Predictable solution for reflected BSDEs when the obstacle is not right-continuous

2020 ◽  
Vol 28 (4) ◽  
pp. 269-279
Author(s):  
Mohamed Marzougue ◽  
Mohamed El Otmani

AbstractIn the present paper, we consider reflected backward stochastic differential equations when the reflecting obstacle is not necessarily right-continuous in a general filtration that supports a one-dimensional Brownian motion and an independent Poisson random measure. We prove the existence and uniqueness of a predictable solution for such equations under the stochastic Lipschitz coefficient by using the predictable Mertens decomposition.

2007 ◽  
Vol 2007 ◽  
pp. 1-14 ◽  
Author(s):  
Jiajie Wang ◽  
Qikang Ran ◽  
Qihong Chen

We are concerned with the solutions of a special class of backward stochastic differential equations which are driven by a Brownian motion, where the uniform Lipschitz continuity is replaced by a stochastic one. We prove the existence and uniqueness of the solution in Lp with p>1.


2020 ◽  
Vol 23 (05) ◽  
pp. 2050034
Author(s):  
MOHAMED MARZOUGUE

In this paper, we prove the existence and uniqueness of the solution to backward stochastic differential equations with lower reflecting barrier in a Brownian setting under stochastic monotonicity and general increasing growth conditions. As an application, we study the fair valuation of American options.


2016 ◽  
Vol 12 (4) ◽  
pp. 6139-6147
Author(s):  
Xuecheng XU ◽  
Min Chen

This paper is devoted to solving multidimensional anticipated backward stochastic differential equations (anticipated BSDEs for short) with a kind of non-Lipschitz generators. We establish the existence and uniqueness result for L2 solutions of this kind of anticipated BSDEs, and establish the corresponding one-dimensional comparison theorems for the type of anticipated BSDEs. Our results improve some known results.


2021 ◽  
pp. 2250002
Author(s):  
Hongchao Qian ◽  
Jun Peng

In this paper, we establish the existence and uniqueness of solutions of reflected stochastic partial differential equations (SPDEs) driven both by Brownian motion and by Poisson random measure in a convex domain. Penalization method plays a crucial role.


2016 ◽  
Vol 6 (3) ◽  
pp. 253-277 ◽  
Author(s):  
Yu Fu ◽  
Jie Yang ◽  
Weidong Zhao

AbstractBy introducing a new Gaussian process and a new compensated Poisson random measure, we propose an explicit prediction-correction scheme for solving decoupled forward backward stochastic differential equations with jumps (FBSDEJs). For this scheme, we first theoretically obtain a general error estimate result, which implies that the scheme is stable. Then using this result, we rigorously prove that the accuracy of the explicit scheme can be of second order. Finally, we carry out some numerical experiments to verify our theoretical results.


2018 ◽  
Vol 26 (1) ◽  
pp. 11-22
Author(s):  
Navegué Tuo ◽  
Harouna Coulibaly ◽  
Auguste Aman

AbstractThis paper is devoted to establish an existence and uniqueness result of one-dimensional reflected backward stochastic differential equations with time-delayed generators (RBSDEs with time-delayed generators, in short). Our proof is based on approximation via a penalization method.


Sign in / Sign up

Export Citation Format

Share Document