Large Deviation for Reflected Backward Stochastic Differential Equations

Reflected forward-backward stochastic differential equations driven by G-Brownian motion with continuous monotone coefficients

In this paper, we prove that there exists at least one solution for the reflected forward-backward stochastic differential equation driven by G-Brownian motion satisfying the obstacle constraint with monotone coefficients.

Reflected backward doubly stochastic differential equations with discontinuous generator

In this note, we study one-dimensional reflected backward doubly stochastic differential equations (RBDSDEs) with one continuous barrier and discontinuous generator (left-or right-continuous). By a comparison theorem establish here for RBDSDEs, we provide a minimal or a maximal solution to RBDSDEs

Obstacle problem for SPDE with nonlinear Neumann boundary condition via reflected generalized backward doubly SDEs

This paper is intended to give a representation for stochastic viscosity solution of semi-linear reflected stochastic partial differential equations with nonlinear Neumann boundary condition. We use its connection with reflected generalized backward doubly stochastic differential equations.

Reflected backward SDEs with two barriers under monotonicity and general increasing conditions

In this paper, we prove the existence and uniqueness result of the reflected BSDE with two continuous barriers under monotonicity and general increasing condition on $y$, with Lipschitz condition on $z$.

Reflected generalized backward doubly SDEs driven by Lévy processes and Applications

In this paper, a class of reflected generalized backward doubly stochastic differential equations (reflected GBDSDEs in short) driven by Teugels martingales associated with Lévy process and the integral with respect to an adapted continuous increasing process is investigated. We obtain the existence and uniqueness of solutions to these equations. A probabilistic interpretation for solutions to a class of reflected stochastic partial differential integral equations (PDIEs in short) with a nonlinear Neumann boundary condition is given.

Reflected backward doubly stochastic differential equations with time delayed generators

We consider a class of reflected backward doubly stochastic differential equations with time delayed generator (in short RBDSDE with time delayed generator), in this case generator at time $t$ can depend on the values of a solution in the past. Under a Lipschitz condition, we ensure the existence and uniqueness of the solution.

Reflected solutions of Anticipated Backward Doubly SDEs driven by Teugels Martingales

We deal with reflected solutions of anticipated backward doubly stochastic differential equations (RABDSDEs) driven by Teugels martingales associated with Lévy process under a Lipschitz generator where the coefficients of these BDSDEs depend on the future and present value of the solution $\left( Y,Z\right) $. Also we study the existence of a solution for anticipated BDSDEs.

Filtration-Consistent Dynamic Operator with a Floor and Associated Reflected Backward Stochastic Differential Equations

This paper introduces the notion of a filtration-consistent dynamic operator with a floor, by suitably formulating four axioms. It is shown that under some suitable conditions, a filtration-consistent dynamic operator with a continuous upper-bounded floor is necessarily represented by the solution of a backward stochastic differential equation reflected upwards on the floor.

Some Properties of Reflected Backward Stochastic Differential Equations for a Finite State Markov Chain Model

In this paper, we provide an estimate for the solutions of reflected backward stochastic differential equations (RBSDEs) driven by a Markov chain, derive a continuous dependence property for their solutions with respect to the parameters of the equations, and show similar properties for solutions of backward stochastic differential equations (BSDEs). We finally establish a comparison result for the solutions of RBSDEs driven by a Markov chain.

Switching Game of Backward Stochastic Differential Equations and Associated System of Obliquely Reflected Backward Stochastic Differential Equations

This paper is concerned with the switching game of a one-dimensional backward stochastic differential equation (BSDE). The associated Bellman-Isaacs equation is a system of matrix-valued BSDEs living in a special unbounded convex domain with reflection on the boundary along an oblique direction. In this paper, we show the existence of an adapted solution to this system of BSDEs with oblique reflection by the penalization method, the monotone convergence, and the a priori estimates.

