Related Experiment Video
Updated: Apr 6, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks
Matteo Smerlak1, Brady Stoll2, Agam Gupta3
1Perimeter Institute for Theoretical Physics, 31 Caroline Street North, N2L 2Y5 Waterloo ON, Canada.
Abstract:
The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology.
Related Concept Videos
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
Propagation of Uncertainty from Systematic Error
Hazard Rate
Critical Values
Multimachine Stability
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
First Derivative Test: Problem Solving