Monte Carlo Methods for Portfolio Credit Risk
The 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.
|Date of creation:||Jul 2012|
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- L. Randall Wray & Stephanie Bell, 2004. "Introduction," Chapters,in: Credit and State Theories of Money, chapter 1 Edward Elgar Publishing.
- Paul Glasserman & Jingyi Li, 2005. "Importance Sampling for Portfolio Credit Risk," Management Science, INFORMS, vol. 51(11), pages 1643-1656, November.
- 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.
- Nikolay Nenovsky & S. Statev, 2006. "Introduction," Post-Print halshs-00260898, HAL.
- Donnelly, Catherine & Embrechts, Paul, 2010. "The Devil is in the Tails: Actuarial Mathematics and the Subprime Mortgage Crisis," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 40(01), pages 1-33, May.
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