增强还是减弱：新型金融与传统金融行业之间系统性风险溢出

doi:10.16381/j.cnki.issn1003-207x.2022.0567

Abstract

Abstract:

At the beginning of 2020， COVID-19 broke out. The epidemic had a major impact on China’s social stability and economic development， leading to economic downturn and increasing systemic risks in the financial system； At the same time， diversified finance is developing rapidly in China. It is also of great practical significance to investigate the systematic risk spillovers of diversified finance and traditional financial industries. Diversified finance refers to other emerging financial industries except traditional financial industries such as banking， securities and insurance. Based on the daily loss rate data of ShenyinWanguo secondary industry index （banking index， securities index， insurance index and diversified financial index）， CoVaR and Δ CoVaR model is used to measure the systematic risk among financial industries， examines the systematic risk spillover effect between diversified finance and traditional financial industries， and compares it with the systematic risk spillover effect between traditional financial industries. It is found that systematic risk spillovers between diversified finance and traditional financial industries weaken each other， which indicates that traditional finance and diversified finance play a role in mutually reducing systematic risk， but systematic risk spillovers between traditional financial industries strengthen each other. In addition， under extreme market conditions， the mutual weakening effect of systemic risks between diversified finance and traditional financial industries is stronger. During the same period， the level of systemic risk spillover between traditional financial industries has increased， and the increase caused by direct impact is greater than that caused by indirect impact. The research shows that the development of diversified finance not only provides more abundant financial service products for the real economy， but also hedges the systematic risk of traditional finance. The findings of this study are of great significance for the future development of China's financial market. China should continue to adhere to the supply side reform of the financial industry and vigorously develop diversified finance， especially science and technology finance. This will not only further enrich China's financial market and promote the development of the financial system， but also help hedge the systematic risks of the traditional financial industry and promote the healthy development of the entire financial system.

Key words: diversified finance, extreme stage, systemic risk, traditional financial industries, systemic risk spillover

CLC Number:

F830.9

Haixiang Yao, Qiuyu Liu, Xiaoguang Yang. Strengthening or Weakening: Systemic Risk Spillovers between Diversified Financial in Dustries and Traditional Financial Industries[J]. Chinese Journal of Management Science, 2025, 33(3): 1-12.

Figures/Tables 10

变量	$Δ C o V a R j i$
j i	银行业	证券业	保险业	新型金融
银行业		2.90	3.02	-2.11
证券业	2.18		2.60	-2.78
保险业	2.47	3.24		-2.50
新型金融	-1.78	-3.45	-2.52

数量	2008年 $β ̂ q j \| i$				2015年 $β ̂ q j \| i$
j i	银行业	证券业	保险业	新型金融	银行业	证券业	保险业	新型金融
银行业		0.736	0.911	-1.028		1.343	1.193	-0.390
证券业	0.616		0.644	-0.781	0.326		0.549	-0.594
保险业	0.689	0.623		-0.750	0.861	1.245		-0.408
新型金融	-0.646	-0.823	-0.675		-0.185	-0.822	-0.651
	2020年 $β ̂ q j i$				2017年 $β ̂ q j i$
银行业		1.397	1.329	-0.923		0.708	1.500	0.025
证券业	0.506		0.693	-0.799	0.523		0.216	-0.416
保险业	0.722	1.264		-0.823	0.383	0.366		-0.096
新型金融	-0.344	-1.218	-0.831		-0.157	-0.830	-0.216

