Implied volatility string dynamics
A 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 v...
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| Hauptverfasser: | , , |
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| Dokumenttyp: | Book/Monograph Arbeitspapier |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin
Humboldt-Universität
2003
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| Schriftenreihe: | Discussion papers of interdisciplinary research project 373
2003,54 |
| In: |
Discussion papers of interdisciplinary research project 373 (2003,54)
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| Schlagworte: | |
| Online-Zugang: | Resolving-System, Volltext: http://hdl.handle.net/10419/66280 Resolving-System, Volltext: http://nbn-resolving.de/urn:nbn:de:kobv:11-10050885 Verlag, Volltext: http://edoc.hu-berlin.de/series/sfb-373-papers/2003-54/PDF/54.pdf |
| Verfasserangaben: | Matthias R. Fengler; Wolfgang Härdle; Enno Mammen |
MARC
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| 520 | |a A 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. -- Implied Volatility Surface ; Smile ; Generalized Additive Models ; Backfitting ; Functional Principal Component Analysis | ||
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