Credit Risk Contributions under the Vasicek One-factor Model: A fast wavelet expansion approximation

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

May 2011

Abstract: 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 consuming 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 computational effort in the approximation while, at the same time, the accuracy increases.

JEL Classification: C63, G21.

Keywords: Wavelets, Credit risk, VaR, Expected Shortfall, Credit Portfolio, Quantitative Finance, Risk Contributions.

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

Download paper (835K PDF) 23 pages

[