Advances in Modelling Systemic Risk in Financial Networks

Jorge A Chan-Lau

Chapter 8 introduced balance-sheet network analysis, a simple but practical way to analyse too connected to fail (TCTF) or interconnectedness risk in a financial network. Conducting the analysis requires data on counterparty exposures of the different firms and/ or agents in the financial network. When available, this analysis provides insights on the nature of interconnectedness, and facilitates the calculation of systemic risk measures associated with potential losses due to cascade effects prompted by the failure of an individual firm or a group of firms.11 For instance, see Sun and Chan-Lau (2017) for a detailed analysis of systemic risk in an advanced emerging market economy, Demekas et al (2013) on the use of direct exposure networks for identifying systemic financial jurisdictions, and the empirical work cited in Caccioli, Barucca and Kobayashi (2018). For a theoretical analysis, see Acemoglu, Ozdaglar and Tahbaz-Salehi (2015).

Counterparty exposure data are usually difficult to obtain, especially for disaggregated data. It is possible to reconstruct bilateral exposures from aggregate data using a variety of methods, however in many instances the reconstructed data

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