Displaying similar documents to “Probabilistic methods for semilinear partial differential equations. Applications to finance”

Numerical schemes for multivalued backward stochastic differential systems

Lucian Maticiuc, Eduard Rotenstein (2012)

Open Mathematics

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We define approximation schemes for generalized backward stochastic differential systems, considered in the Markovian framework. More precisely, we propose a mixed approximation scheme for the following backward stochastic variational inequality: d Y t + F ( t , X t , Y t , Z t ) d t ∈ ∂ φ ( Y t ) d t + Z t d W t , where ∂φ is the subdifferential operator of a convex lower semicontinuous function φ and (X t)t∈[0;T] is the unique solution of a forward stochastic differential equation. We use an Euler type scheme for the system of decoupled forward-backward...

Stochastic differential equations driven by processes generated by divergence form operators I: a Wong-Zakai theorem

Antoine Lejay (2006)

ESAIM: Probability and Statistics

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We show in this article how the theory of “rough paths” allows us to construct solutions of differential equations (SDEs) driven by processes generated by divergence-form operators. For that, we use approximations of the trajectories of the stochastic process by piecewise smooth paths. A result of type Wong-Zakai follows immediately.

Euler schemes and half-space approximation for the simulation of diffusion in a domain

Emmanuel Gobet (2001)

ESAIM: Probability and Statistics

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This paper is concerned with the problem of simulation of ( X t ) 0 ≤ t ≤ T , the solution of a stochastic differential equation constrained by some boundary conditions in a smooth domain D : namely, we consider the case where the boundary ∂ D is killing, or where it is instantaneously reflecting in an oblique direction. Given N discretization times equally spaced on the interval [ 0 , T ] , we propose new discretization schemes: they are fully implementable and provide a weak error of order N - 1 under some conditions....

Forward-backward stochastic differential equations and PDE with gradient dependent second order coefficients

Romain Abraham, Olivier Riviere (2006)

ESAIM: Probability and Statistics

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We consider a system of fully coupled forward-backward stochastic differential equations. First we generalize the results of Pardoux-Tang [7] concerning the regularity of the solutions with respect to initial conditions. Then, we prove that in some particular cases this system leads to a probabilistic representation of solutions of a second-order PDE whose second order coefficients depend on the gradient of the solution. We then give some examples in dimension 1 and dimension 2 for...