Leitao, AlvaroOrtiz Gracia, Luis2020-06-082022-10-312020-100096-3003https://hdl.handle.net/2445/164735In this work, we propose a non-parametric density estimation technique for measuring the risk in a credit portfolio, aiming at efficiently computing the marginal risk contributions. The novel method is based on wavelets, and we derive closed-form expressions to calculate the Value-at-Risk (VaR), the Expected Shortfall (ES) as well as the individual risk contributions to VaR (VaRC) and ES (ESC). We consider the multi-factor Gaussian and t-copula models for driving the defaults. The results obtained along the numerical experiments show the impressive accuracy and speed of this method when compared with crude Monte Carlo simulation (...)application/pdfengcc-by-nc-nd (c) Elsevier B.V., 2020http://creativecommons.org/licenses/by-nc-nd/3.0/esRisc de crèditEstadística no paramètricaMètode de MontecarloCredit riskNonparametric statisticsMonte Carlo methodinfo:eu-repo/semantics/article7007992020-06-08info:eu-repo/semantics/openAccess