan, 2018. "Systemic importance analysis of chinese financial institutions based on volatility spillover network," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 19-30.
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    3. Bouri, Elie & Harb, Etienne, 2022. "The size of good and bad volatility shocks does matter for spillovers," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).

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