Micro-structural models of contagion and systemic risk emphasize that shock propagation is inherently multi-channel, spanning counterparty exposures, short-term funding and roll-over risk, securities cross-holdings, and common-asset (fire-sale) spillovers. Empirical implementations, however, often rely on stylized or simulated networks, or focus on a single exposure dimension, reflecting the practical difficulty of reconciling heterogeneous granular collections into a coherent representation with consistent identifiers and consolidation rules. We close part of this gap by constructing an empirically grounded multilayer network for euro area significant banking groups that integrates several supervisory and statistical datasets into layer-consistent exposure matrices defined on a common node set. Each layer corresponds to a distinct transmission channel, long- and short-term credit, securities cross-holdings, short-term secured funding, and overlapping external portfolios, and nodes are enriched with balance-sheet information to support model calibration. We document pronounced cross-layer heterogeneity in connectivity and centrality, and show that an aggregated (flattened) representation can mask economically relevant structure and misidentify the institutions that are systemically important in specific markets. We then illustrate how the resulting network disciplines standard systemic-risk analytics by implementing a centrality-based propagation measure and a micro-structural agent-based framework on real exposures. The approach provides a data-grounded basis for layer-aware systemic-risk assessment and stress testing across multiple dimensions of the banking network.

翻译：传染与系统性风险的微观结构模型强调，冲击传播本质上是多通道的，涵盖交易对手敞口、短期融资与展期风险、证券交叉持有以及共同资产（抛售）溢出效应。然而，实证研究往往依赖程式化或模拟网络，或仅关注单一敞口维度，这反映了将异质性颗粒数据集整合为具有一致标识符与合并规则之连贯表征的实际困难。我们通过构建一个基于实证的欧元区重要银行集团多层网络，部分填补了这一空白。该网络将多个监管与统计数据集整合至定义在共同节点集上的各层一致敞口矩阵中。每一层对应一个特定的传导渠道：长期与短期信贷、证券交叉持有、短期有担保融资以及重叠的外部投资组合，节点则通过资产负债表信息进行丰富以支持模型校准。我们记录了连接性与中心性在跨层间的显著异质性，并表明聚合（扁平化）的表征可能掩盖经济相关的结构，并错误识别在特定市场中具有系统重要性的机构。随后，我们通过在实际敞口上实施基于中心性的传播度量与基于微观结构的智能体框架，展示了所得网络如何规范标准的系统性风险分析。该方法为跨银行网络多个维度的、具备层间意识的系统性风险评估与压力测试提供了基于数据的坚实基础。