Complex non-linear interactions between banks and assets we model by two time-dependent Erdos Renyi network models where each node, representing bank, can invest either to a single asset (model I) or multiple assets (model II). We use dynamical network approach to evaluate the collective financial failure---systemic risk---quantified by the fraction of active nodes. The systemic risk can be calculated over any future time period, divided on sub-periods, where within each sub-period banks may contiguously fail due to links to either (i) assets or (ii) other banks, controlled by two parameters, probability of internal failure p and threshold T_h ( ``solvency'' parameter). The systemic risk non-linearly increases with p and decreases with average network degree faster when all assets are equally distributed across banks than if assets are randomly distributed. The more inactive banks each bank can endure (smaller T_h), the smaller the systemic risk---for some T_h values in %DIFDELCMD < {\bf %%% I we report a discontinuity in systemic risk. When contiguous spreading becomes stochastic (ii) controlled by probability p_2---a condition for the bank to be solvent (active) is stochastic---with increasing p_2, the systemic risk decreases with both pand T_h . We analyse asset allocation for the U.S. banks.
Complex non-linear interactions between banks and assets we model by two time-dependent Erdos Renyi network models where each node, representing bank, can invest either to a single asset (model I) or multiple assets (model II). We use dynamical network approach to evaluate the collective financial failure---systemic risk---quantified by the fraction of active nodes. The systemic risk can be calculated over any future time period, divided on sub-periods, where within each sub-period banks may contiguously fail due to links to either (i) assets or (ii) other banks, controlled by two parameters, probability of internal failure p and threshold T_h ( "solvency" parameter). The systemic risk non-linearly increases with p and decreases with average network degree faster when all assets are equally distributed across banks than if assets are randomly distributed. The more inactive banks each bank can sustain (smaller T_h), the smaller the systemic risk---for some T_h values in %DIFDELCMD < {\bf %%% I we report a discontinuity in systemic risk. When contiguous spreading becomes stochastic (ii) controlled by probability p_2---a condition for the bank to be solvent (active) is stochastic---the systemic risk decreases with decreasing p_2 . We analyse asset allocation for the U.S. banks.
R
``solvency''
"solvency"
R
endure
sustain
R
I
I
R
stochastic---with increasing p_2, the
stochastic---the
R
both pand T_h
decreasing p_2