中国管理科学 ›› 2022, Vol. 30 ›› Issue (12): 1-12.doi: 10.16381/j.cnki.issn1003-207x.2022.0060
• 论文 • 下一篇
刘志东, 张培元, 荆中博
收稿日期:
2021-07-31
修回日期:
2022-01-28
出版日期:
2022-12-20
发布日期:
2022-12-20
通讯作者:
荆中博(1985-),男(汉族),河北沧州人,中央财经大学管理科学与工程学院,副教授、硕士研究生导师, 博士, 研究方向: 大数据分析与金融风险管理,Email:zbjing@cufe.edu.cn.
E-mail:zbjing@cufe.edu.cn
基金资助:
LIU Zhi-dong, ZHANG Pei-yuan, JING Zhong-bo
Received:
2021-07-31
Revised:
2022-01-28
Online:
2022-12-20
Published:
2022-12-20
Contact:
荆中博
E-mail:zbjing@cufe.edu.cn
摘要: 实体行业受到外部冲击时存在跨行业风险溢出效应,导致银行所持有的不同行业资产的损失之间存在较高相关性。本文首先基于LASSO-VAR构建行业风险溢出网络,准确刻画特定行业风险上升带来的行业间风险联动特征。然后,利用DBNM-BA模型构建跨行业风险溢出冲击下的“实体行业-银行系统”两层级风险网络,并分别识别两层级网络中导致银行业系统性风险上升的关键节点:系统重要性行业和系统脆弱性银行。本文实证研究表明:(1)若不引入行业风险溢出网络,我国银行业系统性风险被低估约57.78%。(2)系统重要性行业方面。行业间风险溢出特征对系统重要性行业分布具有显著影响,行业相对规模的影响显著性次之,行业贷款集中度的影响显著性最弱。(3)系统脆弱性银行方面。我国银行体系抗风险能力总体呈上升趋势。2015年之后,国有商业银行和股份制商业银行风险水平迅速降低,银行业系统性风险主要来源于部分城市商业银行与农村商业银行。本文为我国采取精准措施防范化解系统性风险提供科学参考依据。
中图分类号:
刘志东, 张培元, 荆中博. 跨行业风险溢出冲击下我国银行业系统性风险研究[J]. 中国管理科学, 2022, 30(12): 1-12.
LIU Zhi-dong, ZHANG Pei-yuan, JING Zhong-bo. Research on the Systemic Risk of China’s Banking Industry under the Impact of Cross-industry Risk Spillover[J]. Chinese Journal of Management Science, 2022, 30(12): 1-12.
[1] 贾妍妍,方意,荆中博. 中国金融体系放大了实体经济风险吗[J].财贸经济, 2020,41(10):111-128.Jia Yanyan, Fang Yi, Jing Zhongbo. Does China’s financial system amplify risks in the real economy[J]. Finance and Trade Economics,2020,41(10):111-128. [2] 朱波, 马永谈. 行业特征、货币政策与系统性风险——基于“经济金融”关联网络的分析[J]. 国际金融研究, 2018(4):22-32.Zhu Bo, Ma Yongtan. Industrial characteristics, monetary policy and systemic risk——An analysis based on “Economic and Financial” linkage network[J]. Studies of International Finance, 2018(4):22-32. [3] 赵华, 王杰. 基于混频数据的实体经济与金融市场时变溢出效应研究[J]. 统计研究, 2018,35(7):49-61.Zhao Hua, Wang Jie. A study on time-varying spillover effects on real economy and financial markets based on mixed frequency var[J]. Statistical Research, 2018,35(7):49-61. [4] 李政, 刘淇, 梁琪. 基于经济金融关联网络的我国系统性风险防范研究[J]. 统计研究, 2019, 36(2):25-39.Li Zheng, Liu Qi, Liang Qi. A study on forestalling China`s systemic risk based on financial industry and real economy interacted network[J]. Statistical Research, 2019, 36(2):25-39. [5] 翟永会. 系统性风险管理视角下实体行业与银行业间风险溢出效应研究[J]. 国际金融研究, 2019(12):76-86.Zhai Yonghui. Research on the risk spillover effect between entity industry and banking industry from the perspective of systemic risk management[J]. Studies of International Finance, 2019(12):76-86. [6] 杨子晖. 金融市场与宏观经济的风险传染关系——基于混合频率的实证研究[J]. 中国社会科学, 2020(12): 160-180+204.Yang Zihui. The risk contagion relationship between the financial market and the macro economy: a mixed-frequency based empirical research[J]. Social Sciences in China, 2020(12): 160-180+204. [7] 司登奎, 李小林, 赵仲匡. 非金融企业影子银行化与股价崩盘风险[J]. 中国工业经济, 2021(6): 174-192.Si Dengkui, Li Xiaolin, Zhao Zhongkuang. Non-financial enterprises` shadow banking business and stock price crash risk[J]. China Industrial Economics, 2021(6): 174-192. [8] 范小云, 王道平, 方意. 我国金融机构的系统性风险贡献测度与监管——基于边际风险贡献与杠杆率的研究[J]. 