Solving some Stochastic Partial Differential Equations driven by Lévy Noise using two SDEs. * - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Stochastics: An International Journal of Probability and Stochastic Processes Année : 2022

Solving some Stochastic Partial Differential Equations driven by Lévy Noise using two SDEs. *

Résumé

The method of characteristics is a powerful tool to solve some nonlinear second order stochastic PDEs like those satisfied by a consistent dynamic utilities, see [EM13, MM20]. In this situation the solution V (t, z) is theoretically of the formX t V (0,ξ t (z)) whereX and Y are solutions of a system of two SDEs,ξ is the inverse flow ofȲ and V (0, .) is the initial condition. Unfortunately this representation is not explicit except in simple cases whereX andȲ are solutions of linear equations. The objective of this work is to take advantage of this representation to establish a numerical scheme approximating the solution V using Euler approximations X N and ξ N of X and ξ. This allows us to avoid a complicated discretizations in time and space of the SPDE for which it seems really difficult to obtain error estimates. We place ourselves in the framework of SDEs driven by Lévy noise and we establish at first a strong convergence result, in L p-norms, of the compound approximation X N t (Y N t (z)) to the compound variable X t (Y t (z)), in terms of the approximations of X and Y which are solutions of two SDEs with jumps. We then apply this result to Utility-SPDEs of HJB type after inverting monotonic stochastic flows.
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Dates et versions

hal-03211171 , version 1 (28-04-2021)

Identifiants

  • HAL Id : hal-03211171 , version 1

Citer

Mohamed Mrad. Solving some Stochastic Partial Differential Equations driven by Lévy Noise using two SDEs. *. Stochastics: An International Journal of Probability and Stochastic Processes, 2022. ⟨hal-03211171⟩
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