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A new technique for calibrating stochastic volatility models: the Malliavin gradient method 

Authors: Christian-Oliver Ewald a; Aihua Zhang b
Affiliations:   a School of Mathematics, University of Leeds, UK
b Fraunhofer Institute ITWM, University of Kaiserslautern, Kaiserslautern, 67663, Germany
DOI: 10.1080/14697680500531676
Publication Frequency: 10 issues per year
Published in: journal Quantitative Finance, Volume 6, Issue 2 April 2006 , pages 147 - 158
Formats available: HTML (English) : PDF (English)
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Abstract

We discuss the application of gradient methods to calibrate mean reverting stochastic volatility models. For this we use formulas based on Girsanov transformations as well as a modification of the Bismut-Elworthy formula to compute the derivatives of certain option prices with respect to the parameters of the model by applying Monte Carlo methods. The article presents an extension of the ideas to apply Malliavin calculus methods in the computation of Greek's.
Keywords: Malliavin calculus; Monte Carlo simulation; Stochastic volatility models; Calibration; Gradient methods; Value at risk
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