Our papers are the official record of our discoveries. They allow others to build on and apply our work. Each paper is the result of many months of research, so we make a special effort to make them clear, beautiful and inspirational, and publish them in leading journals.
Statistical physics contributes to new models and metrics for the study of financial network structure, dynamics, stability and instability.
Fire sales of common asset holdings can whip through a channel of contagion between banks, insurance companies and investments funds.
Consistent valuation of interbank claims within an interconnected financial system can be found with a recursive update of banks' equities.
A mathematical model captures the temporal and steady state behaviour of networks whose two sets of nodes either generate or destroy links.
Exact solutions for the dynamics of interacting memristors predict whether they relax to higher or lower resistance states given random initialisations.
Network users who have access to the network’s most informative node, as quantified by a novel index, the InfoRank, have a competitive edge.
An iterative version of a method to identify hierarchies and rankings of nodes in directed networks can partly overcome its resolution limit.
The large-scale structure of the interbank network changes drastically in times of crisis due to the effect of measures from central banks.
An explicit analytical solution reproduces the main features of random graph ensembles with many short cycles under strict degree constraints.
Complex networks model the links between financial institutions and how these channels can transition from diversifying to propagating risk.
The spectral density of graph ensembles provides an exact solution to the graph partitioning problem and helps detect community structure.
Inference from single snapshots of temporal networks can misleadingly group communities if the links between snapshots are correlated.