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dc.contributor.authorHager, Svenjaen_US
dc.contributor.authorSchöbel, Raineren_US
dc.date.accessioned2008-02-21en_US
dc.date.accessioned2010-09-24T14:42:26Z-
dc.date.available2010-09-24T14:42:26Z-
dc.date.issued2006en_US
dc.identifier.piurn:nbn:de:bsz:21-opus-21859en_US
dc.identifier.urihttp://hdl.handle.net/10419/40319-
dc.description.abstractEven if the correct modeling of default dependence is essential for the valuation of portfolio credit derivatives, for the pricing of synthetic CDOs a one-factor Gaussian copula model with constant and equalpairwise correlationsfor all assets in the reference portfolio has become the standard market model. If this model were a re?ection of market opinion, there wouldn't be the implied correlation smilethatis observedinthe market. Thepurposeof thispaperistoderive a correlation structure from observed CDO tranche spreads. The correlation structure is chosen such that all tranche spreads of the traded CDO can be reproduced. This implied correlation structure can then be used to price o?-market tranches with the same underlying as the traded CDO. Using this approach we can significantly reduce the risk to misprice o?-market derivatives. Due to the complexity of the optimization problem we apply Evolutionary Algorithms.en_US
dc.language.isoengen_US
dc.publisherUniv., Wirtschaftswiss. Fak. Tübingenen_US
dc.relation.ispartofseriesTübinger Diskussionsbeitrag 300en_US
dc.subject.ddc330en_US
dc.subject.stwFinanzderivaten_US
dc.subject.stwKreditsicherungen_US
dc.subject.stwWertpapieranalyseen_US
dc.subject.stwPortfolio-Managementen_US
dc.subject.stwEvolutionärer Algorithmusen_US
dc.subject.stwTheorieen_US
dc.titleDeriving the dependence structure of portfolio credit derivatives using evolutionary algorithmsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn558781845en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:tuedps:300-
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