Downside and upside risk spillovers from commercial banks into China’s financial system: a new copula quantile regression-based CoVaR model

References

• Abadie, A. (2002). Bootstrap tests for distributional treatment effects in instrumental variable models. Journal of the American Statistical Association, 97(457), 284–292. https://doi.org/10.1198/016214502753479419
   Web of Science ®Google Scholar
• Acharya, V., Engle, R., & Richardson, M. (2012). Capital shortfall: A new approach to ranking and regulating systemic risks. American Economic Review, 102(3), 59–64. https://doi.org/10.1257/aer.102.3.59
   Web of Science ®Google Scholar
• Acharya, V., Pedersen, L. H., Philippon, T., & Richardson, M. (2017). Measuring systemic risk. Review of Financial Studies, 30(1), 2–47. https://doi.org/10.1093/rfs/hhw088
   Web of Science ®Google Scholar
• Adams, Z., Füss, R., & Gropp, R. (2014). Spillover effects among financial institutions: A state-dependent sensitivity value-at-risk approach. Journal of Financial and Quantitative Analysis, 49(3), 575–598. https://doi.org/10.1017/S0022109014000325
   Web of Science ®Google Scholar
• Adrian, T., & Brunnermeier, M. K. (2016). CoVaR. American Economic Review, 106(7), 1705–1741. https://doi.org/10.1257/aer.20120555
   Web of Science ®Google Scholar
• Ameur, H. B., Jawadi, F., Jawadi, N., & Cheffou, A. I. (2020). Assessing downside and upside risk spillovers across conventional and socially responsible stock markets. Economic Modelling, 88, 200–210. https://doi.org/10.1016/j.econmod.2019.09.023
   Web of Science ®Google Scholar
• Bernal, O., Gnabo, J. Y., & Guilmin, G. (2014). Assessing the contribution of banks, insurance and other financial services to systemic risk. Journal of Banking & Finance, 47, 270–287. https://doi.org/10.1016/j.jbankfin.2014.05.030
   Web of Science ®Google Scholar
• Bernardi, M., Maruotti, A., & Petrella, L. (2017). Multiple risk measures for multivariate dynamic heavy-tailed models. Journal of Empirical Finance, 43, 1–32. https://doi.org/10.1016/j.jempfin.2017.04.005
   Web of Science ®Google Scholar
• Billio, M., Getmansky, M., Lo, A. W., & Pelizzon, L. (2012). Econometric measures of connectedness and systemic risk in the finance and insurance sectors. Journal of Financial Economics, 104(3), 535–559. https://doi.org/10.1016/j.jfineco.2011.12.010
   Web of Science ®Google Scholar
• Bisias, D., Flood, M. D., Lo, A. W., & Valavanis, S. (2012). A survey of systemic risk analytics. U.S. Department of Treasury, Office of Financial Research No. 0001, https://ssrn.com/abstract=1983602 or https://doi.org/10.2139/ssrn.1983602.
   Google Scholar
• Borri, N., & Giorgio, G. D. (2022). Systemic risk and the COVID challenge in the European banking sector. Journal of Banking & Finance, 140, 106073. https://doi.org/10.1016/j.jbankfin.2021.106073
   Web of Science ®Google Scholar
• Bouyé, E., & Salmon, M. (2009). Dynamic copula quantile regressions and tail area dynamic dependence in forex markets. The European Journal of Finance, 15(7-8), 721–750. https://doi.org/10.1080/13518470902853491
   Web of Science ®Google Scholar
• Brownlees, C., & Engle, R. (2017). SRISK: A conditional capital shortfall measure of systemic risk. Review of Financial Studies, 30(1), 48–79. https://doi.org/10.1093/rfs/hhw060
   Web of Science ®Google Scholar
• Charpentier, A., & Segers, J. (2007). Lower tail dependence for Archimedean copulas: Characterizations and pitfalls. Insurance: Mathematics and Economics, 40(3), 525–532.
