The description of the empirical structure of interbank networks constitutes an important field of study since network theory can be used as a powerful tool to assess the resilience of financial systems and their robustness against failures. On the other hand, the development of reliable models of interbank market structure is relevant as they can be used to analyze systemic risk in the absence of transaction data or to test statistical hypotheses regarding network properties. Based on a detailed data-driven analysis of bank positions (assets and liabilities) taken from the Bankscope database, we here develop a minimal, stochastic, agent-based network model that accounts for the basic topology of interbank networks reported in the literature. The main assumption of our model is that loans between banks attempt to compensate assets and liabilities at each time step, and the model renders networks comparable with those observed in empirical studies. In particular, our model is able to qualitatively reproduce degree distributions, the distribution of the number of transactions, the distribution of exposures, the correlations with nearest-neighbor out-degree, and the clustering coefficient. As our simple model captures the overall structure of empirical networks, it can thus be used as a null model for testing hypotheses relative to other specific properties of interbank networks.

中文翻译：

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基于最小代理的模型重现了银行间网络的整体拓扑

银行间网络经验结构的描述构成了一个重要的研究领域，因为网络理论可以用作评估金融系统的弹性及其对失败的稳健性的有力工具。另一方面，可靠的银行间市场结构模型的发展是相关的，因为它们可用于在没有交易数据的情况下分析系统性风险或测试有关网络属性的统计假设。基于从Bankscope数据库中获得的银行头寸（资产和负债）的详细数据驱动分析，我们在此建立了一个基于代理的最小，随机，最小化的网络模型，该模型解释了文献中报道的银行间网络的基本拓扑。我们模型的主要假设是，银行之间的贷款试图在每个时间步长上补偿资产和负债，并且该模型使网络与实证研究中观察到的网络具有可比性。特别地，我们的模型能够定性地再现度分布，交易数量的分布，风险敞口的分布，与最近邻度的相关性以及聚类系数。由于我们的简单模型捕获了经验网络的整体结构，因此可以用作测试与银行间网络其他特定属性相关的假设的空模型。交易数量的分布，风险的分布，与最近邻出境度的相关性以及聚类系数。由于我们的简单模型捕获了经验网络的整体结构，因此可以用作测试与银行间网络其他特定属性相关的假设的空模型。交易数量的分布，风险的分布，与最近邻出境度的相关性以及聚类系数。由于我们的简单模型捕获了经验网络的整体结构，因此可以用作测试与银行间网络其他特定属性相关的假设的空模型。