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• W1488572891 abstract "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." @default.
• W1488572891 created "2016-06-24" @default.
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• W1488572891 date "2005-03-06" @default.
• W1488572891 modified "2023-09-27" @default.
• W1488572891 title "A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics" @default.
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• W1488572891 doi "https://doi.org/10.18452/3886" @default.
• W1488572891 hasPublicationYear "2005" @default.
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