A block-structured model for the reconstruction of directed and weighted financial networks, spanning multiple countries, is developed. In a first step, link-probability matrices are derived via a fitness model that is calibrated to reproduce a desired density and reciprocity for each block (i.e. country and cross-border sub-matrix). The resulting probability matrix allows for fast simulation through bivariate Bernoulli trials. In a second step, weights are allocated to a sampled adjacency matrix via an exponential random graph model (ERGM), which fulfills the row, column, and block weights. This model is analytically tractable, calibrated only on scarce publicly available data, and closely reconstructs known network characteristics of financial markets. In addition, an algorithm for the parameter estimation of the ERGM is presented. Furthermore, calibrating our model to the EU interbank market, we are able to assess the systemic risk within the European banking network by applying various contagion models.     «

A block-structured model for the reconstruction of directed and weighted financial networks, spanning multiple countries, is developed. In a first step, link-probability matrices are derived via a fitness model that is calibrated to reproduce a desired density and reciprocity for each block (i.e. country and cross-border sub-matrix). The resulting probability matrix allows for fast simulation through bivariate Bernoulli trials. In a second step, weights are allocated to a sampled adjacency m...     »