References 35

1	国际货币基金组织. 2011年4月期全球金融稳定报告［M］. 北京：中国金融出版社， 2011.
	International Monetary Fund. April 2011 global financial stability report ［M］. Beijing： China Financial Publishing House， 2011.
2	European Central Bank. Annual report 2010［EB/OL］.（2011-02-25）［2011-02-25］. .
3	谢志刚．系统性风险与系统重要性：共识和方向［J］．保险研究，2016（7）：25-34.
	Xie Z G ．Systemic risks and systemic importance： Consensus and future directions［J］．Insurance Studies，2016（7）：25-34.
4	杨子晖，陈里璇，陈雨恬．经济政策不确定性与系统性金融风险的跨市场传染——基于非线性网络关联的研究［J］．经济研究，2020， 55（1）：65-81.
	Yang Z H， Chen L X， Chen Y T ．Cross-market contagion of economic policy uncertainty and systemic financial risk： A nonlinear network connectedness analysis［J］．Economic Research Journal，2020， 55（1）：65-81.
5	陆静，胡晓红．基于条件在险价值法的商业银行系统性风险研究［J］．中国软科学， 2014（4）：25-42.
	Lu J， Hu X H ．Study on systemic risk of commercial banks based on conditional value at risk［J］．China Soft Science， 2014（4）：25-42.
6	白雪梅，石大龙．中国金融体系的系统性风险度量［J］．国际金融研究，2014（6）：75-85.
	Bai X M， Shi D L ．Measurement of the systemic risk of China’s financial system［J］．Studies of International Finance，2014（6）：75-85.
7	White H， Kim T H， Manganelli S. VAR for VaR： Measuring tail dependence using multivariate regression quantiles［J］. Journal of Econometrics， 2015，187（1）： 169-188
8	Hartmann P， Straetmans S， Vries C D. Asset market linkages in crisis periods［J］. Review of Economics and Statistics， 2004， 86（1）： 3113-3126.
9	裴茜，朱书尚.中国股票市场金融传染及渠道——基于行业数据的实证研究［J］. 管理科学学报，2019，22（3）：90-112.
	Pei X， Zhu S S.Financial contagion in China’s stock market： A study based on industry-level data［J］. Journal of Management Sciences in China，2019，22（3）：90-112.
10	杨子晖，陈雨恬，张平淼．重大突发公共事件下的宏观经济冲击、金融风险传导与治理应对［J］．管理世界，2020，36（5）：13-35+7.
	Yang Z H， Chen Y T， Zhang P M ．Macroeconomic shock， financial risk transmission and governance response to major public emergencies［J］．Journal of Management World，2020，36（5）：13-35+7.
11	陈建青，王擎，许韶辉. 金融行业间的系统性金融风险溢出效应研究［J］. 数量经济技术经济研究， 2015， 32（9）： 89-100.
	Chen J Q， Wang Q， Xu S H. A CoVaR research on spillover effect of systemic financial risk between financial sub-sectors［J］. The Journal of Quantitative & Technical Economics， 2015， 32（9）： 89-100.
12	苏明政，张庆君. 关联性视阈下我国金融行业间系统性风险传染效应研究［J］. 会计与经济研究， 2015， 29（6）： 111-124.
	Su M Z， Zhang Q J. A Study on the contagion effect of systemic risk in Chinese financial sectors： A correlation perspective［J］. Journal of Accounting and Economics， 2015， 29（6）： 111-124.
13	梁琪，常姝雅.我国金融混业经营与系统性金融风险——基于高维风险关联网络的研究［J］.财贸经济，2020，41（11）：67-82.
	Liang Q， Chang S Y. China’s universal financial operation and financial systemic Risk：A study on high-dimensional risk interconnected network［J］.Finance & Trade Economics，2020，41（11）：67-82.
14	彭建刚，邹克，蒋达.混业经营对金融业系统性风险的影响与我国银行业经营模式改革［J］.中国管理科学，2014，22（S1）：272-280.
	Peng J G， Zou K， Jiang D. Effect of mixed operation on financial systemic risk and reform of business model of China banking［J］.Chinese Journal of Management Science，2014，22（S1）：272-280.
15	Wagner W. Diversification at financial institutions and systemic crises［J］. Journal of Financial Intermediation，2009，19（3）： 373-386
16	Allen F， Gale D. Optimal currency crises［J］. Carnegie-Rochester Conference Series on Public Policy， 2000， 53（1）： 177-230.
17	李政，梁琪，涂晓枫．我国上市金融机构关联性研究——基于网络分析法［J］．金融研究，2016（8）：95-110.
	Li Z， Liang Q， Tu X F ．The connectedness of Chinese listed financial institutions： A study based on network analysis［J］．Journal of Financial Research，2016（8）：95-110.
18	欧阳红兵，刘晓东．中国金融机构的系统重要性及系统性风险传染机制分析——基于复杂网络的视角［J］．中国管理科学，2015，23（10）：30-37.
	Ouyang H B， Liu X D ．An analysis of the systemic importance and systemic risk contagion mechanism of China’s financial institutions based on network analysis［J］．Chinese Journal of Management Science，2015，23（10）：30-37.
19	Adrian T， Brunnermeier M K. CoVaR［J］. American Economic Review，2016，106（7）：1705-1741.
20	Girardi G， Erguen A T. Systemic risk measurement： Multivariate GARCH estimation of CoVaR［J］. Journal of Banking & Finance， 2013， 37（8）： 3169-3180.
