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Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network

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  • Yu Chen
  • Jie Hu
  • Weiping Zhang

Abstract

This paper focuses on volatility spillover effects and considers the issue of how to measure the connectedness of networks among financial firms. To assess the network connectedness of firms from different industries, we proposed a novel procedure and applied it to 20 leading financial institutions from four industries in China's stock markets. The results show that the total connectedness of the Chinese financial system was much higher during the stock market crisis between June 2015 and February 2016 than during stable periods of economic development. This analysis can be used to determine which firms play a dominant role in risk transmission throughout the entire system. It is suggested that the government should provide targeted regulatory policies to particular types of firms.

Suggested Citation

  • Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.
    • Handle: RePEc:bla:chinae:v:28:y:2020:i:6:p:78-100
    DOI: 10.1111/cwe.12357
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    as
    1. Matteo Barigozzi & Christian Brownlees, 2019. "NETS: Network estimation for time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 347-364, April.
    2. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    3. Härdle, Wolfgang Karl & Wang, Weining & Yu, Lining, 2016. "TENET: Tail-Event driven NETwork risk," Journal of Econometrics, Elsevier, vol. 192(2), pages 499-513.
    4. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    5. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    6. Fang, Libing & Sun, Boyang & Li, Huijing & Yu, Honghai, 2018. "Systemic risk network of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 190-206.
    7. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    8. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    9. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    10. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    11. repec:fip:fedhpr:y:2010:i:may:p:65-71 is not listed on IDEAS
    12. Restrepo, Natalia & Uribe, Jorge M. & Manotas, Diego, 2018. "Financial risk network architecture of energy firms," Applied Energy, Elsevier, vol. 215(C), pages 630-642.
    13. Freixas, Xavier & Parigi, Bruno M & Rochet, Jean-Charles, 2000. "Systemic Risk, Interbank Relations, and Liquidity Provision by the Central Bank," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(3), pages 611-638, August.
    14. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    15. repec:taf:jnlbes:v:30:y:2012:i:2:p:212-228 is not listed on IDEAS
    16. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    17. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    18. Constantin, Andreea & Peltonen, Tuomas A. & Sarlin, Peter, 2018. "Network linkages to predict bank distress," Journal of Financial Stability, Elsevier, vol. 35(C), pages 226-241.
    19. Yaron Leitner, 2005. "Financial Networks: Contagion, Commitment, and Private Sector Bailouts," Journal of Finance, American Finance Association, vol. 60(6), pages 2925-2953, December.
    20. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2014. "Forecasting systemic impact in financial networks," International Journal of Forecasting, Elsevier, vol. 30(3), pages 781-794.
    21. Seyed Alireza Hasheminasab & Behrouz Tork Ladani, 2018. "Security Investment in Contagious Networks," Risk Analysis, John Wiley & Sons, vol. 38(8), pages 1559-1575, August.
    22. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    23. Adams, Zeno & Füss, Roland & Gropp, Reint, 2014. "Spillover Effects among Financial Institutions: A State-Dependent Sensitivity Value-at-Risk Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 575-598, June.
    24. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2019. "Tail event driven networks of SIFIs," Journal of Econometrics, Elsevier, vol. 208(1), pages 282-298.
    25. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    26. Viral Acharya & Robert Engle & Matthew Richardson, 2012. "Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks," American Economic Review, American Economic Association, vol. 102(3), pages 59-64, May.
    27. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
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    3. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).

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