   Web of Science ®Google Scholar
• Dell’Ariccia, G., Igan, D., Laeven, L., & Tong, H. (2016). Credit booms and macrofinancial stability. Economic Policy, 31(86), 299–355. https://doi.org/10.1093/epolic/eiw002
   Web of Science ®Google Scholar
• Fan, X. Q., Du, M. D., & Long, W. (2017). Risk spillover effect of Chinese commercial banks: Based on indicator method and CoVAR approach. Procedia Computer Science, 122, 932–940. https://doi.org/10.1016/j.procs.2017.11.457
   Google Scholar
• Ghulam, Y., & Doering, J. (2018). Spillover effects among financial institutions within Germany and the United Kingdom. Research in International Business and Finance, 44, 49–63. https://doi.org/10.1016/j.ribaf.2017.03.004
   Web of Science ®Google Scholar
• Girardi, G., & Ergün, A. (2013). Systemic risk measurement: Multivariate GARCH estimation of CoVaR. Journal of Banking & Finance, 37(8), 3169–3180. https://doi.org/10.1016/j.jbankfin.2013.02.027
   Web of Science ®Google Scholar
• Glasserman, P., & Young, P. (2015). How likely is contagion in financial networks? Journal of Banking & Finance, 50, 383–399. https://doi.org/10.1016/j.jbankfin.2014.02.006
   Web of Science ®Google Scholar
• Ji, Q., Liu, B., & Fan, Y. (2019). Risk dependence of CoVaR and structural change between oil prices and exchange rates: A time-varying copula model. Energy Economics, 77, 80–92. https://doi.org/10.1016/j.eneco.2018.07.012
   Web of Science ®Google Scholar
• Ji, Q., Liu, B. Y., Zhao, W. L., & Fan, Y. (2020). Modelling dynamic dependence and risk spillover between all oil price shocks and stock market returns in the BRICS. International Review of Financial Analysis, 68, 101238. https://doi.org/10.1016/j.irfa.2018.08.002
   Web of Science ®Google Scholar
• Karimalis, E. N., & Nomikos, N. K. (2018). Measuring systemic risk in the European banking sector: A copula CoVaR approach. The European Journal of Finance, 24(11), 944–975. https://doi.org/10.1080/1351847X.2017.1366350
   Web of Science ®Google Scholar
• Koenker, R. (2005). Quantile regression. Cambridge University Press.
   Google Scholar
• Kolari, J. W., Lopez-Iturriaga, F. J., & Sanz, I. P. (2020). Measuring systemic risk in the US Banking system. Economic Modelling, 91, 646–658. https://doi.org/10.1016/j.econmod.2019.12.005
   Web of Science ®Google Scholar
• Laeven, L., Ratnovski, L., & Tong, H. (2016). Bank size, capital, and systemic risk: Some international evidence. Journal of Banking & Finance, 69, S25–S34. https://doi.org/10.1016/j.jbankfin.2015.06.022
   Web of Science ®Google Scholar
• Lin, E. M. H., Sun, E. W., & Yu, M. T. (2018). Systemic risk, financial markets, and performance of financial institutions. Annals of Operations Research, 262(2), 579–603. https://doi.org/10.1007/s10479-016-2113-8
   Web of Science ®Google Scholar
• López-Espinosa, G., Moreno, A., Rubia, A., & Valderrama, L. (2015). Systemic risk and asymmetric responses in the financial industry. Journal of Banking & Finance, 58(152), 471–485. https://doi.org/10.1016/j.jbankfin.2015.05.004
   Google Scholar
• Medina-Olivares, V., Calabrese, R., Dong, Y. Z., & Shi, B. F. (2022). Spatial dependence in microfinance credit default. International Journal of Forecasting, 38(3), 1071–1085. https://doi.org/10.1016/j.ijforecast.2021.05.009
   Web of Science ®Google Scholar
• Nelsen, R. B. (2006). An introduction to copulas (2nd ed.). Springer.
   Google Scholar
• Ouyang, Z. S., Huang, Y., Jia, Y., & Luo, C. Q. (2020). Measuring systemic risk contagion effect of the banking industry in China: A directed network approach. Emerging Markets Finance and Trade, 56(6), 1312–1335. https://doi.org/10.1080/1540496X.2019.1711368
   Web of Science ®Google Scholar
• Pham, T. N., Powell, R., & Bannigidadmath, D. (2021). Systemically important banks in Asian emerging markets: Evidence from four systemic risk measures. Pacific-Basin Finance Journal, 70, 101670. https://doi.org/10.1016/j.pacfin.2021.101670
   Web of Science ®Google Scholar
• Raffestin, L. (2014). Diversification and systemic risk. Journal of Banking & Finance, 46, 85–106. https://doi.org/10.1016/j.jbankfin.2014.05.014
   Web of Science ®Google Scholar
• Reboredo, J., & Ugolini, A. (2015). Systemic risk in European sovereign debt markets: A CoVaR-copula approach. Journal of International Money and Finance, 51(3), 214–244. https://doi.org/10.1016/j.jimonfin.2014.12.002
   Google Scholar
• Reboredo, J., Rivera-Castro, M., & Ugolini, A. (2016). Downside and upside risk spillovers between exchange rates and stock prices. Journal of Banking & Finance, 62, 76–96. https://doi.org/10.1016/j.jbankfin.2015.10.011
   Web of Science ®Google Scholar
• Roukny, T., Battiston, S., & Stiglitz, J. E. (2018). Interconnectedness as a source of uncertainty in systemic risk. Journal of Financial Stability, 35(4), 93–106. https://doi.org/10.1016/j.jfs.2016.12.003
   Google Scholar
• Sun, Y., Chai, N. N., Dong, Y. Z., & Shi, B. F. (2022). Assessing and predicting small industrial enterprises’ credit ratings: A fuzzy decision making approach. International Journal of Forecasting, 38(3), 1158–1172. https://doi.org/10.1016/j.ijforecast.2022.01.006
   Web of Science ®Google Scholar
• Teply, P., & Kvapilikova, I. (2017). Measuring systemic risk of the US banking sector in time-frequency domain. Journal of Economics and Finance, 42, 461–472.
