We characterize the evolution over time of a network of credit relations among financial agents as a system of coupled stochastic processes. Each process describes the dynamics of individual financial robustness, while the coupling results from a network of liabilities among agents. The average level of risk diversification of the agents coincides with the density of links in the network. In addition to a process of diffusion of financial distress, we also consider a discrete process of default cascade, due to the re-evaluation of agents' assets. In this framework we investigate the probability of individual defaults as well as the probability of systemic default as a function of the network density. While it is usually thought that diversification of risk always leads to a more stable financial system, in our model a tension emerges between individual risk and systemic risk. As the number of counterparties in the credit network increases beyond a certain value, the default probability, both individual and systemic, starts to increase. This tension originates from the fact that agents are subject to a financial accelerator mechanism. In other words, individual financial fragility feeding back on itself may amplify the effect of an initial shock and lead to a full fledged systemic crisis. The results offer a simple possible explanation for the endogenous emergence of systemic risk in a credit network.

We present a simple model of a production network in which firms are linked by supplier-customer relationships involving extension of trade-credit. Our aim is to identify the minimal set of mechanisms which reproduce qualitatively the main stylized facts of industrial demography, such as firms' size distribution, and, at the same time, the correlation, over time and across firms, of output, growth and bankruptcies. The behavior of aggregate variables can be traced back to the direct firm-firm interdependence. In this paper, we assume that the number of firms is constant and the network has a periodic static structure. But the framework allows further extensions to investigate which network structures are more robust against domino effects and, if the network is let to evolve in time, which structures emerge spontaneously, depending on the individual strategies for orders and delivery. r

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