The latest NAG Student Prize Winner

6 July 2017

shines a light on the calibration of stochastic local volatility models

Snapshot of part of NAG Student Prize Winner's posterNAG met one of their latest Student Prize winners at the QuanTech London conference recently. Maartyn Wyns who studies at the University of Antwerp, won a free pass to QuanTech for his work on 'A Finite Volume - Alternating Direction Implicit Approach for the Calibration of Stochastic Local Volatility Models'. View his paper and poster.


Calibration of stochastic local volatility (SLV) models to their underlying local volatility model is often performed by numerically solving a two-dimensional non-linear forward Kolmogorov equation. We propose a novel finite volume (FV) discretization in the numerical solution of general 1D and 2D forward Kolmogorov equations. The FV method does not require a transformation of the PDE. This constitutes a main advantage in the calibration of SLV models as the pertinent PDE coefficients are often nonsmooth. Moreover, the FV discretization has the crucial property that the total numerical mass is conserved. Applying the FV discretization in the calibration of SLV models yields a non-linear system of ODEs. Numerical time stepping is performed by the Hundsdorfer-Verwer ADI scheme to increase the computational efficiency. The non-linearity in the system of ODEs is handled by introducing an inner iteration. Ample numerical experiments are presented that illustrate the effectiveness of the calibration procedure.

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