Reflected backward stochastic differential equations with two optional barriers

We consider reflected backward stochastic differential equations with two general optional barriers. The solutions to these equations have the so-called regulated trajectories, i.e trajectories with left and right finite limits. We prove the existence and uniqueness of $\mathbb L^p$ solutions, $p\geq 1$, and show that the solutions may be approximated by a modified penalization method.

Optimal stopping of marked point processes and reflected backward stochastic differential equations

We define a class of reflected backward stochastic differential equation (RBSDE) driven by a marked point process (MPP) and a Brownian motion, where the solution is constrained to stay above a given càdlàg process. The MPP is only required to be non-explosive and to have totally inaccessible jumps. Under suitable assumptions on the coefficients we obtain existence and uniqueness of the solution, using the Snell envelope theory. We use the equation to represent the value function of an optimal stopping problem, and we characterize the optimal strategy. Keywords: reflected backward stochastic di…

Reflected Backward Stochastic Differential Equations Driven by Lévy Process

In this paper, we deal with a class of reflected backward stochastic differential equations associated to the subdifferential operator of a lower semi-continuous convex function driven by Teugels martingales associated with Lévy process. We obtain the existence and uniqueness of solutions to these equations by means of the penalization method. As its application, we give a probabilistic interpretation for the solutions of a class of partial differential-integral inclusions.

Reflected Backward Stochastic Differential Equation with Rank-based Data

In this paper, we study reflected backward stochastic differential equation (reflected BSDE in abbreviation) with rank-based data in a Markovian framework; that is, the solution to the reflected BSDE is above a prescribed boundary process in a minimal fashion and the generator and terminal value of the reflected BSDE depend on the solution of another stochastic differential equation (SDE in abbreviation) with rank-based drift and diffusion coefficients. We derive regularity properties of the solution to such reflected BSDE, and show that the solution at the initial starting time $t$ and positi…

Reflected Discontinuous Backward Doubly Stochastic Differential Equation With Poisson Jumps

In this paper{\}we prove the existence of a solution for reflected backward doubly stochastic differential equations with poisson jumps (RBDSDEPs) with one continuous barrier where the generator is continuous and also we study the RBDSDEPs with a linear growth condition and left continuity in $y$ on the generator. By a comparison theorem established here for this type of equation we provide a minimal or a maximal solution to RBDSDEPs.

Reflected Generalized Backward Doubly SDEs driven by Lévy processes and Applications

In this paper, we study reflected generalized backward doubly stochastic differential equations driven by Teugels martingales associated with Lévy process (RGBDSDELs, in short) with one continuous barrier. Under uniformly Lipschitz coefficients, we prove existence and uniqueness result by means of the penalization method and the fixed point theorem. As an application, this study allows us to give a probabilistic representation for the solutions to a class of reflected stochastic partial differential integral equations (SPDIEs, in short) with a nonlinear Neumann boundary condition.

Reflected Backward Stochastic Volterra Integral Equations and related time-inconsistent optimal stopping problems

We study solutions of a class of one-dimensional continuous reflected backward stochastic Volterra integral equations driven by Brownian motion, where the reflection keeps the solution above a given stochastic process (lower obstacle). We prove existence and uniqueness by a fixed point argument and we derive a comparison result. Moreover, we show how the solution of our problem is related to a time-inconsistent optimal stopping problem and derive an optimal strategy.

Zero-sum Switching Game, Systems of Reflected Backward SDEs and Parabolic PDEs with bilateral interconnected obstacles

In this paper we study a zero-sum switching game and its verification theorems expressed in terms of either a system of Reflected Backward Stochastic Differential Equations (RBSDEs in short) with bilateral interconnected obstacles or a system of parabolic partial differential equations (PDEs in short) with bilateral interconnected obstacles as well. We show that each one of the systems has a unique solution. Then we show that the game has a value.

