Ranking Consistency of Systemic Risk Measures: A Simulation-Based Analysis in a Banking Network Model

Abstract

In a banking network model, the ranking consistency of various popular systemic risk measures (SRMs) is analyzed. In contrast to previous studies, this model-based analysis offers the advantage that the sensitivity of the ranking consistency with respect to bank and network characteristics can easily be checked. The employed network model accounts, among others, for bank insolvencies as well as illiquidities, stochastic dependencies of non-bank loans as well as of liquidity buffer assets across various banks, bank rating-dependent volumes of deposits and interbank liabilities, and the funding liquidity reducing effect of fire sales of other banks. Within the assumed banking network model, it can be shown that, in general, the ranking consistency (measured by the rank correlation) of various SRMs is rather low. Furthermore, the ranking consistency can significantly vary, for example, for an increasing correlation between the returns of the liquidity buffer assets across banks, for an increasing degree of heterogeneity in the banks’ balance sheets or with a changing network structure of the banking system. However, forecasting which effect a specific change in parameters, bank behavior or network characteristics has on the ranking consistency of SRMs in general seems to be rather difficult because the sign of the effect can be different for different pairs of SRMs.