M. Bardoscia

P. Barucca

Statistical physics contributes to new models and metrics for the study of financial network structure, dynamics, stability and instability.

Consistent valuation of interbank claims within an interconnected financial system can be found with a recursive update of banks' equities.

Processes believed to stabilize financial markets can drive them towards instability by creating cyclical structures that amplify distress.

Non-linear models of distress propagation in financial networks characterise key regimes where shocks are either amplified or suppressed.

Percolation theory shows that the formation of giant clusters of neurons relies on a few parameters that could be measured experimentally.

A dynamical microscopic theory of instability for financial networks reformulates the DebtRank algorithm in terms of basic accounting principles.