arXiv subjects

Khaled Bahlali

Publications and source records attributed to Khaled Bahlali.

14 recordsLinked to original sources

arXiv2022

Approximation of a degenerate semilinear PDEs with a nonlinear Neumann boundary condition

We consider a system of semilinear partial differential equations (PDEs) with a nonlinearity depending on both the solution and its gradient. The Neumann boundary condition depends on the solution in a nonlinear manner. The uniform ellipticity is not required to the diffusion coefficient. We show that this problem admits a viscosity solution which can be approximated by a penalization. The Lipschitz condition is required to the coefficients of the diffusion part. The nonlinear part as well as the Neumann condition are Lipschitz. Moreover, the nonlinear part is assumed monotone in the solution variable. Note that the existence of a viscosity solution to this problem has been established in [13] then completed in [15]. In the present paper, We construct a sequence of penalized system of decoupled forward backward stochastic differential equations (FBSDEs) then we directly show its strong convergence. This allows us to deal with the case where the nonlinearity depends on both the solution and its gradient. Our work extends, in particular, the result of [4] and, in some sense, those of [1, 3]. In contrast to works [1, 3, 4], we do not pass by the weak compactness of the laws of the stochastic system associated to our problem.

math.PR↗

arXiv2021

BSDEs driven by $|z|^2/y$ and applications to PDEs and decision theory

Existence and uniqueness is established for a large class of backward stochastic differential equations which contain singular terms of the form $\pm|z|^2/y$. The results are applied to investigate singular partial differential equations (PDEs) and to decision theory problems that cannot be studied using classical regular BSDEs. The application to PDEs concerns the existence of viscosity solutions to PDEs containing a singular term of the form $\pm|\nabla v|^2/v$ with rather weak assumptions on the regularity of the coefficients. Such PDEs with singularity in the value process appear in several applications in physics and economics. Regarding the application to decision theory, on the one hand, we use singular BSDEs to solve portfolio optimization problems with logarithm and power utility and non-trivial terminal endowment. Moreover, we derive existence and uniqueness of the general version of the non-Markovian Kreps-Porteus stochastic differential utility defined by Duffie and Lions [17] and constructed, in the Markovian case using PDE arguments by Duffie and Lions [19].

math.PR↗

arXiv2020

Penalization for a PDE with a Nonlinear Neumann boundary condition and measurable coefficients *

We consider a system of semi-linear partial differential equations with measurable coefficients and a nonlinear Neumann boundary condition. We then construct a sequence of penalized partial differential equations which converges to a solution of our initial problem. The solution we construct is in the L p --viscosity sense, since the coefficients can be not continuous. The method we use is based on backward stochastic differential equations and their S-tightness. The present work is motivated by the fact that many partial differential equations arising in physics have discontinuous coefficients.

math.PR↗

arXiv2020

Quadratic transportation inequalities for SDEs with measurable drift

Let X be the solution of the multidimensional stochastic differential equationdX(t) = b(t, X(t)) dt + sigma(t, X(t)) dW(t)\, with X(0)=x where W is a standard Brownian motion. We show that when b is measurable and sigma is in an appropriate Sobolev space, the law of X satisfies a uniform quadratic transportation inequality.

math.PR↗

arXiv2019

Approximation and generic properties of McKean-Vlasov stochastic equations with continuous coefficients

We consider various approximation properties for systems driven by a Mc Kean-Vlasov stochastic differential equations (MVSDEs) with continuous coefficients, for which pathwise uniqueness holds. We prove that the solution of such equations is stable with respect to small perturbation of initial conditions, parameters and driving processes. Moreover, the unique strong solutions may be constructed by effective approximation procedures, without using the famous Yamada-Watanabe theorem. Finally we show that the set of bounded uniformly continuous coefficients for which the corresponding MVSDE have a unique strong solution is a set of second category in the sense of Baire.