21	李政，涂晓枫，卜林．金融机构系统性风险：重要性与脆弱性［J］．财经研究，2019，45（2）：100-112+152.
	Li Z， Tu X F， Bu L ．Systemic risks of financial institutions： Importance and vulnerability［J］．Journal of Finance and Economics，2019，45（2）：100-112+152.
22	韩浩，王向楠，刘璐．保险业系统性风险及对相关行业的溢出效应研究［J］．保险研究，2020（7）：31-48.
	Han H， Wang X N， Liu L ．Insurance industry’s systemic risk and its spillover effect on related sectors［J］．Insurance Studies，2020（7）：31-48.
23	姚登宝，施腾，刘治戎. 金融周期视角下中国系统性金融风险的状态转换效应研究［J］.金融经济学研究， 2021， 36（2）： 3-17.
	Yao D B， Shi T， Liu Z R. State transition effect of China’s systemic financial risks from the financial cycle perspective［J］.Financial Economics Research， 2021， 36（2）： 3-17.
24	张冰洁，汪寿阳，魏云捷，赵雪婷. 基于CoES模型的我国金融系统性风险度量［J］. 系统工程理论与实践，2018，38（3）：565-575.
	Zhang B J， Wang S Y， Wei Y J，et al. Measuring the systemic risk contribution of financial institutes in China based on coesmodel［J］. Systems Engineering-Theory & Practice，2018，38（3）：565-575.
25	李政，梁琪，方意. 中国金融部门间系统性风险溢出的监测预警研究——基于下行和上行ΔCoES指标的实现与优化［J］. 金融研究，2019（2）：40-58.
	Li Z， Liang Q， Fang Y. Monitoring and forewarning of systemic risk spillover in China’s financial sector based on modified coes indicators［J］. Journal of Financial Research，2019（2）：40-58.
26	Acharya V V， Pedersen L H， Philippon T， et al. Measuring systemic risk［J］. The Review of Financial Studies， 2017， 30（1）： 2-47.
27	卜林，李政．我国上市金融机构系统性风险溢出研究——基于CoVaR和MES的比较分析［J］．当代财经，2015（6）：55-65.
	Bu L， Li Z ．A study of systematic risk spillover of China’s listed financial institutions： A comparative analysis based on covar and MES［J］．Contemporary Finance & Economics，2015（6）：55-65.
28	Brownlees C， Engle R F. SRISK： A conditional capital shortfall measure of systemic risk［J］. The Review of Financial， 2017， 30（1）：48-79
29	陈湘鹏，周皓，金涛，等. 微观层面系统性金融风险指标的比较与适用性分析——基于中国金融系统的研究［J］. 金融研究，2019（5）：17-36.
	Chen X P， Zhou H， Jin T， et al. Comparison and applicability analysis of micro-level systemic risk measures： A study based on China’s financial system［J］. Journal of Financial Research，2019（5）：17-36.
30	赵林海，陈名智. 金融机构系统性风险溢出和系统性风险贡献——基于滚动窗口动态Copula模型双时变相依视角［J］. 中国管理科学， 2021， 29（7）： 71-83.
	Zhao L H， Chen M Z. Systemic risk spillovers and systemic risk contributions of financial institutions in China： A perspective of dual time：Varing dependence of rolling window dynamic copula model［J］. Chinese Journal of Management Science， 2021， 29（7）： 71-83.
31	Koenker R， Bassett Jr G. Regression quantiles［J］. Econometrica， 1978（46）： 33-50.
32	胡吉祥. 互联网金融对证券业的影响［J］. 中国金融， 2013（16）： 73-74.
	Hu J X. TheIinfluence of internet finance on securities industry［J］. China Finance， 2013（16）： 73-74.
33	朱晓谦，李靖宇，李建平，等.基于危机条件概率的系统性风险度量研究［J］.中国管理科学，2018，26（6）：1-7.
	Zhu X Q， Li J Y， Li J P， et al.An indicator of conditional probability of crisis for systemic risk measurement［J］.Chinese Journal of Management Science，2018，26（6）：1-7.
34	陈守东，王妍. 我国金融机构的系统性金融风险评估——基于极端分位数回归技术的风险度量［J］. 中国管理科学，2014，22（7）：10-17.
	Chen S D，WangY. Measuring systemic financial risk of China’s financial institutions：Applying extremal quantile regression technology and covarmodel［J］. Chinese Journal of Management Science，2014，22（7）：10-17.
35	李绍芳，刘晓星. 中国金融机构关联网络与系统性金融风险［J］. 金融经济学研究， 2018， 33（5）： 34-48.
	Li S F， Liu X X. The interconnected network and systemic risk of China’s financial Institutions［J］. Financial Economics Research， 2018， 33（5）： 34-48.

状态变量	计算方法
股票市场收益率（m1）	沪深300指数收益率
股票市场波动（m2）	沪深300指数波动率
期限利差变动（m3）	10年期国债即期收益率与一年期国债即期收益率之差
流动性价差（m4）	6个月Shibor与6个月固定利率国债到期收益率之差
房地产超额收益（m5）	沪深300房地产指数收益率与上证综指收益率之差

行业	均值	标准差（%）	偏度	峰度
银行业	0	1.8038	0.0227	8.5673
证券业	0.0001	2.6150	0.0788	5.9657
保险业	-0.0001	2.2472	0.0293	6.0799
新型金融	0.0003	2.3323	0.5573	6.3353

指标	银行业	证券业	保险业	新型金融
ADF值	-55.62^***	-53.63^***	-55.42^***	-52.79^***
概率值P	0.0001	0.0001	0.0001	0.0001
平稳性	平稳	平稳	平稳	平稳

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Strengthening or Weakening: Systemic Risk Spillovers between Diversified Financial in Dustries and Traditional Financial Industries

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