   Web of Science ®Google Scholar
• Tiwari, A. K., Jena, S. K., Kumar, S., & Hille, E. (2022). Is oil price risk systemic to sectoral equity markets of an oil importing country? Evidence from a dependence-switching copula delta CoVaR approach. Annals of Operations Research, 315(1), 429–461. https://doi.org/10.1007/s10479-021-04218-6
   Web of Science ®Google Scholar
• Wang, G. J., Xie, C., He, K., & Stanley, H. E. (2017). Extreme risk spillover network: Application to financial institutions. Quantitative Finance, 17(9), 1417–1433. https://doi.org/10.1080/14697688.2016.1272762
   Web of Science ®Google Scholar
• Wang, G. J., Xie, C., Zhao, L. F., & Jiang, Z. Q. (2018). Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more? Journal of International Financial Markets, Institutions & Money, 57, 205–230. https://doi.org/10.1016/j.intfin.2018.07.008
   Web of Science ®Google Scholar
• Warshaw, E. (2019). Extreme dependence and risk spillovers across North American equity markets. The North American Journal of Economics and Finance, 47, 237–251. https://doi.org/10.1016/j.najef.2018.12.012
   Web of Science ®Google Scholar
• Xiao, Y. (2020). The risk spillovers from the Chinese stock market to major East Asian stock markets: A MSGARCH-EVT-copula approach. International Review of Economics & Finance, 65, 173–186. https://doi.org/10.1016/j.iref.2019.10.009
   Web of Science ®Google Scholar
• Xu, Q., Chen, L., Jiang, C., & Jing, Y. (2018). Measuring systemic risk of the banking industry in China: A DCC-MIDAS-t approach. Pacific-Basin Finance Journal, 51, 13–31. https://doi.org/10.1016/j.pacfin.2018.05.009
   Web of Science ®Google Scholar
• Xu, Q., Jin, B., & Jiang, C. (2021). Measuring systemic risk of the Chinese banking industry: A wavelet-based quantile regression approach. The North American Journal of Economics and Finance, 55, 101354. https://doi.org/10.1016/j.najef.2020.101354
   Web of Science ®Google Scholar
• Yang, J., Yu, Z. L., & Ma, J. (2019). China’s financial network with international spillovers: A first look. Pacific-Basin Finance Journal, 58, 101222. https://doi.org/10.1016/j.pacfin.2019.101222
   Web of Science ®Google Scholar
• Yang, K., Wei, Y., Li, S. W., & He, J. M. (2020). Asymmetric risk spillovers between Shanghai and Hong Kong stock markets under China’s capital account liberalization. The North American Journal of Economics and Finance, 51, 101100. https://doi.org/10.1016/j.najef.2019.101100
   Web of Science ®Google Scholar
• Yang, Z., & Li, D. (2018). An investigation of the systemic risk of Chinese banks: An application based on leave-one-out. Economic Research, 8, 36–51.
   Google Scholar
• Ye, J., Zhang, A., & Dong, Y. (2019). Banking reform and industry structure: Evidence from China. Journal of Banking & Finance, 104, 70–84. https://doi.org/10.1016/j.jbankfin.2019.05.004
   Web of Science ®Google Scholar
• Zhu, X. (2021). The varying shadow of China’s banking system. Journal of Comparative Economics, 49(1), 135–146. https://doi.org/10.1016/j.jce.2020.07.006
   Web of Science ®Google Scholar