math.PR↗

arXiv2019

Solving Unbounded Quadratic BSDEs by a Domination Method

We introduce a domination argument which asserts that: if we can dominate theparameters of a quadratic backward stochastic differential equation (QBSDE) with continuousgenerator from above and from below by those of two BSDEs having ordered solutions, thenalso the original QBSDE admits at least one solution. This result is presented in a generalframework: we do not impose any integrability condition on none of the terminal data of thethree involved BSDEs, we do not require any constraint on the growth nor continuity of thetwo dominating generators. As a consequence, we establish the existence of a maximal anda minimal solution to BSDEs whose coefficient H is continuous and satisfies |H(t, y, z)| $\le$$α$ t + $β$ t |y| + $θ$ t |z| + f (|y|)|z| 2 , where $α$ t , $β$ t , $θ$ t are positive processes and the function f ispositive, continuous and increasing (or even only positive and locally bounded) on R. This isdone with unbounded terminal value. We cover the classical QBSDEs where the function f isconstant ([10], [12], [23], [25]) and when f (y) = y p ([21]) and also the cases where the generator has super linear growth such as y|z|, e |y| |z| p , e e |z| 2 , (k $\ge$ 0, 0 $\le$ p < 2) and so on. Incontrast to the works [10, 12, 21, 23, 25], we get the existence of a a maximal and a minimalsolution and we cover the BSDEs with at most linear growth (take f = 0). In particular,we cover and extend the results of [22] and [24]. Furthermore, we establish the existence anduniqueness of solutions to BSDEs driven by f (y)|z| 2 when f is merely locally integrable on R.

math.PR↗

arXiv2019

Stability of Mc Kean-Vlasov stochastic differential equations and applications

We consider Mc Kean-Vlasov stochastic differential equations (MVSDEs), which are SDEs where the drift and diffusion coefficients depend not only on the state of the unknown process but also on its probability distribution. This type of SDEs was studied in statistical physics and represents the natural setting for stochastic mean-field games. We will first discuss questions of existence and uniqueness of solutions under an Osgood type condition improving the well known Lipschitz case. Then we derive various stability properties with respect to initial data, coefficients and driving processes, generalizing known results for classical SDEs. Finally, we establish a result on the approximation of the solution of a MVSDE associated to a relaxed control by the solutions of the same equation associated to strict controls. As a consequence, we show that the relaxed and strict control problems have the same value function. This last property improves known results proved for a special class of MVSDEs, where the dependence on the distribution was made via a linear functional. Key words: Mc Kean-Vlasov stochastic differential equation -- Stability -- Martingale measure - Wasserstein metric -- Existence -- Mean-field control -- Relaxed control.

math.PR↗

arXiv2017

Existence of an Optimal Control for a coupled FBSDE with a non degenerate diffusion coefficient

We a controlled system driven by a coupled forward-backward stochastic differential equation (FBSDE) with a non degenerate diffusion matrix. The cost functional is defined by the solution of the controlled backward stochastic differential equation (BSDE), at the initial time. Our goal is to find an optimal control which minimizes the cost functional. The method consists to construct a sequence of approximating controlled systems for which we show the existence of a sequence of feedback optimal controls. By passing to the limit, we establish the existence of a relaxed optimal control to the initial problem. The existence of a strict control follows from the Filippov convexity condition. Our results improve in some sense those of Buckdahn et al..

math.OC↗

arXiv2017

On the relaxed mean-field stochastic control problem

This paper is concerned with optimal control problems for systems governed by mean-field stochastic differential equation, in which the control enters both the drift and the diffusion coefficient. We prove that the relaxed state process, associated with measure valued controls, is governed by an orthogonal martingale measure rather that a Brownian motion. In particular, we show by a counter example that replacing the drift and diffusion coefficient by their relaxed counterparts does not define a true relaxed control problem. We establish the existence of an optimal relaxed control, which can be approximated by a sequence of strict controls. Moreover under some convexity conditions, we show that the optimal control is realized by a strict control.

math.OC↗

arXiv2017

Existence and optimality conditions for relaxed mean-field stochastic control problems

