Cascades in multiplex financial networks with debts of different seniority

TL;DR

This paper models the impact of debt seniority in multiplex financial networks on systemic stability, showing that mixing debt levels can reduce cascading defaults and identifying optimal seniority ratios.

Contribution

It introduces a multiplex network model incorporating debt seniority, analyzing its effect on cascade dynamics and deriving optimal seniority ratios for stability.

Findings

Mixing debt seniority levels enhances system stability.

Optimal seniority ratio increases as default thresholds decrease.

Analytical results extend to multiple seniority levels and heavy-tailed networks.

Abstract

The seniority of debt, which determines the order in which a bankrupt institution repays its debts, is an important and sometimes contentious feature of financial crises, yet its impact on system-wide stability is not well understood. We capture seniority of debt in a multiplex network, a graph of nodes connected by multiple types of edges. Here, an edge between banks denotes a debt contract of a certain level of seniority. Next we study cascading default. There exist multiple kinds of bankruptcy, indexed by the highest level of seniority at which a bank cannot repay all its debts. Self-interested banks would prefer that all their loans be made at the most senior level. However, mixing debts of different seniority levels makes the system more stable, in that it shrinks the set of network densities for which bankruptcies spread widely. We compute the optimal ratio of senior to junior debts, which we call the optimal seniority ratio, for two uncorrelated Erdos-Renyi networks. If institutions erode their buffer against insolvency, then this optimal seniority ratio rises; in other words, if default thresholds fall, then more loans should be senior. We generalize the analytical results to arbitrarily many levels of seniority and to heavy-tailed degree distributions.