Systemic risk and financial interconnectedness: network measures and the impact of the indirect effect.

This paper considers several network measures of connectedness applied to the network extracted using pairwise quantile regressions, i.e. it proposes the use of quantile based network measures to estimate the importance of Globally Systemically Important Financial Institutions. The purpose is to assert the different informative content between quantile based network measures and quantile based loss measures such as CoVaR. We consider Globally Systemically Important Banks and Insurers and several Hedge Fund indices. We investigate whether systemic risk indicators based on network measures are similar to those based on CoVaR and show that they are capturing different features. In particular, quantile regression based on network measures capture the indirect effect of risk spillovers that is instead ignored by quantile based loss measures. Finally, we compare quantile based network measures and quan- tile based losses measures highlighting the predicting power of the former during the global systemic crisis of 2007/2008.