由G-Brownian运动驱动的双重反射倒向随机微分方程与带有双重障碍的完全非线性偏微分方程

Doubly Reflected Backward SDEs Driven by G-Brownian Motions and Fully Nonlinear PDEs with Double Obstacles

本文提出通过单调递减的惩罚反射G-BSDE逼近解的新方法，在已知最弱条件下证明了双重反射G-BSDE解的适定性，并首次揭示其与带双重障碍的完全非线性偏微分方程的关系。

Reflected backward stochastic differential equations with jumps in time-dependent random convex domains

In this paper, we study a class of multi-dimensional reflected backward stochastic differential equations when the noise is driven by a Brownian motion and an independent Poisson point process, and when the solution is forced to stay in a time-dependent adapted and continuous convex domain ${\cal{D}}=\{D_t, t\in[0,T]\}$. We prove the existence an uniqueness of the solution, and we also show that the solution of such equations may be approximated by backward stochastic differential equations with jumps reflected in appropriately defined discretizations of $\cal{D}$, via a penalization method.

Reflected Backward Stochastic Difference Equations and Optimal Stopping Problems under g-expectation

In this paper, we study reflected backward stochastic difference equations (RBSDEs for short) with finitely many states in discrete time. The general existence and uniqueness result, as well as comparison theorems for the solutions, are established under mild assumptions. The connections between RBSDEs and optimal stopping problems are also given. Then we apply the obtained results to explore optimal stopping problems under $g$-expectation. Finally, we study the pricing of American contingent claims in our context.

Mean-Field Doubly Reflected Backward Stochastic Differential Equations

We study mean-field doubly reflected BSDEs. First, using the fixed point method, we show existence and uniqueness of the solution when the data which define the BSDE are $p$-integrable with $p=1$ or $p>1$. The two cases are treated separately. Next by penalization we show also the existence of the solution. The two methods do not cover the same set of assumptions.

Reflected backward stochastic differentialequation with jumps and viscosity solution of second order integro-differential equation without monotonicity condition: case with the measure of Levy infinite

We consider the problem of viscosity solution of integro-partial differential equation(IPDE in short) with one obstacle via the solution of reflected backward stochastic differential equations(RBSDE in short) with jumps. We show existence and uniqueness of a continuous viscosity solution of equation with non local terms, in case the generator is not monotonous and Levy's measure is infinite.

布朗滤波初始放大下的倒向随机微分方程与反射倒向随机微分方程

Backward and reflected backward stochastic differential equations under initial enlargement of Brownian filtrations

该研究探讨布朗滤波初始放大对BSDEs和RBSDEs的影响，建立相关表示性质与恒等式，通过反例说明奇异方程解的唯一性问题，发展正则BSDE的条件参数化并讨论扩展方向。

Reflected Backward Stochastic Differential Equations for a Finite State Markov Chain Model and Applications to American Options

In this paper, we introduce a new kind of reflected backward stochastic differential equations (RBSDEs) driven by a martingale, in a Markov chain model, but not driven by Brownian motion, and give existence and uniqueness results for the new equations. Then we discuss American options in a finite state Markov chain model, in the presence of a stochastic discount function (SDF) and using the theory of the new RBSDEs. We show that there exists a constrained super-hedging strategy for an American option, which is unique in our framework as the solution to an RBSDE.

由$G$-布朗运动驱动的具有二次生成函数的双反射反向随机微分方程

Doubly Reflected Backward SDEs Driven by $G$-Brownian Motion with Quadratic Generator

本文研究由$G$-布朗运动驱动的双反射反向随机微分方程在二次生成函数下的性质，证明了解的存在性和唯一性，并通过罚函数反射建立其与具有双障碍的非线性偏微分方程的关系。

Reflected backward stochastic differential equations with optional barriers: monotone approximation

In this short note we consider RBSDE with Lipschitz drivers and barrier processes that are optional and right upper semicontinuous. We treat the case when the barrier can be represented as a decreasing limit of cadlag barriers. We combine well known existence results for cadlag barriers with comparison arguments for the control process to construct solutions. Finally, we highlight the connection of such RBSDEs with usual cadlag BSDEs.

