Interbank and counterparty contagion
Bilateral exposures are arranged as a network and default cascades are simulated to see how losses spread from an initial failure and which institutions amplify them.
GRA · Banking Nexus
空间金融资本与危害、风险暴露和转型的交汇之处
面向银行传导的网络科学
Network science maps how banks are linked through interbank lending, derivatives, common asset holdings, payment flows and shared service providers. It shows where a single failure could cascade, which institutions are central to the system, and why contagion differs from the sum of individual bank risks.
01目录
Network science for banking contagion in five parts.
02申请
What network science and contagion does here.
Network science and contagion study how the structure of connections among entities shapes the spread of failures, information and disease. It provides tools to analyse interdependent infrastructure, supply chains and financial 系统. In financial stability, capital markets and investment and climate and hazards, network science identifies critical nodes and pathways through which shocks propagate across sectors. It informs targeted protection and diversification to limit cascades. The canonical description is on STEM Commons.
Overlapping portfolios and fire sales
Common holdings of securities and loans are mapped so that forced sales by one bank can be traced through price falls to losses at other holders.
Operational dependency mapping
Banks, payment systems, cloud and software providers are represented as a multilayer network to find concentration points whose failure would affect many institutions together.
03空间金融
结算依赖关系，以及节点失效会导致什么失效。
一个金融中心的故障如何通过结算联系扩散。为设计的联系，并非真实的依赖关系。
04数据
该方法使用的输入。
Datasets and records used by network science and contagion on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| Supervisory large exposure and counterparty data | Bilateral links between institutions | 已发布统计 |
| BIS international banking statistics | Cross-border exposures by country | 已发布统计 |
| Payment system transaction data | Payment flow networks | 观测 |
| Registers of third-party arrangements | Service dependency links | 已报告 |
05监测
Network analysis.
团队遵循该方法时会使用的界面：其指标、状态与决策。名称为示例，数值仅作示意。
网络分析
Banking · Network science for banking · Run R-5964
单点故障GRA · Banking Nexus
依赖关系图
nodes: assets · edges: dependencies
Most central nodes
| N3 | 0.25 | 4 | Critical |
| N4 | 0.16 | 12 | 正常 |
| N5 | 0.17 | 11 | 正常 |
| N6 | 0.18 | 8 | 正常 |
Cascade size under removal
06验证
结果如何核查。
Models are checked by reproducing observed cascades and outbreaks. Robustness of results to missing or uncertain links is tested.
| 核查 | 如何开展 |
|---|---|
| Missing link sensitivity | Results are tested under alternative reconstructions of unobserved exposures, and the range is reported |
| Historical replay | Models are checked against known stress episodes and failures |
| Behavioural assumptions | Assumptions about liquidity hoarding, fire sales and recovery rates are stated and varied |
Network data are often incomplete or confidential. Static network models may miss adaptive behaviour during cascades.
07压力测试
资产冲击如何演变为系统性损失。
银行间传染之后系统损失的权益，相对于最初的冲击，随杠杆、互联程度和回收率变化而变化，这是宏观审慎 压力测试. Teaching model with stated illustrative values, not a prediction. The map on this page shows Western Europe; the model itself is not tied to a place.
控制措施
- 外部资产下降
- 2.0%
- 杠杆率（资产与权益之比）
- 10 倍
- 银行间资产占比
- 10%
- 银行间债权的回收
- 40%
- 体系内的银行
- 20
- 核心银行
- 占银行的 20%
读数
- 初始冲击造成的权益损失
- 18.0%
- 传染后的权益损失
- 45.0%
- 传染新增（DebtRank）
- 27.0 个点
- 违约银行
- 0
数字、方法与来源
| 轮次 | 系统权益损失（%） | 违约银行 |
|---|---|---|
| 0 | 18.00 | 0 |
| 1 | 28.80 | 0 |
| 2 | 35.28 | 0 |
| 3 | 39.17 | 0 |
| 4 | 41.50 | 0 |
| 5 | 42.90 | 0 |
| 6 | 43.74 | 0 |
| 7 | 44.24 | 0 |
| 8 | 44.55 | 0 |
| 9 | 44.73 | 0 |
| 10 | 44.84 | 0 |
| 11 | 44.90 | 0 |
| 12 | 44.94 | 0 |
| 13 | 44.96 | 0 |
| 14 | 44.98 | 0 |
| 15 | 44.99 | 0 |
| 16 | 44.99 | 0 |
| 17 | 45.00 | 0 |
| 18 | 45.00 | 0 |
| 19 | 45.00 | 0 |
| 20 | 45.00 | 0 |
| 21 | 45.00 | 0 |
| 22 | 45.00 | 0 |
| 23 | 45.00 | 0 |
| 24 | 45.00 | 0 |
| 25 | 45.00 | 0 |
| 26 | 45.00 | 0 |
| 27 | 45.00 | 0 |
| 28 | 45.00 | 0 |
| 29 | 45.00 | 0 |
| 30 | 45.00 | 0 |
方法
- DebtRank Battiston 等（2012），Scientific Reports 2:541
- 差异化 DebtRank Bardoscia and others (2015), PLOS ONE 10
- 金融网络中的传染 Gai and Kapadia (2010), Proc. R. Soc. A 466
- 金融网络中的清算 Eisenberg 和 Noe（2001），Management Science 47
- 不确定性扇形图（参数蒙特卡罗） Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- 单因素敏感性（龙卷风图） Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
数据
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
贯穿六大支柱，由 Nexus Consortium 牵头
09孪生与级联模拟器
Trace a shock in network science for banking contagion to the balance sheet.
