This paper shows how the combined endogenous reaction of banks and investment funds to an exogenous shock can amplify or dampen losses to the financial system compared to results from single-sector stress testing models. We build a new model of contagion propagation using a very large and granular data set for the euro area. Based on the economic shock caused by the Covid-19 outbreak, we model three sources of exogenous shocks: a default shock, a market shock and a redemption shock. Our contagion mechanism operates through a dual channel of liquidity and solvency risk. Our analysis reveals that adding the fund sector to our model for banks leads to additional losses through fire sales and a further depletion of banks’ capital ratios by around one percentage point. The main driver of additional bank losses are endogenous market losses generated by investment funds’ asset liquidation.

Capturing financial network linkages and contagion in stress test models are important goals for banking supervisors and central banks responsible for micro- and macroprudential policy. However, granular data on financial networks is often lacking, and instead the networks must be reconstructed from partial data. In this paper, we conduct a horse race of network reconstruction methods using network data obtained from 25 different markets spanning 13 jurisdictions. Our contribution is two-fold: first, we collate and analyze data on a wide range of financial networks. And second, we rank the methods in terms of their ability to reconstruct the structures of links and exposures in networks.