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# An application to credit risk of a hybrid Monte Carlo-Optimal quantization method

## Author

Listed:
• Giorgia Callegaro

(PMA)

• Abass Sagna

(PMA)

## Abstract

In this paper we use a hybrid Monte Carlo-Optimal quantization method to approximate the conditional survival probabilities of a firm, given a structural model for its credit defaul, under partial information. We consider the case when the firm's value is a non-observable stochastic process $(V_t)_{t \geq 0}$ and inverstors in the market have access to a process $(S_t)_{t \geq 0}$, whose value at each time t is related to $(V_s, s \leq t)$. We are interested in the computation of the conditional survival probabilities of the firm given the "investor information". As a application, we analyse the shape of the credit spread curve for zero coupon bonds in two examples.

## Suggested Citation

• Giorgia Callegaro & Abass Sagna, 2009. "An application to credit risk of a hybrid Monte Carlo-Optimal quantization method," Papers 0907.0645, arXiv.org.
• Handle: RePEc:arx:papers:0907.0645
as

File URL: http://arxiv.org/pdf/0907.0645

## References listed on IDEAS

as
1. Delia Coculescu & Hélyette Geman & Monique Jeanblanc, 2008. "Valuation of default-sensitive claims under imperfect information," Finance and Stochastics, Springer, vol. 12(2), pages 195-218, April.
2. Gobet, Emmanuel, 2000. "Weak approximation of killed diffusion using Euler schemes," Stochastic Processes and their Applications, Elsevier, vol. 87(2), pages 167-197, June.
3. Pham Huyên & Runggaldier Wolfgang & Sellami Afef, 2005. "Approximation by quantization of the filter process and applications to optimal stopping problems under partial observation," Monte Carlo Methods and Applications, De Gruyter, vol. 11(1), pages 57-81, March.
4. Duffie, Darrell & Lando, David, 2001. "Term Structures of Credit Spreads with Incomplete Accounting Information," Econometrica, Econometric Society, vol. 69(3), pages 633-664, May.
5. Pagès Gilles & Printems Jacques, 2003. "Optimal quadratic quantization for numerics: the Gaussian case," Monte Carlo Methods and Applications, De Gruyter, vol. 9(2), pages 135-165, April.
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