Abstract
This paper introduces an empirical analysis of a selective model for the impact on various sources of financial risk, with particular focus on credit risk. Practitioners in risk management are still strongly linked to value-at-risk as the most widely used methodology for the analysis and prediction of financial risk. Modern research in financial economics shows that this approach becomes misleading if we relax some constraints in order to get closer to the real world. The model tries to overtake the inadequacy of value-at-risk by introducing a selection algorithm.
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