IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v55y2021ics1062940820302357.html
   My bibliography  Save this article

Measuring systemic risk of the Chinese banking industry: A wavelet-based quantile regression approach

Author

Listed:
  • Xu, Qifa
  • Jin, Bei
  • Jiang, Cuixia

Abstract

In systemic risk measure, a large amount of literature has emerged, but few of them take into account the multi-scale natures of financial data. Considering these natures, we develop a novel W-QR-CoVaR method to measure systemic risk. To be specific, the W-QR-CoVaR method combines the wavelet multiresolution analysis (MRA) with the conditional value-at-risk (CoVaR) method based on the quantile regression (QR) framework. We then apply it to measure the systemic risk in the Chinese banking industry covering the period from September 2007 to September 2018. Our experiment results show that the hybrid W-QR-CoVaR method performs better than the traditional CoVaR method in terms of predictive accuracy. Furthermore, we also explore the relation between the systemic risk contribution of each individual bank and the bank-specific characteristics. Size and leverage appear to be the most robustness determinants. The findings suggest that regulators should pay more attention to the banks with smaller size and higher leverage.

Suggested Citation

  • Xu, Qifa & Jin, Bei & Jiang, Cuixia, 2021. "Measuring systemic risk of the Chinese banking industry: A wavelet-based quantile regression approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    • Handle: RePEc:eee:ecofin:v:55:y:2021:i:c:s1062940820302357
    DOI: 10.1016/j.najef.2020.101354
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940820302357
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2020.101354?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    3. Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    4. López-Espinosa, Germán & Moreno, Antonio & Rubia, Antonio & Valderrama, Laura, 2012. "Short-term wholesale funding and systemic risk: A global CoVaR approach," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3150-3162.
    5. Bonaccolto, Giovanni & Caporin, Massimiliano & Paterlini, Sandra, 2019. "Decomposing and backtesting a flexible specification for CoVaR," Journal of Banking & Finance, Elsevier, vol. 108(C).
    6. Bernal, Oscar & Gnabo, Jean-Yves & Guilmin, Grégory, 2014. "Assessing the contribution of banks, insurance and other financial services to systemic risk," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 270-287.
    7. Huang, Shian-Chang, 2011. "Wavelet-based multi-resolution GARCH model for financial spillover effects," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(11), pages 2529-2539.
    8. de Mendonça, Helder Ferreira & Silva, Rafael Bernardo da, 2018. "Effect of banking and macroeconomic variables on systemic risk: An application of ΔCOVAR for an emerging economy," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 141-157.
    9. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    10. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    11. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yuan, Jing, 2018. "Measuring systemic risk of the banking industry in China: A DCC-MIDAS-t approach," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 13-31.
    12. Shumaila Zeb & Abdul Rashid, 2019. "Systemic risk in financial institutions of BRICS: measurement and identification of firm-specific determinants," Risk Management, Palgrave Macmillan, vol. 21(4), pages 243-264, December.
    13. Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
    14. Christian Brownlees & Robert F. Engle, 2017. "SRISK: A Conditional Capital Shortfall Measure of Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 48-79.
    15. Meng, Xiangcai & Huang, Chia-Hsing, 2019. "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 131-148.
    16. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Systemic risk in European sovereign debt markets: A CoVaR-copula approach," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 214-244.
    17. Xu, Qifa & Li, Mengting & Jiang, Cuixia & He, Yaoyao, 2019. "Interconnectedness and systemic risk network of Chinese financial institutions: A LASSO-CoVaR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    18. Jammazi, Rania & Reboredo, Juan C., 2016. "Dependence and risk management in oil and stock markets. A wavelet-copula analysis," Energy, Elsevier, vol. 107(C), pages 866-888.
    19. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.
    20. Hua Zhou & Wenjin Liu & Liang Wang, 2020. "Systemic Risk of China’s Financial System (2007–2018): A Comparison between ΔCoVaR, MES and SRISK across Banks, Insurance and Securities Firms," Chinese Economy, Taylor & Francis Journals, vol. 53(3), pages 221-245, May.
