Evolution of Credit Risk Using a Personalized Pagerank Algorithm for Multilayer Networks

In this paper we present a novel algorithm to study the evolution of credit risk across complex multilayer networks. Pagerank-like algorithms allow for the propagation of an influence variable across single networks, and allow quantifying the risk single entities (nodes) are subject to given the connection they have to other nodes in the network... (read more)

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