Measuring systemic risk: A factor-augmented correlated default approach
In this paper, we extend existing correlated default models for measuring systemic risk by proposing a model that incorporates an observable common factor that features conditional heteroscedasticity. The addition of the common factor helps to effectively capture realistic time-varying characteristics in individual asset return volatility as well as return correlations. We apply the model for large US financial institutions. The common factor proves its importance in explaining asset return dynamics and measuring systemic risk. We also apply the model in the context of systemic risk contribution analysis and show its applicability.
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