Credit risk contributions under the Vasicek one-factor model: a fast wavelet expansion approximation
| Autor: | Josep Masdemont Soler, Luis Ortiz-Gracia |
|---|---|
| Přispěvatelé: | Centre de Recerca Matemàtica, Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada I, Universitat Politècnica de Catalunya. EGSA - Equacions Diferencials, Geometria, Sistemes Dinàmics i de Control, i Aplicacions |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
Vasicek model
Risc de crèdit Applied Mathematics Computation Monte Carlo method Matemàtiques i estadística [Àrees temàtiques de la UPC] Credit--Mathematical models Wavelets (Mathematics) Measure (mathematics) 33 - Economia Impostos Computer Science Applications Expected shortfall Crèdit -- Models matemàtics Risc (Economia) Order (exchange) Econometrics Bancs -- Gestió del risc Ondetes (Matemàtica) Finance Value at risk Credit risk Mathematics |
| Zdroj: | RECERCAT (Dipòsit de la Recerca de Catalunya) Recercat. Dipósit de la Recerca de Catalunya instname Universitat Jaume I UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Popis: | To measure the contribution of individual transactions inside the total risk of a credit portfolio is a major issue in financial institutions. VaR Contributions (VaRC) and Expected Shortfall Contributions (ESC) have become two popular ways of quantifying the risks. However, the usual Monte Carlo (MC) approach is known to be a very time consum- ing method for computing these risk contributions. In this paper we consider the Wavelet Approximation (WA) method for Value at Risk (VaR) computation presented in [Mas10] in order to calculate the Expected Shortfall (ES) and the risk contributions under the Vasicek one-factor model framework. We decompose the VaR and the ES as a sum of sensitivities representing the marginal impact on the total portfolio risk. Moreover, we present technical improvements in the Wavelet Approximation (WA) that considerably reduce the computa- tional effort in the approximation while, at the same time, the accuracy increases |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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