Scenario-Free Analysis of Financial Stability with Interacting Contagion Channels

Currently financial stress test simulations that take into account multiple interacting contagion mechanisms are conditional on a specific, subjectively imposed stress-scenario. Eigenvalue-based approaches, in contrast, provide a scenario-independent measure of systemic stability, but only handle a single contagion mechanism. We develop an eigenvalue-based approach that gives the best of both worlds, allowing analysis of multiple, interacting contagion channels without the need to impose a subjective stress scenario. This allows us to demonstrate that the instability due to interacting channels can far exceed that of the sum of the individual channels acting alone. We derive an analytic formula in the limit of a large number of institutions that gives the instability threshold as a function of the relative size and intensity of contagion channels, providing valuable insights into financial stability whilst requiring very little data to be calibrated to real financial systems.