On the measure of contagion in fuzzy financial networks

Abstract

Previous literature shows that financial networks are sometimes described by fuzzy data. This paper aims to extend classical models of financial contagion to the framework of fuzzy financial networks. The degree of default of each bank in the network is defined. It consists in a (real valued) measure of the fuzzy default and it is computed as a fixed point for the dynamics of a modified “fictitious default algorithm”. Two specific models of degree of default are also introduced and investigated; namely, an optimistic model and a pessimistic one. Finally, the algorithm is implemented in Matlab and tested numerically on a real data set.