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Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?

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  • Wang, Gang-Jin
  • Xie, Chi
  • Zhao, Longfeng
  • Jiang, Zhi-Qiang

Abstract

Using the volatility spillover network of Diebold and Yilmaz (2014), we investigate volatility connectedness in the Chinese banking system based on daily range-based volatility series of 14 publicly-traded commercial banks from 2008 to 2016. Both static and dynamic total connectedness show that the 14 commercial banks are highly interconnected. Total directional connectedness (including from-connectedness, to-connectedness and net-connectedness) shows that state-owned commercial banks contribute less to volatility connectedness than joint-stock and city commercial banks, and that city commercial banks are the largest (net-) emitters of volatility connectedness. Statically, we find a positive (negative) rank correlation between size and from-connectedness (to-connectedness and net-connectedness) of banks. Dynamically, however, the positive rank correlation loses its statistical significance and the negative rank correlation disappears completely during the recent global financial crisis and “the 2015–2016 Chinese stock market turbulence.” Our findings suggest (i) that a bank might be “too big to fail,” but not necessarily “too interconnected to fail” and vice versa, and (ii) that these two cases may coexist conditional on the system being in distress.

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  • Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
  • Handle: RePEc:eee:intfin:v:57:y:2018:i:c:p:205-230
    DOI: 10.1016/j.intfin.2018.07.008
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    References listed on IDEAS

