Network analysis and systemic FX settlement risk

Abstract

Abstract A proposal for applying network analysis to a foreign exchange (FX) settlement system is considered. In particular, network centrality metrics are used to analyse payments of financial institutions which settle through CLS Bank (CLS). Network centrality metrics provide a way to study settlement members’ connectivity, obtain a sense of their payments evolution with time, and measure their network topology variability. The analysis shows that although the continuous link settlement (CLS) network structure can be approximated with a power law degree distribution for many trade days, this is not always the case. A network community detection algorithm is applied to the FX settlement network to explore relationships between communities and to detect classification patterns in the FX trading net payments. A metric called SinkRank is used to build a ranking of the most systemic settlement risk important financial institutions trading on the FX system, and to understand how the metric depends on network’s connectivity. Since network metrics do not fully explain the dynamics of the settlement process, the CLS’ settlement system is simulated to measure the contagion of unsettled trades and its spread among network members. The effect of settlement failure and contagion on the settlement members is also explored.