An Analytical Model Of Contagion

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cite{gai} developed an analytical model of contagion in financial networks with arbitrary structure which distinguishes the probability of contagious default from its potential spread using statistical techniques from the literature on complex networks citep[see][]{stro} into a financial system setting. Their paper finds that although contagion risk is low, the effects can be extremely widespread.

In the financial network literature, cite{alleng} provide microeconomic foundations for financial contagion. Using a liquidity preference model in which a shock to one part of the economy can spread to other parts and potentially lead to an economy wide financial crisis, they find evidence connectivity and incompleteness are conductive of contagion. Similarly, cite{freix} analyse the stability of the banking system when one bank becomes insolvent, the role of the central bank and the effect on market discipline. They use a model of payment flows similar to cite{dd} and find that connectedness boosts resilience of the system but the too-big-to-fail policy has moral hazard implications when the central bank intervenes to allow an insolvent bank to continue operating. On the other hand, cite{bru} model contagion in the interbank deposit market, using the return on the gambling asset as the mechanism of contagion in this network. They find greater connectivity increases contagion risk through two channels, the first is that banks make more risky investments given that more financial
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