The need to monitor aggregate financial stability was made clear during the global financial crisis of 2008-2009, and, of course, the need to monitor individual financial firms from a microprudential standpoint remains. However, linkages between financial firms cannot be observed or measured easily. In this paper, we propose a procedure that generates measures of connectedness between individual firms and for the system as a whole based on information observed only at the firm level; i.e., no explicit linkages are observed. We show how bank outcome variables of interest can be decomposed, including with mixed-frequency models, for how network analysis to measure connectedness across firms. We construct two such measures: one based on a decomposition of bank stock returns, the other based on a decomposition of their quarterly return on assets. Network analysis of these decompositions produces measures that could be of use in financial stability monitoring as well as the analysis of individual firms’ linkages.
Hale, Galina, and Jose A. Lopez. 2018. “Monitoring Banking System Connectedness with Big Data,” Federal Reserve Bank of San Francisco Working Paper 2018-01. Available at https://doi.org/10.24148/wp2018-01