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Model-free computation of risk contributions in credit portfolios

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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 (...)

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Applied Mathematics and Computation, 2020, vol. 382, num. October, p. 125351

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Articles publicats en revistes  (Econometria, Estadística i Economia Aplicada)

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Model-free computation of risk contributions in credit portfolios