Exploring Nonlinearities in Financial Systemic Risk

Abstract

We propose a new methodology of assessing the effects of individual institution's risk on the others and on the system as a whole. We build upon the Conditional Value-at-Risk approach, however, we introduce the explicit Granger causal linkages and we account for possible nonlinearities in the financial time series. Conditional Value-at-Risk-Nonlinear Granger Causality, or CoVaR-NGraCo as we call it, has regular asymptotic properties which makes it particularly appealing for practical applications. We test our approach empirically and assess the contribution of the euro area financial companies to the overall systemic risk. We find that only a few financial institutions pose a serious ex ante threat to the systemic risk, whereas, given that the system is already in trouble, there are more institutions which hamper its recovery. Moreover, we discover non-negligible nonlinear structures in the systemic risk profile of the euro zone.JEL Codes: C1, G01, G20, G32