An integral part of advanced stress-testing frameworks is the macrofinancial model, which maps the impact of macroeconomic shocks on bank-specific risk factors. The standard practice for the development of such models is the use of a single model. However, such an approach exposes the whole framework to model risk, since any individual model may be misspecified and/or affected by structural changes in ways that can be very difficult to predict in advance. To address this issue, we use a model combination approach to develop robust macrofinancial models for credit risk stress testing. The empirical part utilizes data from the Greek economy, which experienced a sharp change from normal to distressed conditions; this makes it a particularly challenging case to forecast. The results expose the inadequacy of any individual model to capture the evolution of credit risk and indicate that relying on a single model can result in significant misestimation of risk. This holds whether the estimation sample includes only precrisis information or data from both tranquil and stressed periods. However, model combination gives a better forecasting performance than standard benchmark models. Overall, the proposed approach can lead to a more robust assessment of risk.
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