13-18 mai 2018 Saint Pierre d'Oléron (France)
Numerical analysis of a particle calibration procedure for local and stochastic volatility models
Benjamin Jourdain  1@  , Alexandre Zhou  2@  
1 : Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique  (CERMICS)  -  Site web
Université Paris Est (UPE), École des Ponts ParisTech (ENPC)
6 et 8 avenue Blaise Pascal Cité Descartes - Champs sur Marne 77455 Marne la Vallée Cedex 2 -  France
2 : Centre dÉnseignement et de Recherche en Mathématiques et Calcul Scientifique
École des Ponts ParisTech (ENPC)

 

The calibration of a local and stochastic volatility model to the market prices of vanilla options leads to a diffusion nonlinear in the sense of McKean, as the coefficients contain conditional expectations computed w.r.t. the coordinates of the solution. Guyon and Henry-Labordère introduced an efficient calibration procedure using kernel approximations of the conditional expectation and interacting particles systems. We show the weak convergence at order 1 for the explicit Euler scheme with constant time step discretizing the diffusion nonlinear in the sense of McKean, using the technique developed by Talay and Tubaro. We then perform a numerical analysis of the calibration procedure from Guyon and Henry Labordère and illustrate the efficiency of the method. 

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