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Model risk of systemic risk models

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Statistical systemic risk measures (SRMs) have been proposed by several authors. Those generally depend on established methods from market risk forecasting. The two most common SRMs, MES and CoVaR, along with VaR, are compared theoretically and then critically empirically analyzed. They are found to contain a high degree of model risk so that the signal they produce is highly unreliable. Finally, the papers discusses the main problems in systemic risk forecasting and proposed evaluation criteria fur such models.

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