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Accepted version

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2020-10

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cc-by-nc-nd (c) Elsevier B.V., 2020
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/164735

Model-free computation of risk contributions in credit portfolios

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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 (...)

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Risc de crèdit, Estadística no paramètrica, Mètode de Montecarlo

Subject (English)

Credit risk, Nonparametric statistics, Monte Carlo method

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

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LEITAO, Alvaro and ORTIZ GRACIA, Luis. Model-free computation of risk contributions in credit portfolios. Applied Mathematics and Computation. 2020. Vol. 382, num. October, pags. 125351. ISSN 0096-3003. [consulted: 18 of August of 2026]. Available at: https://hdl.handle.net/2445/164735

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