A new Technique for Calibrating Stochastic Volatility Models: The Malliavin Gradient Method

Ewald, Christian-Oliver; Zhang, Aihua

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%T A new Technique for Calibrating Stochastic Volatility Models: The Malliavin Gradient Method
%A Ewald, Christian-Oliver
%A Zhang, Aihua
%J Quantitative Finance
%N 2
%P 147-158
%V 6
%D 2006
%K Monte Carlo Methods; Calibration of Stochastic Volatility; Derivative Pricing Models; Option Pricing via Simulation; Computational Finance; Stochastic Volatility; Financial Mathematics; Value at Risk
%= 2011-05-11T15:32:00Z
%~ http://www.peerproject.eu/
%> https://nbn-resolving.org/urn:nbn:de:0168-ssoar-220813
%X 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.
%C GBR
%G en
%9 journal article
%W GESIS - http://www.gesis.org
%~ SSOAR - http://www.ssoar.info