Assembled from the Nexus Standards area profile 银行业: the shocks it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Pick an initiating shock and step through the cascade to see which exposures it reaches and where losses could concentrate. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise, not a forecast, a valuation, a rating or investment advice. To model a place of your own choosing, open the full System Builder.
灾害
系统与耦合
- 银行业
- 中央银行与金融监管机构 耦合
- 保险与再保险 耦合
- 城市与建成环境 耦合
- 数字、电信与平台 耦合
控制措施
NS-0章程与原则NS-3风险记录 UNI（语法、旧编码对照、分配机构）NS-9情境 UNI（部署、实例、计划实例）NS-10政策和条款（机器可读的义务：定义、约束、评估和执行）NS-11验证与监测（证据、证明、零信任符合性观测）NS-14符合性及与外部标准的对照NRS-U2宇宙 platform profile: Banking NexusNRS-F2银行业气候、自然与转型风险NRS-H113危害类别：金融体系脆弱性（NHS-1 soc.financial-system）NRS-K20领域包规范：气候适应（DOMAIN-020）NRS-U8Universe 平台概况：Energy NexusNRS-D1风险知情的发展与项目筛查
观测
- BIS statistics (banking, credit, debt securities, property prices) (listed for reference)
- IMF data services (IFS, FSI, WEO, GFS) (listed for reference)
- World Development Indicators (listed for reference)
- GLEIF Golden Copy (LEI Level 1 and Level 2 data) (listed for reference)
- Bank capital to assets ratio (%)
- Bank nonperforming loans to total gross loans (%)
- Domestic credit to private sector (% of GDP)
- (a) Number of commercial bank branches per 100,000 adults and (b) number of automated teller machines (ATMs) per 100,000 adults
示例地理范围
- 西欧：152 个六边形网格
- 过去半小时降雨率（IMERG），NASA GIBS
- 今夜夜间灯光与停电（VIIRS 昼夜波段），NASA GIBS
- 穿透云层的地表水，30 m（OPERA DSWx-S1 雷达），NASA GIBS
- Carbon monoxide, smoke transport (AIRS), NASA GIBS
10管理责任
由谁维护该方法。
系统科学与建模 stewards network science and contagion for the Consortium and reviews how it is applied across platforms.
11风险暴露、损失与资本
What network science for banking contagion means for exposure, loss and capital.
风险官、监管者或财政部会要求的风险暴露、损失、情景和资本视图，以及它们据以报告的框架。结构遵循监管和精算实务。数值为说明性：绝非价格、评级或建议。
传导渠道
How a shock in network science for banking contagion reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
NGFS 气候情景 · 央行与监管机构绿色金融网络IFRS S2 气候相关披露 · ISSBTCFD 建议 · 金融稳定理事会 TCFD有效管理气候相关金融风险的原则 · 巴塞尔银行监管委员会
12已关联
本页在整个联合体中通向何处。
13问题
问题与解答。
What are the limits of network science and contagion in this field?
Network data are often incomplete or confidential. Static network models may miss adaptive behaviour during cascades.
结果如何核查？
Models are checked by reproducing observed cascades and outbreaks. Robustness of results to missing or uncertain links is tested.
本页面上的数值是真实的吗？
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
该方法还应用于何处？
维持社会运转的各个 规范方法页面 列出应用该方法的每个平台。
报告贡献
从本页贡献证据。
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
全球风险联盟（Global Risks Alliance）Banking Nexus金融与保险准备度情景与压力测试
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法律
法律文件。
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