Abstract
ABSTRACT Using an econophysics framework, this study applies actor-network theory to analyse bilateral risk in Savings and Loan Holding Companies (SLHCs). We construct intercompany funding and exposure networks using intercompany assets and liabilities data by utilizing a maximum entropy model on the annual balance sheets of 147 US SLHCs from 2013 to 2023. Two algorithms are employed to extract core-periphery network features, which allow us to assess optimal linkages and disruptions from external shocks. Our findings show that external shocks lead to network shrinkage, thus increasing vulnerability to contagion. Furthermore, negative degree assortativity values indicate a tendency for small SLHCs to connect with large SLHCs preferentially rather than other small ones. Simulating the removal of core nodes from the core-periphery structure in weighted graphs reveals that direct interconnections between SLHCs are the primary drivers of systemic risk. In contrast to the findings in commercial bank systems, intercompany exposure and funding networks in SLHCs display similar connectivity patterns, likely due to their limited branch networks and narrower business focus. This study expands on previous research to evaluate the robustness and resilience of SLHC networks to shocks by incorporating additional core-periphery network features, providing a more comprehensive understanding of SLHCs’ risk dynamics.
Published Version
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