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dc.contributor.authorFengler, Matthias R.en
dc.contributor.authorHärdle, Wolfgangen
dc.contributor.authorMammen, Ennoen
dc.date.accessioned2012-11-19T15:23:21Z-
dc.date.available2012-11-19T15:23:21Z-
dc.date.issued2003-
dc.identifier.piurn:nbn:de:kobv:11-10050885en
dc.identifier.urihttp://hdl.handle.net/10419/66280-
dc.description.abstractA primary goal in modelling the dynamics of implied volatility surfaces (IVS) aims at reducing complexity. For this purpose one fits the IVS each day and applies a principal component analysis using a functional norm. This approach, however, neglects the degenerated string structure of the implied volatility data and may result in a severe modelling bias. We propose a dynamic semiparametric factor model, which approximates the IVS in a finite dimensional function space. The key feature is that we only fit in the local neighborhood of the design points. Our approach is a combination of methods from functional principal component analysis and backfitting techniques for additive models. The model is found to have an approximate 10% better performance than the typical naïve trader models. The model can be a backbone in risk management serving for value at risk computations and scenario analysis.en
dc.language.isoengen
dc.publisher|aHumboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes |cBerlinen
dc.relation.ispartofseries|aSFB 373 Discussion Paper |x2003,54en
dc.subject.jelC14en
dc.subject.jelG12en
dc.subject.ddc330en
dc.subject.keywordImplied Volatility Surfaceen
dc.subject.keywordSmileen
dc.subject.keywordGeneralized Additive Modelsen
dc.subject.keywordBackfittingen
dc.subject.keywordFunctional Principal Component Analysisen
dc.titleImplied volatility string dynamics-
dc.typeWorking Paperen
dc.identifier.ppn73007675Xen
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:sfb373:200354en

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