Monte Carlo Methods for Portfolio Credit Risk
AbstractThe financial crisis of 2007 – 2009 began with a major failure in credit markets. The causes of this failure stretch far beyond inadequate mathematical modeling (see Donnelly and Embrechts  and Brigo et al.  for detailed discussions from a mathematical finance perspective). Nevertheless, it is clear that some of the more popular models of credit risk were shown to be flawed. Many of these models were and are popular because they are mathematically tractable, allowing easy computation of various risk measures. More realistic (and complex) models come at a significant computational cost, often requiring Monte Carlo methods to estimate quantities of interest.
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Bibliographic InfoPaper provided by Australian National University, College of Business and Economics, School of Economics in its series ANU Working Papers in Economics and Econometrics with number 2012-579.
Length: 33 Pages
Date of creation: Jul 2012
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-08-23 (All new papers)
- NEP-BAN-2012-08-23 (Banking)
- NEP-RMG-2012-08-23 (Risk Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Chan, Joshua C.C. & Kroese, Dirk P., 2010. "Efficient estimation of large portfolio loss probabilities in t-copula models," European Journal of Operational Research, Elsevier, vol. 205(2), pages 361-367, September.
- Damiano Brigo & Andrea Pallavicini & Roberto Torresetti, 2009. "Credit models and the crisis, or: how I learned to stop worrying and love the CDOs," Papers 0912.5427, arXiv.org, revised Feb 2010.
- Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
- repec:cup:cbooks:9780521496032 is not listed on IDEAS
- Paul Glasserman & Jingyi Li, 2005. "Importance Sampling for Portfolio Credit Risk," Management Science, INFORMS, vol. 51(11), pages 1643-1656, November.
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