中国金融机构系统性风险回测与关联研究

doi:10.16381/j.cnki.issn1003-207x.2022.1453

Abstract

Abstract:

The premise of preventing and defusing systemic risk is to accurately measure systemic risk. Through literature review， it is known that most of the existing research focuses on the measurement of systemic risk， and there is little literature evaluating the validity and accuracy of systemic risk. In addition， it is found that most of the literature mainly discusses the risk connectedness of financial institutions in the time domain， ignoring the connecting mechanism in the frequency domain. As a result， it focusy on two issues：（1） Backtesting the systemic risk of Chinese financial institutions to examine the effectiveness of MES and ΔCoVaR. （2） Based on the backtesting results of systemic risks， the risk connectedness among financial institutions is investigated by the quantile connectedness network in frequency.In response to the above problems， the following work is done： First， the MES and ΔCoVaR of 35 financial institutions in China are backtested by the unconditional coverage test， aiming to evaluate the effectiveness of MES and ΔCoVaR. Second， the early warning system is calulated to analyze the risk evolution of the financial system. Third， the quantile connectedness networks in the frequency domain through the quantile coherence method is proposed to explore the risk connectedness among financial institutions. Finally， the connectedness importance of financial institutions on specific frequency bands is measured.It is found that　（1） During the period of financial market crisis， commonly used systemic risk indicators such as MES， CoVaR， and ΔCoVaR fail to measure the systemic risk of financial institutions. （2） Compared with the short-term and medium-term connectedness layer， Chinese financial institutions have obvious extreme risk linkage effects in the long-term connectedness layer. （3） In the short-， medium-， and long-term， small- and medium-sized financial institutions such as Bank of Ningbo， Industrial Securities， and Dongfang Energy have connectedness importance. Therefore， the regulatory authorities should pay attention to preventing the risk of "too connected to fail" of small- and medium-sized financial institutions.

Key words: systemic risk, backtesting, financial institutions

CLC Number:

F830.91

Zisheng Ouyang, Xuewei Zhou. Systemic Risk Backtesting and Connectedness of Chinese Financial Institutions: Evidence from MES and ΔCoVaR[J]. Chinese Journal of Management Science, 2025, 33(6): 14-26.

Figures/Tables 14

References 38

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序号	机构	行业	序号	机构	行业
1	中国平安	保险	19	中信银行	银行
2	中国太保	保险	20	东北证券	证券
3	中国人寿	保险	21	国元证券	证券
4	平安银行	银行	22	广发证券	证券
5	宁波银行	银行	23	长江证券	证券
6	浦发银行	银行	24	中信证券	证券
7	华夏银行	银行	25	国金证券	证券
8	民生银行	银行	26	海通证券	证券
9	招商银行	银行	27	招商证券	证券
10	南京银行	银行	28	太平洋证券	证券
11	兴业银行	银行	29	兴业证券	证券
12	北京银行	银行	30	华泰证券	证券
13	农业银行	银行	31	光大证券	证券
14	交通银行	银行	32	泛海控股	多元金融
15	工商银行	银行	33	海德股份	多元金融
16	光大银行	银行	34	东方能源	多元金融
17	建设银行	银行	35	同花顺	多元金融
18	中国银行	银行

LOO_3		LOO_6		LOO_12
金融机构	关联重要性（%）	金融机构	关联重要性（%）	金融机构	关联重要性（%）
宁波银行	8.87	宁波银行	7.97	宁波银行	5.81
东方能源	8.87	中信银行	6.52	交通银行	5.48
兴业证券	8.06	长江证券	6.52	中信银行	4.84
中国银行	7.26	兴业证券	6.52	兴业证券	4.84
南京银行	5.65	东方能源	6.52	东方能源	4.84
长江证券	5.65	南京银行	5.80	平安银行	4.52
光大证券	5.65	光大证券	5.80	民生银行	4.52
交通银行	4.84	交通银行	5.07	北京银行	4.52
泛海控股	4.84	中国人寿	4.35	长江证券	4.52
中国太保	4.03	海德股份	4.35	招商银行	3.87

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Systemic Risk Backtesting and Connectedness of Chinese Financial Institutions: Evidence from MES and ΔCoVaR

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