A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics
Author | : Matthias R. Fengler |
Publisher | : |
Total Pages | : 43 |
Release | : 2017 |
ISBN-10 | : OCLC:1305401624 |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
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.