Wiener and compensated Poisson processes, as normal martingales, are associated to classical sequences of polynomials, namely Hermite polynomials for the first one and Charlier polynomials for the second. The problem studied in this paper is to find if there exist other normal martingales which are associated to classical sequences of polynomials. Privault, Solé and Vives [5] solved this problem via the quantum Kabanov formula under some assumptions on the normal martingales considered. We solve...

The parabolic equations driven by linearly multiplicative Gaussian noise are stabilizable in probability by linear feedback controllers with support in a suitably chosen open subset of the domain. This procedure extends to Navier − Stokes equations with multiplicative noise. The exact controllability is also discussed.

Set-valued semimartingales are introduced as an extension of the notion of single-valued semimartingales. For such multivalued processes their semimartingale selection properties are investigated.

Dans cet article, nous étudions les résultats de grandes déviations associés au couple $(X^{\epsilon },{\nu }^{\epsilon })$, solution de l’E.D.S. interprétée au sens d’Itô :$$d{X}_t^{\epsilon }=\sqrt{\epsilon }{\sigma }_{{\nu }^{\epsilon }\left(t\right)}\left(X_t^{\epsilon }\right)d{W}_t+b_{{\nu }^{\epsilon }\left(t\right)}\left(X_t^{\epsilon }\right)dt;X_0^{\epsilon }=x\in {ℝ}^d$$avec des conditions assez générales sur les coefficients et dans les deux cas suivants :Premier cas : ${\nu }^{\epsilon }$ est indépendant du mouvement brownien $W$ et satisfait à un principe de grandes déviations ;Deuxième cas : ${\nu }^{\epsilon }$ est un processus markovien avec un nombre fini d’états $\{1,...,n\}$ vérifiant$$\mathbb{P}\{{\nu }^{\epsilon }(t+\Delta )=j/{\nu }^{\epsilon }\left(t\right)=i,X^{\epsilon }\left(t\right)=x\}=d_{ij}\left(x\right)\Delta +o\left(\Delta \right)$$uniformément dans ${ℝ}^d$ pourvu que $\Delta \downarrow 0,1\le i,j\le n,i\ne j$.Ces résultats sont des extensions de ceux de Bezuidenhout...

In this paper we study different algorithms for backward stochastic differential equations (BSDE in short) basing on random walk framework for 1-dimensional Brownian motion. Implicit and explicit schemes for both BSDE and reflected BSDE are introduced. Then we prove the convergence of different algorithms and present simulation results for different types of BSDEs.

In this paper we study different algorithms for backward stochastic differential equations (BSDE in short) basing on random walk framework for 1-dimensional Brownian motion. Implicit and explicit schemes for both BSDE and reflected BSDE are introduced. Then we prove the convergence of different algorithms and present simulation results for different types of BSDEs.

Parallel replica dynamics is a method for accelerating the computation of processes characterized by a sequence of infrequent events. In this work, the processes are governed by the overdamped Langevin equation. Such processes spend much of their time about the minima of the underlying potential, occasionally transitioning into different basins of attraction. The essential idea of parallel replica dynamics is that the exit distribution from a given well for a single process can be approximated by...

We introduce and analyze a numerical strategy to approximate effective coefficients in stochastic homogenization of discrete elliptic equations. In particular, we consider the simplest case possible: An elliptic equation on the d-dimensional lattice ${\mathbb{Z}}^d$ with independent and identically distributed conductivities on the associated edges. Recent results by Otto and the author quantify the error made by approximating the homogenized coefficient by the averaged energy of a regularized corrector (with...

We introduce and analyze a numerical strategy to approximate effective coefficients in stochastic homogenization of discrete elliptic equations. In particular, we consider the simplest case possible: An elliptic equation on the d-dimensional lattice ${\mathbb{Z}}^d$ with independent and identically distributed conductivities on the associated edges. Recent results by Otto and the author quantify the error made by approximating the homogenized coefficient by the averaged energy of a regularized corrector (with...

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: $$d{Y}_t+F(t,X_t,Y_t,Z_t)dt\in \partial \phi \left(Y_t\right)dt+Z_{t}d{W}_t,$$ 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 variational...

This paper deals with the construction of numerical solution of the Black-Scholes (B-S) type equation modeling option pricing with variable yield discrete dividend payment at time $t_d$. Firstly the shifted delta generalized function $\delta (t-t_d)$ appearing in the B-S equation is approximated by an appropriate sequence of nice ordinary functions. Then a semidiscretization technique applied on the underlying asset is used to construct a numerical solution. The limit of this numerical solution is independent of the...