A Dynamic Semiparametric Factor Model For Implied Volatility String Dynamics

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A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics

A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics
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Total Pages : 43
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ISBN-10 : OCLC:1305401624
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Book Synopsis A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics by : Matthias R. Fengler

Download or read book A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics written by Matthias R. Fengler and published by . This book was released on 2017 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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