Credit risk contagion

Current approaches to credit risk modelling typically explain correlation between companies by their exposure to common macroeconomic and financial risk factors. However, this explanation must be incomplete as common sense tells us that a credit event at one company affects the solvency of related companies directly. This effect is known intuitively by risk managers and regulators, which is why they track the interconnectedness of the companies they oversee. In this article, we suggest a way of adding the idiosyncratic interconnectedness of companies to existing portfolio models. In these models, the default of individual companies is considered to be independent, conditional on the overall state of the market. In the model presented in this article, the default of individual companies also depends on the default state of all related companies in the previous time step. By recognising that credit events can be transmitted by business relationships between companies, clusters of defaults become more likely. This in turn increases the concentration of loss events and the capital requirements.

This article presents an approach to modelling this 'credit contagion', the spread of credit events between related companies. Previous approaches have considered adding contagion effects into credit risk models, but have generally required a complex implementation. In our approach, we combine credit contagion with the general factor correlation of a standard Merton portfolio model to create a model that is relatively straightforward to implement and parameterise. In this model, if one firm is 'infected' by a credit event, there will be a knock-on effect on related firms, and the effect is proportional to the strength of the relationship. Specifically, in the time period following the credit event, the asset value of the infected firm's suppliers will decrease by an amount proportional to the strength of the sales relationship between them.

The contagion risk part of the model is inspired by modern epidemic models (see, for example, Halloran et al, 2002). These models relate the risk of contagion between two individuals in a population to the closeness of their relationship. In general, infected individuals are most likely to infect their family members, somewhat less likely to infect their fellow workers and students, and relatively unlikely to infect random members of the public. Each new infection sets off another chain of contagion. Readers who have school-age children, or who have co-workers who do, will be aware of this effect.

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