    21. Teply, Petr & Kvapilikova, Ivana, 2017. "Measuring systemic risk of the US banking sector in time-frequency domain," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 461-472.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yao, Can-Zhong & Li, Min-Jian, 2023. "GARCH-MIDAS-GAS-copula model for CoVaR and risk spillover in stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    2. Yao, Yinhong & Li, Jingyu & Chen, Wei, 2024. "Multiscale extreme risk spillovers among the Chinese mainland, Hong Kong, and London stock markets: Comparing the impacts of three Stock Connect programs," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1217-1233.
    3. Zhao, Jing & Cui, Luansong & Liu, Weiguo & Zhang, Qiwen, 2023. "Extreme risk spillover effects of international oil prices on the Chinese stock market: A GARCH-EVT-Copula-CoVaR approach," Resources Policy, Elsevier, vol. 86(PB).
    4. Ting Yao & Liangrong Song, 2023. "Can digital transformation reduce bank systemic risk? Empirical evidence from listed banks in China," Economic Change and Restructuring, Springer, vol. 56(6), pages 4445-4463, December.
    5. Das, Sanjiv R. & Kalimipalli, Madhu & Nayak, Subhankar, 2022. "Banking networks, systemic risk, and the credit cycle in emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    6. Dai, Zhifeng & Zhu, Haoyang, 2023. "Dynamic risk spillover among crude oil, economic policy uncertainty and Chinese financial sectors," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 421-450.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2021. "Systemically important banks in Asian emerging markets: Evidence from four systemic risk measures," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    2. Morelli, David & Vioto, Davide, 2020. "Assessing the contribution of China’s financial sectors to systemic risk," Journal of Financial Stability, Elsevier, vol. 50(C).
    3. Shuting Liu & Qifa Xu & Cuixia Jiang, 2021. "Systemic risk of China’s commercial banks during financial turmoils in 2010-2020: A MIDAS-QR based CoVaR approach," Applied Economics Letters, Taylor & Francis Journals, vol. 28(18), pages 1600-1609, October.
    4. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    5. Bonaccolto, Giovanni & Caporin, Massimiliano & Paterlini, Sandra, 2019. "Decomposing and backtesting a flexible specification for CoVaR," Journal of Banking & Finance, Elsevier, vol. 108(C).
    6. Curcio, Domenico & Gianfrancesco, Igor & Vioto, Davide, 2023. "Climate change and financial systemic risk: Evidence from US banks and insurers," Journal of Financial Stability, Elsevier, vol. 66(C).
    7. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    8. Usman, Muhammad & Umar, Zaghum & Choi, Sun-Yong & Teplova, Tamara, 2024. "Quantifying endogenous and exogenous shocks to financial sector systemic risk: A comparison of GFC and COVID-19," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 281-293.
    9. Martin Waltz & Abhay Kumar Singh & Ostap Okhrin, 2022. "Vulnerability-CoVaR: investigating the crypto-market," Quantitative Finance, Taylor & Francis Journals, vol. 22(9), pages 1731-1745, September.
    10. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    11. 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.
    12. Jian, Zhihong & Wu, Shuai & Zhu, Zhican, 2018. "Asymmetric extreme risk spillovers between the Chinese stock market and index futures market: An MV-CAViaR based intraday CoVaR approach," Emerging Markets Review, Elsevier, vol. 37(C), pages 98-113.
    13. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2017. "Multiple risk measures for multivariate dynamic heavy–tailed models," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 1-32.
    14. Rahman, Md Lutfur & Troster, Victor & Uddin, Gazi Salah & Yahya, Muhammad, 2022. "Systemic risk contribution of banks and non-bank financial institutions across frequencies: The Australian experience," International Review of Financial Analysis, Elsevier, vol. 79(C).
    15. Xu, Qifa & Li, Mengting & Jiang, Cuixia & He, Yaoyao, 2019. "Interconnectedness and systemic risk network of Chinese financial institutions: A LASSO-CoVaR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    16. Wided Khiari & Salim Ben Sassi, 2019. "On Identifying the Systemically Important Tunisian Banks: An Empirical Approach Based on the △CoVaR Measures," Risks, MDPI, vol. 7(4), pages 1-15, December.
    17. Denisa Banulescu-Radu & Christophe Hurlin & Jérémy Leymarie & Olivier Scaillet, 2021. "Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures," Management Science, INFORMS, vol. 67(9), pages 5730-5754, September.
    18. Alin Marius Andrieş & Simona Nistor, 2018. "Systemic Risk and Foreign Currency Positions of Banks: Evidence from Emerging Europe," Eastern European Economics, Taylor & Francis Journals, vol. 56(5), pages 382-421, September.
    19. Shimizu, Katsutoshi & Ly, Kim Cuong, 2017. "Were regulatory interventions effective in lowering systemic risk during the financial crisis in Japan?," Journal of Multinational Financial Management, Elsevier, vol. 41(C), pages 80-91.
    20. Caporin, Massimiliano & Garcia-Jorcano, Laura & Jimenez-Martin, Juan-Angel, 2021. "TrAffic LIght system for systemic Stress: TALIS3," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:55:y:2021:i:c:s1062940820302357. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.