A dynamic semiparametric factor model for implied volatility string dynamics
A primary goal in modelling the implied volatility surface (IVS) for pricing and hedging 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 th...
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| Other Authors: | , , |
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| Format: | Book/Monograph Working Paper |
| Language: | English |
| Published: |
Berlin
SFB 649, Economic Risk
06 Mar. 2005
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| Series: | SFB 649 discussion paper
2005,020 |
| In: |
SFB 649 discussion paper (2005,020)
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| Online Access: | Verlag, Volltext: http://141.20.100.9/papers/pdf/SFB649DP2005-020.pdf Download aus dem Internet, Stand 15.08.2005, Volltext: http://hdl.handle.net/10419/25039 
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| Author Notes: | Matthias R. Fengler; Wolfgang Härdle; Enno Mammen |
| Summary: | A primary goal in modelling the implied volatility surface (IVS) for pricing and hedging 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 modelling bias. We propose a dynamic semiparametric factor model (DSFM), 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 a sticky moneyness model. Finally, based on the DSFM, we devise a generalized vega-hedging strategy for exotic options that are priced in the local volatility framework. The generalized vega-hedging extends the usual approaches employed in the local volatility framework. -- smile ; local volatility ; generalized additive model ; backfitting ; functional principal component analysis |
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| Physical Description: | Online Resource |
| Format: | Systemvoraussetzungen: Acrobat Reader. |