Measuring systemic risk: a model uncertainty approach
Systemic risk is concerned with the failure of an interconnected system as a consequence of the actions of its components. In the event of a financial crisis, it becomes important to measure and allocate the systemic risk of a network of financial institutions. In this talk, we will focus on a recent multivariate approach for measuring systemic risk where the state of the financial network is modeled as a random vector of individual equities/losses. Then, the systemic risk measure is defined as the set of all capital allocation vectors that make the “impact of the system to the society” acceptable. We present a dual representation theorem for systemic risk measures and provide a “model uncertainty” and “weight ambiguity” interpretation of the dual variables. As a special case, we will consider a financial system with exponential aggregation mechanism, where the distances of the financial institutions with respect to the society are measured in terms of relative entropies.