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This work deals with backward stochastic differential equation (BSDE) with random marked jumps, and their applications to default risk. We show that these BSDEs are linked with Brownian BSDEs through the decomposition of processes with…

Optimization and Control · Mathematics 2012-06-05 Idris Kharroubi , Thomas Lim

In this paper we are concerned with backward stochastic differential equations with random default time and their applications to default risk. The equations are driven by Brownian motion as well as a mutually independent martingale…

Computational Finance · Quantitative Finance 2009-10-13 Shige Peng , Xiaoming Xu

This paper is dedicated to the analysis of backward stochastic differential equations (BSDEs) with jumps, subject to an additional global constraint involving all the components of the solution. We study the existence and uniqueness of a…

Probability · Mathematics 2011-03-10 Romuald Elie , Idris Kharroubi

This paper introduces a backward stochastic differential equation driven by both Brownian motion and a Markov chain (BSDEBM). Regime-switching is also incorporated through its driver. The existence and uniqueness of the solution of the…

Probability · Mathematics 2022-03-08 Engel John C. Dela Vega , Robert J. Elliott

Rough stochastic differential equations (rough SDEs), recently introduced by Friz, Hocquet and L\^e in arXiv:2106.10340, have emerged as a versatile tool to study "doubly" SDEs under partial conditioning (with motivation from pathwise…

Probability · Mathematics 2025-07-24 Fabio Bugini , Peter K. Friz , Wilhelm Stannat

Motivated by applications to fluid dynamics, we study rough differential equations (RDEs) and rough partial differential equations (RPDEs) with non-Lipschitz drifts. We prove well-posedness and existence of a flow for RDEs with Osgood…

Analysis of PDEs · Mathematics 2025-02-18 Lucio Galeati , James-Michael Leahy , Torstein Nilssen

We show the existence and uniqueness of strong solutions for stochastic differential equation driven by partial $\alpha$-stable noise and partial Brownian noise with singular coefficients. The proof is based on the regularity of degenerate…

Probability · Mathematics 2017-07-18 Yueling Li , Longjie Xie , Yingchao Xie

In this paper, we are interested in path-dependent stochastic differential equations (SDEs) which are controlled by Brownian motion and its delays. Within this non-Markovian context, we give a H \"ormander-type criterion for the regularity…

Probability · Mathematics 2020-09-17 Reda Chhaibi , Ibrahim Ekren

We consider a differential equation driven by a Brownian motion as well as a rough path. We prove a Girsanov-type result for this equation to construct a weak solution in the probabilistic sense.

Probability · Mathematics 2018-05-04 Torstein Nilssen

In the past decade, an intensive study of strong approximation of stochastic differential equations (SDEs) with a drift coefficient that has discontinuities in space has begun. In the majority of these results it is assumed that the drift…

Probability · Mathematics 2020-10-05 Thomas Müller-Gronbach , Larisa Yaroslavtseva

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…

Probability · Mathematics 2015-05-14 Zhe Yang , Dimbinirina Ramarimbahoaka , Robert J. Elliott

We construct solutions to Burgers type equations perturbed by a multiplicative space-time white noise in one space dimension. Due to the roughness of the driving noise, solutions are not regular enough to be amenable to classical methods.…

Probability · Mathematics 2016-06-02 Martin Hairer , Hendrik Weber

We develop the rough path counterpart of It\^o stochastic integration and - differential equations driven by general semimartingales. This significantly enlarges the classes of (It\^o / forward) stochastic differential equations treatable…

Probability · Mathematics 2017-09-18 Peter K. Friz , Huilin Zhang

In this paper, we study reflected differential equations driven by continuous paths with finite $p$-variation ($1\le p<2$) and $p$-rough paths ($2\le p<3$) on domains in Euclidean spaces whose boundaries may not be smooth. We define…

Probability · Mathematics 2015-04-24 Shigeki Aida

We study the long-time behaviour of solutions to a class of $d$-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H \in (0,1)$. The drift consists of a dissipative Lipschitz term and a…

Probability · Mathematics 2025-12-23 Konstantinos Dareiotis , El Mehdi Haress , Khoa Lê

We study the discrete-time approximation for solutions of quadratic forward back- ward stochastic differential equations (FBSDEs) driven by a Brownian motion and a jump process which could be dependent. Assuming that the generator has a…

Optimization and Control · Mathematics 2012-11-28 Idris Kharroubi , Thomas Lim

In this paper, we introduce a new method to study the doubly reflected backward stochastic differential equation driven by G-Brownian motion (G-BSDE). Our approach involves approximating the solution through a family of penalized reflected…

Probability · Mathematics 2024-03-28 Hanwu Li , Ning Ning

We study non-linear Backward Stochastic Differential Equations (BSDEs) driven by a Brownian motion and p default martingales. The driver of the BSDE with multiple default jumps can take a generalized form involving an optional finite…

Mathematical Finance · Quantitative Finance 2026-01-06 Miryana Grigorova , James Wheeldon

We consider a class of Backward Stochastic Differential Equations with superlinear driver process $f$ adapted to a filtration supporting at least a $d$ dimensional Brownian motion and a Poisson random measure on ${\mathbb R}^m- \{0\}.$ We…

Probability · Mathematics 2019-11-19 Mahdi Ahmadi , Alexandre Popier , Ali Devin Sezer

Applications in quantitative finance such as optimal trade execution, risk management of options, and optimal asset allocation involve the solution of high dimensional and nonlinear Partial Differential Equations (PDEs). The connection…

Machine Learning · Statistics 2019-10-28 Batuhan Güler , Alexis Laignelet , Panos Parpas