南开经济研究, 2011(4):3-20.Fan Xiaoyun, Wang Daoping, Fang Yi. Measuring and supervising financial institutes’ marginal contribution to systemic risk in China: a research based on MES and leverage[J]. Nankai Economic Studies, 2011(4):3-20. [9] 梁琪, 李政, 郝项超. 我国系统重要性金融机构的识别与监管——基于系统性风险指数SRISK方法的分析[J]. 金融研究, 2013(9):56-70.Liang Qi, Li Zheng, Hao Xiangchao. The identification and regulation of domestic systemically important financial institutions of China——a research based on systemic risk index[J]. Journal of Financial Research, 2013(9):56-70. [10] Adrian T, Brunnermeier M. CoVaR[J]. American Economic Review, 2016,106(7):1705-1741. [11] 隋聪, 王宪峰, 王宗尧. 银行间网络连接倾向异质性与风险传染[J]. 国际金融研究, 2017(7):44-53.Sui Cong, Wang Xianfeng, Wang Zongyao. Inter-bank network connectivity heterogeneity and risk contagion[J]. Studies of International Finance, 2017(7):44-53. [12] 项后军, 郜栋玺, 陈昕朋. 基于“渠道识别”的货币政策银行风险承担渠道问题研究[J]. 管理世界, 2018,34(8):55-66.Xiang Houjun, Gao Dongxi, Chen Xinpeng. A study on bank risk-taking channel of monetary policy based on “channel identification” [J]. Management World, 2018,34(8):55-66. [13] 杨子晖, 王姝黛. 行业间下行风险的非对称传染:来自区间转换模型的新证据[J]. 世界经济, 2020,43(6):28-51.Yang Zihui, Wang Shudai. Asymmetric contagion of cross-industrial downside risks: New evidence from the regime-switching model[J]. The Journal of World Economy, 2020,43(6):28-51. [14] Acemoglu D, Ozdaglar A, Tahbaz-Salehi A. Systemic risk and stability in financial metworks[J]. The American Economic Review, 2015, 105(2):564-608. [15] Elliott M, Golub B, Jackson M. Financial networks and contagion[J]. The American Economic Review, 2014, 104(10):3115-3153. [16] Cabrales A, Gottardi P, Vega-Redondo F. Risk sharing and contagion in networks[J]. Review of Financial Studies, 2017, 30(9): 3086-3127. [17] Heider F, Hoerova M, Holthausen C. Liquidity hoarding and interbank market spreads: The role of counterparty risk[J]. Journal of Financial Economics, 2015(2):336-354. [18] Greenwood R, Landier A, Thesmar D. Vulnerable banks[J]. Journal of Financial Economics, 2015,115(3):471-485. [19] 方意, 黄丽灵. 系统性风险、抛售博弈与宏观审慎政策[J]. 经济研究, 2019(9):41-55.Fang Yi, Huang Liling. Systemic risk, the fire sale game and macroprudential policy[J]. Economic Research Journal, 2019(9):41-55. [20] Duarte F, Eisenbach T. Fire-sale spillovers and systemic risk[J]. Journal of Finance, 2021,3(76):1251-1294. [21] 张奇,胡蓝艺,王珏.基于Logit与SVM的银行业信用风险预警模型研究[J].系统工程理论与实践,2015,35(7):1784-1790.Zhang Qi, Hu Lanyi, Wang Jue. Study on credit risk early warning based on Logit and SVM[J]. Systems Engineering-Theory & Practice, 2015,35(7):1784-1790. [22] 庞素琳,何毅舟,汪寿阳,等.基于风险环境的企业多层交叉信用评分模型与应用[J].管理科学学报,2017,20(10):57-69.Pang Sulin, He Yizhou, Wang Shouyang, et al. Multilayer crossing credit scoring models for enterprise and application based on risk environment[J]. Journal of Management Sciences in China, 2017,20(10):57-69. [23] 陈荣达,虞欢欢,余乐安,等.混合泊松违约强度下信用资产组合风险度量[J].管理科学学报,2018,21(12):54-69.Chen Rongda, Yu Huanhuan, Yu Lean, et al. Portfolio credit risk measurement based on mixed Poisson default intensity[J]. Journal of Management Sciences in China, 2018,21(12):54-69. [24] 陈庭强,周文静,童毛弟,等.融合CDS网络的银行间信用风险传染模型研究[J].