A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics

A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics

Author: Matthias R. Fengler

Publisher:

Published: 2017

Total Pages: 43

ISBN-13:

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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.


Semiparametric Modeling of Implied Volatility

Semiparametric Modeling of Implied Volatility

Author: Matthias R. Fengler

Publisher: Springer Science & Business Media

Published: 2005-12-19

Total Pages: 232

ISBN-13: 3540305912

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This book offers recent advances in the theory of implied volatility and refined semiparametric estimation strategies and dimension reduction methods for functional surfaces. The first part is devoted to smile-consistent pricing approaches. The second part covers estimation techniques that are natural candidates to meet the challenges in implied volatility surfaces. Empirical investigations, simulations, and pictures illustrate the concepts.


VAR Modeling for Dynamic Semiparametric Factors of Volatility Strings

VAR Modeling for Dynamic Semiparametric Factors of Volatility Strings

Author: Ralf Brüggemann

Publisher:

Published: 2017

Total Pages: 29

ISBN-13:

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The implied volatility of a European option as a function of strike price and time to maturity forms a volatility surface. Traders price according to the dynamics of this high dimensional surface. Recent developments that employ semiparametric models approximate the implied volatility surface (IVS) in a finite dimensional function space, allowing for a low dimensional factor representation of these dynamics. This paper presents an investigation into the stochastic properties of the factor loading times series using the vector autoregressive (VAR) framework and analyzes associated movements of these factors with movements in some macroeconomic variables of the Euro-economy.


A Semiparametric Factor Model for Implied Volatility Surface Dynamics

A Semiparametric Factor Model for Implied Volatility Surface Dynamics

Author: Matthias R. Fengler

Publisher:

Published: 2010

Total Pages:

ISBN-13:

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We propose a semiparametric factor model, which approximates the implied volatility surface (IVS) in a finite dimensional function space. Unlike standard principal component approaches typically used to reduce complexity, our approach is tailored to the degenerated design of IVS data. In particular, we only fit in the local neighborhood of the design points by exploiting the expiry effect present in option data. Using DAX index option data, we estimate the nonparametric components and a low-dimensional time series of latent factors. The modeling approach is completed by studying vector autoregressive models fitted to the latent factors.


VAR Modeling for Dynamic Loadings Driving Volatility Strings

VAR Modeling for Dynamic Loadings Driving Volatility Strings

Author: Ralf Brüggemann

Publisher:

Published: 2016

Total Pages: 29

ISBN-13:

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The implied volatility of an option as a function of strike price and time to maturity forms a volatility surface. Traders price according to the dynamics of this high dimensional surface. Recent developments that employ semiparametric models approximate the implied volatility surface (IVS) in a finite dimensional function space, allowing for a low dimensional factor representation of these dynamics. This paper presents an investigation into the stochastic properties of the factor loading time series using the vector autoregressive (VAR) framework and analyzes the dynamic relationship of these factors with economic indicators.


Dynamic Factor Models for the Volatility Surface

Dynamic Factor Models for the Volatility Surface

Author: Michel van der Wel

Publisher:

Published: 2016

Total Pages: 51

ISBN-13:

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The implied volatility surface is the collection of volatilities implied by option contracts for different strike prices and time-to-maturity. We study factor models to capture the dynamics of this three-dimensional implied volatility surface. Three model types are considered to examine desirable features for representing the surface and its dynamics: a general dynamic factor model, restricted factor models designed to capture the key features of the surface along the moneyness and maturity dimensions, and in-between spline-based methods. Key findings are that: (i) the restricted and spline-based models are both rejected against the general dynamic factor model, (ii) the factors driving the surface are highly persistent, (iii) for the restricted models option Delta is preferred over the more often used strike relative to spot price as measure for moneyness.