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Credit risk contributions under the Vasicek one-factor model: a fast wavelet expansion approximation

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Masdemont Soler, JosepMés informacióMés informacióMés informació
Ortiz-Gracia, Luis
Document typeArticle
Defense date2014-06
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
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 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
CitationMasdemont, J.J.; Ortiz-Gracia, L. Credit risk contributions under the Vasicek one-factor model: a fast wavelet expansion approximation. "Journal of Computational Finance", Juny 2014, vol. 17, núm. 4, p. 59-97. 
URIhttp://hdl.handle.net/2117/26597
ISSN1460-1559
Publisher versionhttp://www.risk.net/journal-of-computational-finance/journal/2347954/latest-issue-of-the-journal-of-computational-finance-volume-17-issue-4-2014
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