Efficient algorithms for basket default swap pricing with multivariate Archimedean copulas

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We introduce a new importance sampling method for pricing basket default swaps employing exchangeable Archimedean copulas and nested Gumbel copulas. We establish more realistic dependence structures than existing copula models for credit risks in the underlying portfolio, and propose an appropriate density for importance sampling by analyzing multivariate Archimedean copulas. To justify efficiency and accuracy of the proposed algorithms, we present numerical examples and compare them with the crude Monte Carlo simulation, and finally show that our proposed estimators produce considerably smaller variances. (C) 2010 Elsevier By. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2011-03
Language
English
Article Type
Article
Citation

INSURANCE MATHEMATICS ECONOMICS, v.48, no.2, pp.205 - 213

ISSN
0167-6687
DOI
10.1016/j.insmatheco.2010.10.006
URI
http://hdl.handle.net/10203/96788
Appears in Collection
MA-Journal Papers(저널논문)
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