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Computing worst-case tail probabilities in credit risk

Published: 03 December 2006 Publication History

Abstract

Simulation is widely used to measure credit risk in portfolios of loans, bonds, and other instruments subject to possible default. This analysis requires performing the difficult modeling task of capturing the dependence between obligors adequately. Current methods assume a form for the joint distribution of the obligors and match its parameters to given dependence specifications, usually correlations. The value-at-risk risk measure (a function of its tail quantiles) is then evaluated. This procedure is naturally limited by the form assumed, and might not approximate well the "worstcase" possible over all joint distributions that match the given specification. We propose a procedure that approximates the joint distribution with chessboard distributions, and provides a sequence of improving estimates that asymptotically approach this "worst-case" value-at-risk. We use it to experimentally compare the quality of the estimates provided by the earlier procedures.

References

[1]
Basel Committee on Banking Supervision, 2002. The new basel capital accord. <http://www.bis.org/bcbs/bcbscp2.htm>.
[2]
Bassamboo, A., S. Juneja, and A. Zeevi. 2005. Expected shortfall in credit portfolios with extremal dependence. In Proceedings of the 2005 Winter Simulation Conference, ed. M. E. Kuhl, N. M. Steiger, F. B. Armstrong, and J. A. Joines.
[3]
Bassamboo, A., S. Juneja, and A. Zeevi. 2007. Portfolio credit risk with extremal dependence: Asymptotic analysis and efficient simulation. Operations Research. To Appear.
[4]
Billingsley, P. 1986. Probability and measure. 2nd ed. New York: Wiley.
[5]
Billingsley, P. 1995. Probability and measure. 3rd ed. New York: Wiley.
[6]
Ghosh, S. 2004. Dependence in stochastic simulation models. Ph.D. thesis, Department of Operations Research and Industrial Engineering, Cornell University, Ithaca, NY.
[7]
Ghosh, S., and S. G. Henderson. 2002. Chessboard distributions and random vectors with specified marginals and covariance matrix. Operations Research 50 (5): 820--834.
[8]
Glasserman, P., P. Heidelberger, and P. Shahabuddin. 2002. Portfolio value-at-risk with heavy-tailed risk factors. Mathematical Finance 12:239--269.
[9]
Glasserman, P., and J. Li. 2005. Importance sampling for portfolio credit risk. Management Science 51:1643--1656.
[10]
Gupta, G., C. Finger, and M. Bhatia. 1997. Credit metrics technical document. Technical report, J. P. Morgan & Co., New York.
[11]
Kealhofer, S., and J. Bohn. 2001. Portfolio management of credit risk. Technical report, KMV working paper, New York.
[12]
Mashal, R., and A. Zeevi. 2003. Beyond correlation: extreme co-movements between financial assets. <http://ssrn.com/abstract=317122>.
[13]
Queyranne, M., and F. C. R. Spieksma. 1997. Approximation algorithms for multi-index transportation problems with decomposable costs. Discrete Applied Mathematics 76:239--254.
[14]
Queyranne, M., and F. C. R. Spieksma. 2001. Multi-index transportation problems. In The Encyclopedia of Optimization, ed. F. C. and P. Pardalos, 450--456. Dordrecht: Kluwer.

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  • (2018)Improving offensive cyber security assessments using varied and novel initialization perspectivesProceedings of the 2018 ACM Southeast Conference10.1145/3190645.3190673(1-9)Online publication date: 29-Mar-2018

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Published In

cover image ACM Conferences
WSC '06: Proceedings of the 38th conference on Winter simulation
December 2006
2429 pages
ISBN:1424405017

Sponsors

  • IIE: Institute of Industrial Engineers
  • ASA: American Statistical Association
  • IEICE ESS: Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
  • IEEE-CS\DATC: The IEEE Computer Society
  • SIGSIM: ACM Special Interest Group on Simulation and Modeling
  • NIST: National Institute of Standards and Technology
  • (SCS): The Society for Modeling and Simulation International
  • INFORMS-CS: Institute for Operations Research and the Management Sciences-College on Simulation

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Winter Simulation Conference

Publication History

Published: 03 December 2006

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WSC06
Sponsor:
  • IIE
  • ASA
  • IEICE ESS
  • IEEE-CS\DATC
  • SIGSIM
  • NIST
  • (SCS)
  • INFORMS-CS
WSC06: Winter Simulation Conference 2006
December 3 - 6, 2006
California, Monterey

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WSC '06 Paper Acceptance Rate 177 of 252 submissions, 70%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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  • (2018)Improving offensive cyber security assessments using varied and novel initialization perspectivesProceedings of the 2018 ACM Southeast Conference10.1145/3190645.3190673(1-9)Online publication date: 29-Mar-2018

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