Second order reflected backward stochastic differential equations

In this article, we build upon the work of Soner, Touzi and Zhang [Probab. Theory Related Fields 153 (2012) 149-190] to define a notion of a second order backward stochastic differential equation reflected on a lower càdlàg obstacle. We prove existence and uniqueness of the solution under a Lipschitz-type assumption on the generator, and we investigate some links between our reflected 2BSDEs and nonclassical optimal stopping problems. Finally, we show that reflected 2BSDEs provide a super-hedging price for American options in a market with volatility uncertainty.

Controlled Reflected SDEs and Neumann Problem for Backward SPDEs

We solve the optimal control problem of a one-dimensional reflected stochastic differential equation, whose coefficients can be path dependent. The value function of this problem is characterized by a backward stochastic partial differential equation (BSPDE) with Neumann boundary conditions. We prove the existence and uniqueness of sufficiently regular solution for this BSPDE, which is then used to construct the optimal feedback control. In fact we prove a more general result: The existence and uniqueness of strong solution for the Neumann problem for general nonlinear BSPDEs, which might be o…

Reflected anticipated backward stochastic differential equations with nonlinear resistance

In this paper, we consider reflected anticipated backward stochastic differential equations (RABSDEs, for short) with an additional resistance in the generators. Firstly, we study the existence and uniqueness results. In Luo (2020), the condition of a small time horizon is needed. Compared with the proving method in Luo (2020), we use a different proving method to avoid requiring the Lipschitz coefficients of generators $f(t,y,z,θ,\vartheta,m,\bar{m})$ for $y,z,θ,\vartheta$ to be small enough. We only require the Lipschitz coefficient for resistance in generator is small enough. Moreover, a pr…

Local Strict Comparison Theorem and Converse Comparison Theorems for Reflected Backward Stochastic Differential Equations

A local strict comparison theorem and some converse comparison theorems are proved for reflected backward stochastic differential equations under suitable conditions.

Mean-field reflected backward stochastic differential equations

In this paper, we study a class of reflected backward stochastic differential equations (BSDEs) of mean-field type, where the mean-field interaction in terms of the distribution of the $Y$-component of the solution enters in both the driver and the lower obstacle. We consider in details the case where the lower obstacle is a deterministic function of $(Y,\E[Y])$ and discuss the more general dependence on the distribution of $Y$. Under mild Lipschitz and integrability conditions on the coefficients, we obtain the well-posedness of such a class of equations. Under further monotonicity conditions…

具有两个障碍的条件反射倒向随机微分方程

Conditional Reflected Backward Stochastic Differential Equations with Two Barriers

本文研究了具有两个障碍的条件反射BSDEs，通过Skorokhod问题和Dynkin游戏建立了存在性和唯一性结果，并应用于部分信息下的可逆投资问题。

带双重约束的G-布朗运动驱动的均值反射倒向随机微分方程

Mean Reflected Backward Stochastic Differential Equations Driven by G-Brownian Motion with Double Constraints

本文研究带双重均值反射的G-布朗运动驱动的倒向随机微分方程，通过倒向Skorokhod问题与不动点理论证明解的存在唯一性，拓展非Lipschitz系数情形并得到相关性质。

带可选障碍和$L^p$数据的平均场双反射正倒向随机微分方程

Mean-Field Doubly Reflected Forward-Backward SDEs with Optional Barriers and $L^p$-Data

该研究针对带可选障碍和$L^p$数据的平均场双反射正倒向随机微分方程，在短时间区间和全局时间下分别证明了解的存在唯一性，其结果可应用于递归平均场Dynkin博弈与博弈期权估值。

平均场均值反射倒向随机微分方程的混沌传播

Propagation of Chaos for Mean-field Mean Reflected Backward Stochastic Differential Equations

研究平均场均值反射倒向随机微分方程的混沌传播，在生成元不依赖z时证明交互粒子系统解的存在唯一性，并给出收敛速率。

Representation theorems for generators of Reflected BSDEs with continuous and linear-growth generators

In this paper, we establish a local representation theorem for generators of reflected backward stochastic differential equations (RBSDE), whose generators are continuous with linear growth. It generalizes some known representation theorems for generators of backward stochastic differential equations (BSDE). As some applications, a general converse comparison theorem for RBSDE is obtained and some properties of RBSDE are discussed.

