the web's biggest credit risk modeling resource.

Credit Jobs

Home Glossary Links FAQ / About Site Guide Search


Submit Your Paper

In Rememberance: World Trade Center (WTC)

Export citation to:
- Text (plain)
- BibTeX

Haar Wavelets-based Approach for Quantifying Credit Portfolio Losses

by Josep J. Masdemont of the Universitat Politècnica de Catalunya, and
Luis Ortiz-Gracia of the Centre de Recerca Matemàtica

April 2011

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.

JEL Classification: C63, G21.

Keywords: Wavelets, Credit risk, VaR, Credit Portfolio, Quantitative Finance.

Forthcoming in: Quantitative Finance.

Books Referenced in this paper:  (what is this?)

Download paper (732K PDF) 16 pages