    as
    1. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    2. Vít Bubák & Evžen Kocenda & Filip Zikes, 2010. "Volatility Transmission in Emerging European Foreign Exchange Markets," CESifo Working Paper Series 3063, CESifo Group Munich.
    3. Jozef Baruník, Evzen Kocenda and Lukáa Vácha, 2015. "Volatility Spillovers Across Petroleum Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    4. repec:dau:papers:123456789/11708 is not listed on IDEAS
    5. 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.
    6. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    7. FrancisX. 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.
    8. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    9. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    10. 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.
    11. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    12. repec:wly:japmet:v:33:y:2018:i:1:p:1-15 is not listed on IDEAS
    13. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    14. repec:oup:rfinst:v:30:y:2017:i:1:p:48-79. is not listed on IDEAS
    15. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    16. Banulescu, Georgiana-Denisa & Dumitrescu, Elena-Ivona, 2015. "Which are the SIFIs? A Component Expected Shortfall approach to systemic risk," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 575-588.
    17. Nikola Tarashev & Claudio Borio & Kostas Tsatsaronis, 2010. "Attributing systemic risk to individual institutions," BIS Working Papers 308, Bank for International Settlements.
    18. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    19. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Intra- and inter-regional return and volatility spillovers across emerging and developed markets: Evidence from stock indices and stock index futures," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 96-114.
    20. repec:eee:jrpoli:v:53:y:2017:i:c:p:88-102 is not listed on IDEAS
    21. Bubák, Vít & Kocenda, Evzen & Zikes, Filip, 2011. "Volatility transmission in emerging European foreign exchange markets," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2829-2841, November.
    22. 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.
    23. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," Multinational Finance Journal, Multinational Finance Journal, vol. 4(3-4), pages 159-179, September.
    24. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
    25. Apergis, Nicholas & Lau, Marco Chi Keung & Yarovaya, Larisa, 2016. "Media sentiment and CDS spread spillovers: Evidence from the GIIPS countries," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 50-59.
    26. 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.
    27. Jozef Baruník & Evžen Kocenda & Lukáš Vácha, 2015. "Asymmetric Connectedness on the U.S. Stock Market: Bad and Good Volatility Spillover," CESifo Working Paper Series 5305, CESifo Group Munich.
    28. Zhang, Bing & Wang, Peijie, 2014. "Return and volatility spillovers between china and world oil markets," Economic Modelling, Elsevier, vol. 42(C), pages 413-420.
    29. repec:mes:chinec:v:50:y:2017:i:1:p:34-58 is not listed on IDEAS
    30. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    31. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Eugene Stanley, H., 2016. "Who are the net senders and recipients of volatility spillovers in China’s financial markets?," Finance Research Letters, Elsevier, vol. 18(C), pages 255-262.
    32. Dongweí Su, 2003. "Risk, Return and Regulation in Chinese Stock Markets," World Scientific Book Chapters,in: Chinese Stock Markets A Research Handbook, chapter 3, pages 75-122 World Scientific Publishing Co. Pte. Ltd..
    33. Chen Zhou, 2010. "Are Banks Too Big to Fail? Measuring Systemic Importance of Financial Institutions," International Journal of Central Banking, International Journal of Central Banking, vol. 6(34), pages 205-250, December.
    34. Yilmaz, Kamil, 2010. "Return and volatility spillovers among the East Asian equity markets," Journal of Asian Economics, Elsevier, vol. 21(3), pages 304-313, June.
    35. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Volatility spillovers across stock index futures in Asian markets: Evidence from range volatility estimators," Finance Research Letters, Elsevier, vol. 17(C), pages 158-166.
    36. Dimitrios Bisias & Mark Flood & Andrew W. Lo & Stavros Valavanis, 2012. "A Survey of Systemic Risk Analytics," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 255-296, October.
    37. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    38. Sugimoto, Kimiko & Matsuki, Takashi & Yoshida, Yushi, 2014. "The global financial crisis: An analysis of the spillover effects on African stock markets," Emerging Markets Review, Elsevier, vol. 21(C), pages 201-233.
    39. Antonakakis, Nikolaos, 2012. "Exchange return co-movements and volatility spillovers before and after the introduction of euro," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1091-1109.
    40. Christian Brownlees & Robert F. Engle, 2017. "SRISK: A Conditional Capital Shortfall Measure of Systemic Risk," Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 48-79.
    41. Fifield, Suzanne G.M. & Jetty, Juliana, 2008. "Further evidence on the efficiency of the Chinese stock markets: A note," Research in International Business and Finance, Elsevier, vol. 22(3), pages 351-361, September.
    42. Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Commodity Connectedness," Central Banking, Analysis, and Economic Policies Book Series, in: Enrique G. Mendoza & Ernesto Pastén & Diego Saravia (ed.), Monetary Policy and Global Spillovers: Mechanisms, Effects and Policy Measures, edition 1, volume 25, chapter 4, pages 097-136, Central Bank of Chile.
    43. Julien Chevallier & Florian Ielpo, 2013. "Volatility spillovers in commodity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 20(13), pages 1211-1227, September.
    44. repec:bla:asiapr:v:12:y:2017:i:2:p:303-320 is not listed on IDEAS
    45. Fu, Xiaoqing (Maggie) & Heffernan, Shelagh, 2009. "The effects of reform on China's bank structure and performance," Journal of Banking & Finance, Elsevier, vol. 33(1), pages 39-52, January.
    46. Andersen, Torben G. & Bollerslev, Tim & Cai, Jun, 2000. "Intraday and interday volatility in the Japanese stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 10(2), pages 107-130, June.
    47. repec:taf:quantf:v:17:y:2017:i:9:p:1417-1433 is not listed on IDEAS
    48. Darrat, Ali F & Zhong, Maosen, 2000. "On Testing the Random-Walk Hypothesis: A Model-Comparison Approach," The Financial Review, Eastern Finance Association, vol. 35(3), pages 105-124, August.
    49. Jonathan A. Batten & Cetin Ciner & Brian M. Lucey, 2015. "Which precious metals spill over on which, when and why? Some evidence," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 466-473, April.
    50. Mookerjee, Rajen & Yu, Qiao, 1999. "An empirical analysis of the equity markets in China," Review of Financial Economics, Elsevier, vol. 8(1), pages 41-60, June.
    51. Maghyereh, Aktham I. & Awartani, Basel & Bouri, Elie, 2016. "The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 57(C), pages 78-93.
    52. Liow, Kim Hiang, 2015. "Volatility spillover dynamics and relationship across G7 financial markets," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 328-365.
    53. Hung, Jui-Cheng, 2009. "Deregulation and liberalization of the Chinese stock market and the improvement of market efficiency," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 843-857, August.
    54. repec:eee:eneeco:v:66:y:2017:i:c:p:108-115 is not listed on IDEAS
    55. Brian M. Lucey & Charles Larkin & Fergal O'Connor, 2014. "Gold markets around the world - who spills over what, to whom, when?," Applied Economics Letters, Taylor & Francis Journals, vol. 21(13), pages 887-892, September.
    56. repec:mes:emfitr:v:51:y:2015:i:4:p:701-713 is not listed on IDEAS
    57. Zhou, Xiangyi & Zhang, Weijin & Zhang, Jie, 2012. "Volatility spillovers between the Chinese and world equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 247-270.
    58. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
    59. 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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    1. repec:eee:ecolet:v:176:y:2019:i:c:p:103-108 is not listed on IDEAS
    2. repec:eee:finana:v:60:y:2018:i:c:p:98-114 is not listed on IDEAS

    More about this item

    Keywords

    Volatility spillovers; Connectedness; Commercial banks; Chinese banking system; Financial regulation; Financial network;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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