Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/164735
Title: Model-free computation of risk contributions in credit portfolios
Author: Leitao, Alvaro
Ortiz Gracia, Luis
Keywords: Risc de crèdit
Estadística no paramètrica
Mètode de Montecarlo
Credit risk
Nonparametric statistics
Monte Carlo method
Issue Date: Oct-2020
Publisher: Elsevier B.V.
Abstract: In 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 (...)
Note: Versió postprint del document publicat a: https://www.sciencedirect.com/science/article/abs/pii/S0096300320303155
It is part of: Applied Mathematics and Computation, 2020, vol. 382, num. October, p. 125351
URI: http://hdl.handle.net/2445/164735
ISSN: 0096-3003
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

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