中国管理科学,2020,28(6):24-37.Chen Tingqiang, Zhou Wenjing, Tong Maodi, et al. Research on the model of inter-bank credit risk contagion by fusing CDs Networks[J]. Chinese Journal of Management Science, 2020,28(6):24-37. [25] 章彤,迟国泰.基于最优信用特征组合的违约判别模型——以中国A股上市公司为例[J].系统工程理论与实践,2020,40(10):2546-2562.Zhang Tong, Chi Guotai. Default discriminant study based on optimal credit feature set: A case study of China A-share listed companies[J]. Systems Engineering-Theory & Practice, 2020,40(10):2546-2562. [26] 陈暮紫,汤婧,张小溪,等.信用和流动风险冲击下的中国银行业传染分析[J].系统工程理论与实践,2021,41(6):1412-1427.Chen Muzi, Tang Jing, Zhang Xiaoxi, et al. Contagion analysis of China’s banking industry under the impact of credit and liquidity risk[J]. Systems Engineering-Theory & Practice, 2021,41(6):1412-1427. [27] Diebold F, Yilmaz K. Measuring financial asset return and volatility spillovers,with application to global equity markets[J]. The Economic Journal,2009, 534 (119):158-171. [28] Messner J, Pinson P. Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting[J]. International Journal of Forecasting,2019,35(4):1485-1498. [29] Nicholson W, Matteson D, Bien J. VARX-L: Structured regularization for large vector autoregressions with exogenous variables[J]. International Journal of Forecasting,2017,33(3):627-651. [30] Diebold F, Yilmaz K. Better to give than to receive: Predictive directional measurement of volatility spillovers[J]. International Journal of Forecasting,2012,28(1):57-66. [31] Huang Xuqing, Vodenska I, Havlin S. Cascading failures in Bi-partite Graphs: Model for systemic risk propagation[J]. Scientific Reports,2013(1):440442-1028. [32] Levy-Carciente S, Kenett D, Avakian A. Dynamical macroprudential stress testing using network theory[J]. Journal of Banking and Finance, 2015,59:164-181. [33] Cont R, Schaanning E. A threshold model for fire sales and price-mediated contagion [R]. Working Paper, Swiss Finance Institute, 2015. |
[1] | 郭冉冉,叶五一,刘小泉,缪柏其. 商品期货投资组合与市场收益的尾部相依研究[J]. 中国管理科学, 2024, 32(10): 11-19. |
[2] | 韩鑫韬,张晓敏,刘星. 宏观审慎管理配合下的最优货币政策选择[J]. 中国管理科学, 2024, 32(10): 1-10. |
[3] | 成思聪,王天一. 引入隔夜信息的期权定价模型研究[J]. 中国管理科学, 2024, 32(9): 1-10. |
[4] | 吴鑫育,谢海滨,马超群. 经济政策不确定性与人民币汇率波动率[J]. 中国管理科学, 2024, 32(8): 1-14. |
[5] | 谢楠,何海涛,周艳菊,王宗润. 乡村振兴背景下基于中央政府项目补贴分析的供应链金融决策研究[J]. 中国管理科学, 2024, 32(8): 214-229. |
[6] | 于孝建,刘国鹏,刘建林,肖炜麟. 基于LSTM网络和文本情感分析的股票指数预测[J]. 中国管理科学, 2024, 32(8): 25-35. |
[7] | 倪宣明,郑田田,赵慧敏,武康平. 基于最优异质收益率因子的资产定价研究[J]. 中国管理科学, 2024, 32(8): 50-60. |
[8] | 于文华,任向阳,杨坤,魏宇. 传染病不确定性对大宗商品期货价格波动的非对称影响研究[J]. 中国管理科学, 2024, 32(5): 254-264. |
[9] | 蔡毅,唐振鹏,吴俊传,杜晓旭,陈凯杰. 基于灰狼优化的混频支持向量机在股指预测与投资决策中的应用研究[J]. 中国管理科学, 2024, 32(5): 73-80. |
[10] | 李仲飞,周骐. 一个基于BL模型和复杂网络的行业配置模型[J]. 中国管理科学, 2024, 32(4): 1-13. |
[11] | 张雪彤,张卫国,王超. 发达市场与新兴市场的尾部风险[J]. 中国管理科学, 2024, 32(4): 14-25. |
[12] | 尹海员,寇文娟. 基于朴素贝叶斯法的投资者情绪度量及其对股票特质风险的影响[J]. 中国管理科学, 2024, 32(4): 38-47. |
[13] | 王晓燕,杨胜刚,张科坤. 终极所有权结构与企业委托贷款行为[J]. 中国管理科学, 2024, 32(4): 48-57. |
[14] | 李爱忠,任若恩,董纪昌. 图网络风险感知与稀疏低秩的组合管理策略[J]. 中国管理科学, 2024, 32(4): 58-65. |
[15] | 吴鑫育,姜晓晴,李心丹,马超群. 基于已实现EGARCH-FHS模型的上证50ETF期权定价研究[J]. 中国管理科学, 2024, 32(3): 105-115. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||
|