Add to ORKGWe study the optimal discretization error of stochastic integrals, driven by a multidimensional continuous Brownian semimartingale. In this setting we establish a pathwise lower bound for the renormalized quadratic variation of the error and we provide a sequence of discretiza- tion stopping times, which is asymptotically optimal. The latter is defined as hitting times of random ellipsoids by the semimartingale at hand. In comparison with previous available results, we allow a quite large class of semimartingales (relaxing in particular the non degeneracy conditions usually requested) and we prove that the asymptotic lower bound is attainable
We study a semi-discretisation scheme for stochastic optimal control problems whose dynamics are giv...
Through a regularization procedure, a few schemes for approximation of the local time of a large cla...
International audienceIn this work, we study the optimal discretization error of stochastic integral...
We study the optimal discretization error of stochastic integrals, driven by a multidimensional cont...
This paper proves joint convergence of the approximation error for several stochastic integrals with...
We study the convergence in distribution of the renormalized error arising from the discretization o...
Abstract. Given a geometric Brownian motion S = (St)t∈[0,T] and a Borel function g: (0,∞) → IR such...
AbstractGiven a geometric Brownian motion S=(St)t∈[0,T] and a Borel measurable function g:(0,∞)→R su...
AbstractWe study pathwise approximation of scalar stochastic differential equations. The mean square...
This book offers a rigorous and self-contained presentation of stochastic integration and stochastic...
AbstractLetB=(Bt)t≥0be a Brownian motion started atx∈R. Given a stopping time τ forBand a real value...
In this note we prove that the local martingale part of a convex function f of a d-dimen...
In this note we prove that the local martingale part of a convex function f of a d-dimensional semim...
peer reviewedIn this article, an uniform discretization of stochastic integrals $\int_{0}^{1} f'_-(B...
AbstractLet (Ω,J,P;Jz) be a probability space with an increasing family of sub-σ-fields {Jz, z ∈ D},...
We study a semi-discretisation scheme for stochastic optimal control problems whose dynamics are giv...
Through a regularization procedure, a few schemes for approximation of the local time of a large cla...
International audienceIn this work, we study the optimal discretization error of stochastic integral...
We study the optimal discretization error of stochastic integrals, driven by a multidimensional cont...
This paper proves joint convergence of the approximation error for several stochastic integrals with...
We study the convergence in distribution of the renormalized error arising from the discretization o...
Abstract. Given a geometric Brownian motion S = (St)t∈[0,T] and a Borel function g: (0,∞) → IR such...
AbstractGiven a geometric Brownian motion S=(St)t∈[0,T] and a Borel measurable function g:(0,∞)→R su...
AbstractWe study pathwise approximation of scalar stochastic differential equations. The mean square...
This book offers a rigorous and self-contained presentation of stochastic integration and stochastic...
AbstractLetB=(Bt)t≥0be a Brownian motion started atx∈R. Given a stopping time τ forBand a real value...
In this note we prove that the local martingale part of a convex function f of a d-dimen...
In this note we prove that the local martingale part of a convex function f of a d-dimensional semim...
peer reviewedIn this article, an uniform discretization of stochastic integrals $\int_{0}^{1} f'_-(B...
AbstractLet (Ω,J,P;Jz) be a probability space with an increasing family of sub-σ-fields {Jz, z ∈ D},...
We study a semi-discretisation scheme for stochastic optimal control problems whose dynamics are giv...
Through a regularization procedure, a few schemes for approximation of the local time of a large cla...
International audienceIn this work, we study the optimal discretization error of stochastic integral...