A new type of reflected backward doubly stochastic differential equations

In this paper, we introduce a new kind of "variant" reflected backward doubly stochastic differential equations (VRBDSDEs in short), where the drift is the nonlinear function of the barrier process. In the one stochastic case, this type of equations have been already studied by Ma and Wang. They called it as "variant" reflected BSDEs (VRBSDEs in short) based on the general version of the Skorohod problem recently studied by Bank and El Karoui. Among others, Ma and Wang showed that VRBSDEs is a novel tool for some problems in finance and optimal stopping problems where no existing methods can b…

Reflected Backward SDEs with General Jumps

In the first part of this paper we give a solution for the one-dimensional reflected backward stochastic differential equation (BSDE for short) when the noise is driven by a Brownian motion and an independent Poisson point process. The reflecting process is right continuous with left limits (rcll for short) whose jumps are arbitrary. We first prove existence and uniqueness of the solution for a specific coefficient in using a method based on a combination of penalization and the Snell envelope theory. To show the result in the general framework we use a fixed point argument in an appropriate s…

Stochastic Control Representations for Penalized Backward Stochastic Differential Equations

This paper shows that penalized backward stochastic differential equation (BSDE), which is often used to approximate and solve the corresponding reflected BSDE, admits both optimal stopping representation and optimal control representation. The new feature of the optimal stopping representation is that the player is allowed to stop at exogenous Poisson arrival times. The convergence rate of the penalized BSDE then follows from the optimal stopping representation. The paper then applies to two classes of equations, namely multidimensional reflected BSDE and reflected BSDE with a constraint on t…

Large deviation principle for reflected SPDE on infinite spatial domain

We study a large deviation principle for a reflected stochastic partial differential equation on infinite spatial domain. A new sufficient condition for the weak convergence criterion proposed by Matoussi, Sabbagh and Zhang ({\it Appl. Math. Optim.} 83: 849-879, 2021) plays an important role in the proof.

Large deviation principles and Malliavin derivative for mean reflected stochastic differential equations

In this paper, we consider a class of reflected stochastic differential equations for which the constraint is not on the paths of the solution but on its law. We establish a small noise large deviation principle, a large deviation for short time and the Malliavin derivative. To prove large deviation principles, a sufficient condition for the weak convergence method, which is suitable for Mckean-Vlasov stochastic differential equation, plays an important role.

Reflected BSDEs in time-dependent convex regions

We prove existence and uniqueness of solutions of reflected backward stochastic differential equations in time-dependent adapted and càdlàg convex regions $\mathcal{D}=\{D_t;t\in[0,T]\}$. We also show that the solution may be approximated by solutions of backward equations with reflection in appropriately defined discretizations of $\mathcal{D}$ and by a modified penalization method. The approximation results are new even in the one-dimensional case.

带反射的弱相互作用粒子系统的大偏差

Large deviations of reflected weakly interacting particle systems

本文采用弱收敛方法，证明了带反射的弱相互作用扩散系统经验测度的大偏差原理，并论证了受控反射系统经验测度序列收敛于带反射的 McKean--Vlasov 方程的弱解。

Maximum Principle for Quasi-linear Reflected Backward SPDEs

This paper establishes a maximum principle for quasi-linear reflected backward stochastic partial differential equations (RBSPDEs for short). We prove the existence and uniqueness of the weak solution to RBSPDEs allowing for non-zero Dirichlet boundary conditions and, using a stochastic version of De Giorgi's iteration, establish the maximum principle for RBSPDEs on a general domain. The maximum principle for RBSPDEs on a bounded domain and the maximum principle for backward stochastic partial differential equations (BSPDEs for short) on a general domain can be obtained as byproducts. Finally,…

Large Deviation Principle for Reflected Poisson driven SDEs in Epidemic Models

We establish a large deviation principle for a reflected Poisson driven SDE. Our motivation is to study in a forthcoming paper the problem of exit of such a process from the basin of attraction of a locally stable equilibrium associated with its law of large numbers. Two examples are described in which we verify the assumptions that we make to establish the large deviation principle.

