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

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  • 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
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    Cited by:

    1. 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).
    2. 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.
    3. 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).
    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.

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