dc.contributor |
Centre de Recerca Matemàtica |
dc.contributor.author |
Masdemont Soler, Josep |
dc.contributor.author |
Ortiz-Gracia, Luís |
dc.date.accessioned |
2011-09-01T09:37:42Z |
dc.date.available |
2011-09-01T09:37:42Z |
dc.date.created |
2011 |
dc.date.issued |
2011 |
dc.identifier.uri |
http://hdl.handle.net/2072/169247 |
dc.format.extent |
16 |
dc.format.extent |
731269 bytes |
dc.format.mimetype |
application/pdf |
dc.language.iso |
eng |
dc.publisher |
Centre de Recerca Matemàtica |
dc.relation.ispartofseries |
Prepublicacions del Centre de Recerca Matemàtica;1017 |
dc.rights |
Aquest document està subjecte a una llicència d'ús de Creative Commons, amb la qual es permet copiar, distribuir i comunicar públicament l'obra sempre que se'n citin l'autor original, la universitat i el centre i no se'n faci cap ús comercial ni obra derivada, tal com queda estipulat en la llicència d'ús (http://creativecommons.org/licenses/by-nc-nd/2.5/es/) |
dc.subject.other |
Risc de crèdit |
dc.title |
Haar wavelets-based approach for quantifying credit portfolio losses |
dc.type |
info:eu-repo/semantics/preprint |
dc.subject.udc |
336 - Finances. Banca. Moneda. Borsa |
dc.description.abstract |
This paper proposes a new methodology to compute Value at Risk (VaR) for quantifying losses in credit portfolios. We approximate the cumulative distribution of the loss function by a finite combination of Haar wavelet basis functions and calculate the coefficients of the approximation by inverting its Laplace transform. The Wavelet Approximation (WA) method is specially suitable for non-smooth distributions, often arising in small or concentrated portfolios, when the hypothesis of the Basel II formulas are violated. To test the methodology we consider the Vasicek one-factor portfolio credit loss model as our model framework. WA is an accurate, robust and fast method, allowing to estimate VaR much more quickly than with a Monte Carlo (MC) method at the same level of accuracy and reliability. |