Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/40319 
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dc.contributor.authorHager, Svenjaen
dc.contributor.authorSchöbel, Raineren
dc.date.accessioned2008-02-21-
dc.date.accessioned2010-09-24T14:42:26Z-
dc.date.available2010-09-24T14:42:26Z-
dc.date.issued2006-
dc.identifier.piurn:nbn:de:bsz:21-opus-21859en
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
dc.language.isoengen
dc.publisher|aEberhard Karls Universität Tübingen, Wirtschaftswissenschaftliche Fakultät |cTübingenen
dc.relation.ispartofseries|aTübinger Diskussionsbeiträge |x300en
dc.subject.ddc330en
dc.subject.stwFinanzderivaten
dc.subject.stwKreditsicherungen
dc.subject.stwWertpapieranalyseen
dc.subject.stwPortfolio-Managementen
dc.subject.stwEvolutionärer Algorithmusen
dc.subject.stwTheorieen
dc.titleDeriving the dependence structure of portfolio credit derivatives using evolutionary algorithms-
dc.typeWorking Paperen
dc.identifier.ppn558781845en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:tuedps:300en

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