We consider optimal control problems for systems governed by mean-field stochastic differential equations, where the control enters both the drift and the diffusion coefficient. We study the relaxed model, in which admissible controls are measure-valued processes and the relaxed state process is driven by an orthogonal martingale measure, whose covariance measure is the relaxed control. This is a natural extension of the original strict control problem, for which we prove the existence of an optimal control. Then, we derive optimality necessary conditions for this problem, in terms of two adjoint processes extending the known results to the case of relaxed controls.

math.OC↗

arXiv2015

A class of stochastic differential equations with super-linear growth and non-Lipschitz coefficients

The purpose of this paper is to study some properties of solutions to one dimensional as well as multidimensional stochastic differential equations (SDEs in short) with super-linear growth conditions on the coefficients. Taking inspiration from \cite{BEHP, KBahlali, Bahlali}, we introduce a new {\it{local condition}} which ensures the pathwise uniqueness, as well as the non-contact property. We moreover show that the solution produces a stochastic flow of continuous maps and satisfies a large deviations principle of Freidlin-Wentzell type. Our conditions on the coefficients go beyond the existing ones in the literature. For instance, the coefficients are not assumed uniformly continuous and therefore can not satisfy the classical Osgood condition. The drift coefficient could not be locally monotone and the diffusion is neither locally Lipschitz nor uniformly elliptic. Our conditions on the coefficients are, in some sense, near the best possible. Our results are sharp and mainly based on Gronwall lemma and the localization of the time parameter in concatenated intervals

math.PR↗

arXiv2014

Quadratic BSDEs with $\mathbb{L}^2$--terminal data Existence results, Krylov's estimate and Itô--Krylov's formula

In a first step, we establish the existence (and sometimes the uniqueness) of solutions for a large class of quadratic backward stochastic differential equations (QBSDEs) with continuous generator and a merely square integrable terminal condition. Our approach is different from those existing in the literature. Although we are focused on QBSDEs, our existence result also covers the BSDEs with linear growth, keeping $ξ$ square integrable in both cases. As byproduct, the existence of viscosity solutions is established for a class of quadratic partial differential equations (QPDEs) with a square integrable terminal datum. In a second step, we consider QBSDEs with measurable generator for which we establish a Krylov's type a priori estimate for the solutions. We then deduce an Itô--Krylov's change of variable formula. This allows us to establish various existence and uniqueness results for classes of QBSDEs with square integrable terminal condition and sometimes a merely measurable generator. Our results show, in particular, that neither the existence of exponential moments of the terminal datum nor the continuity of the generator are necessary to the existence and/or uniqueness of solutions for quadratic BSDEs. Some comparison theorems are also established for solutions of a class of QBSDEs.

math.PR↗

arXiv2013

Penalization method for a nonlinear Neumann PDE via weak solutions of reflected SDEs

In this paper we prove an approximation result for the viscosity solution of a system of semi-linear partial differential equations with continuous coefficients and nonlinear Neumann boundary condition. The approximation we use is based on a penalization method and our approach is probabilistic. We prove the weak uniqueness of the solution for the reflected stochastic differential equation and we approximate it (in law) by a sequence of solutions of stochastic differential equations with penalized terms. Using then a suitable generalized backward stochastic differential equation and the uniqueness of the reflected stochastic differential equation, we prove the existence of a continuous function, given by a probabilistic representation, which is a viscosity solution of the considered partial differential equation. In addition, this solution is approximated by solutions of penalized partial differential equations.

math.PR↗

arXiv2011

Stochastic Optimal Control and BSDEs with Logarithmic Growth

In this paper, we study the existence of an optimal strategy for the stochastic control of diffusion in general case and a saddle-point for zero-sum stochastic differential games. The problem is formulated as an extended BSDE with logarithmic growth in the $z$-variable and terminal value in some $L^p$ space. We also show the existence and uniqueness of solution of this BSDE.

math.PR↗