基于秩数据的双障碍反射倒向随机微分方程

Two-barriers-reflected BSDE with Rank-based Data

本文研究基于秩数据的双障碍反射倒向随机微分方程，证明其解为对应抛物型偏微分方程障碍问题粘性解的概率表示，并将其应用于美式博弈期权定价。

Reflected backward stochastic differential equations and a class of non linear dynamic pricing rule

In that paper, we provide a new characterization of the solutions of specific reflected backward stochastic differential equations (or RBSDEs) whose driver $g$ is convex and has quadratic growth in its second variable: this is done by introducing the extended notion of $g$-Snell enveloppe. Then, in a second step, we relate this representation to a specific class of dynamic monetary concave functionals already introduced in a discrete time setting. This connection implies that the solution, characterized by means of non linear expectations, has again the time consistency property.

Backward Doubly SDEs and Semilinear Stochastic PDEs in a convex domain

This paper presents existence and uniqueness results for reflected backward doubly stochastic differential equations (in short RBDDSEs) in a convex domain D. Moreover, using a stochastic flow approach a probabilistic interpretation for a class of reflected SPDE's in a domain is given via such RBDSDEs. The solution is expressed as a pair (u,ν) where u is a predictable continuous process which takes values in a Sobolev space and m is a random regular measure. The bounded variation process K, component of the solution of the reflected BDSDE, controls the set when u reaches the boundary of D. This…

Reflected Mean-Field Backward Stochastic Differential Equations. Approximation and Associated Nonlinear PDEs

Mathematical mean-field approaches have been used in many fields, not only in Physics and Chemistry, but also recently in Finance, Economics, and Game Theory. In this paper we will study a new special mean-field problem in a purely probabilistic method, to characterize its limit which is the solution of mean-field backward stochastic differential equations (BSDEs) with reflections. On the other hand, we will prove that this type of reflected mean-field BSDEs can also be obtained as the limit equation of the mean-field BSDEs by penalization method. Finally, we give the probabilistic interpretat…

带粗糙驱动项的反射倒向随机微分方程

Reflected backward stochastic differential equations with rough drivers

本文研究带粗糙驱动项的反射倒向随机微分方程，证明其适定性、惩罚逼近性质，并将其应用于带障碍粗糙PDE的粘性解理论及粗糙路径框架下的美式期权定价与最优停止问题。

Particles Systems for Mean Reflected BSDEs

In this paper, we deal with Reflected Backward Stochastic Differential Equations for which the constraint is not on the paths of the solution but on its law as introduced by Briand, Elie and Hu in [3]. We extend the recent work [2] of Briand, Chaudru de Raynal, Guillin and Labart on the chaos propagation for mean reflected SDEs to the backward framework. When the driver does not depend on z, we are able to treat general reflexions for the particles system. We consider linear reflexion when the driver depends also on z. In both cases, we get the rate of convergence of the particles system towar…

Reflected BSDE with stochastic Lipschitz coefficient

In this paper, we deal with a class of one-dimensional reflected backward stochastic differential equations with stochastic Lipschitz coefficient. We derive the existence and uniqueness of the solutions for those equations via Snell envelope and the fixed point theorem.

Forward and Backward Stochastic Differential Equations with normal constraint in law

In this paper we investigate the well-posedness of backward or forward stochastic differential equations whose law is constrained to live in an a priori given (smooth enough) set and which is reflected along the corresponding ''normal'' vector. We also study the associated interacting particle system reflected in mean field and asymptotically described by such equations. The case of particles submitted to a common noise as well as the asymptotic system is studied in the forward case. Eventually, we connect the forward and backward stochastic differential equations with normal constraints in la…