RiskRank: Measuring interconnected risk

Given the consequences of the recent financial crisis, there is an increased interest in modelling and predicting the behaviour of complex financial systems. As a novel approach to measuring risk in networks, this paper proposes RiskRank as a general-purpose aggregation operator of risk in nodes and links. RiskRank relies on a system represented as a hierarchical network, where node values and linkages represent individual risk levels and interconnectedness, respectively. The measure is used to aggregate risk in the vein of a novel network centrality measure, allowing for the integration of the interrelations of different entities in the network with any other measure of node risk. The use of RiskRank is illustrated through a real-world case on systemic risk in Europe, in which we show that it improves performance in out-of-sample analysis. We provide an estimation of systemic risk from country-level risk indicators and combine it with cross-border linkages to illustrate the practical benefit of the proposed approach. From a policy perspective, our results strengthen the results of previous research and underline the importance of integrating a network perspective in macro-prudential analysis.