Cascades in multiplex financial networks with debts of different seniority

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 systemwide 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 Erdős-Rényi 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.

Extracting the multi-timescale activity patterns of online financial markets

“…This work lays out the foundations for other researchers to study how patterns and anomalies emerge in financial systems at different temporal resolutions: in the future, such a framework could contribute to controlling the spread of financial systemic risk [9,10,[29][30][31]. It would be interesting to investigate whether our method could be used both in predictive and prescriptive ways to help determine what could happen under certain risk conditions, as well as to provide possible intervention strategies prior to shocks or cascading collapses in financial systems.…”

“…Importantly, even in a situation in which bank activity has certain patterns at intra-and inter-day scales, it remains of paramount importance to understand whether the intra-day patterns are independent of the inter-day patterns (i.e., mono-timescale patterns) or they are correlated with each other (i.e., multitimescale patterns). Our framework to extract multi-timescale patterns advances the understanding of when and how banks react to systemic shocks, and in the future it could contribute to controlling the spread of financial systemic risk [9,10,[29][30][31].…”

The evolution of risk and bailout strategy in banking systems

“…Therefore, a potential area of future research would be to improve realism by extending the work to include a more detailed representation of contagion channels, e.g. based on the recent literature on multiplex networks (Montagna and Kok, 2013;Brummitt and Kobayashi, 2015;Poledna et al, 2015). Another possible avenue for future work would be to allow bank connections to evolve over time as strategies change, creating an adaptive network of interconnected balance sheets.…”

Spreading of localized attacks in spatial multiplex networks

“…Most infrastructure is embedded in space, for example the power grid and sewer networks, and thus, several models have been proposed for understanding the vulnerability of spatially embedded networks [1][2][3][4][5][6][7][8][9]. In addition, in recent years, world-wide human, technological, social and economic systems have become more and more integrated and interdependent, affecting infrastructure robustness [10][11][12][13] as well as information spreading [14] and other socioeconomic processes [15][16][17]. Therefore, it is necessary to realistically model these systems as interdependent in order to understand their structure, function and vulnerabilities [18][19][20][21][22][23][24][25][26][27][28].…”