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We consider an open model possessing a Markovian quantum stochastic limit and derive the limit stochastic Schrodinger equations for the wave function conditioned on indirect observations using only the von Neumann projection postulate. We…

Quantum Physics · Physics 2007-05-23 John Gough , Andrei Sobolev

This paper focuses on stochastic partial differential equations (SPDEs) under two-time-scale formulation. Distinct from the work in the existing literature, the systems are driven by $\alpha$-stable processes with $\alpha \in(1,2)$. In…

Statistics Theory · Mathematics 2016-09-30 Jianhai Bao , George Yin , Chenggui Yuan

This paper considers a portfolio optimization problem in which asset prices are represented by SDEs driven by Brownian motion and a Poisson random measure, with drifts that are functions of an auxiliary diffusion factor process. The…

Portfolio Management · Quantitative Finance 2010-11-16 Mark Davis , Sebastien Lleo

IIn this paper, we study a partially observed progressive optimal control problem of forward-backward stochastic differential equations with random jumps, where the control domain is not necessarily convex, and the control variable enter…

Optimization and Control · Mathematics 2022-06-27 Yueyang Zheng , Jingtao Shi

The stochastic motion in a nonhomogeneous medium with traps is studied and diffusion properties of that system are discussed. The particle is subjected to a stochastic stimulation obeying a general L\'evy stable statistics and experiences…

Statistical Mechanics · Physics 2015-06-11 Tomasz Srokowski

We consider a non-Markovian optimal stopping problem on finite horizon. We prove that the value process can be represented by means of a backward stochastic differential equation (BSDE), defined on an enlarged probability space, containing…

Probability · Mathematics 2015-02-20 Marco Fuhrman , Huyên Pham , Federica Zeni

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…

Probability · Mathematics 2016-10-11 Matoussi Anis , Sabbagh Wissal , Tusheng Zhang

In this work, we extend deep learning-based numerical methods to fully coupled forward-backward stochastic differential equations (FBSDEs) within a non-Markovian framework. Error estimates and convergence are provided. In contrast to the…

Mathematical Finance · Quantitative Finance 2025-11-25 Hasib Uddin Molla , Matthew Backhouse , Ankit Banarjee , Jinniao Qiu

This paper deals with a nonlinear filtering problem in which a multi-dimensional signal process is additively affected by a process $\nu$ whose components have paths of bounded variation. The presence of the process $\nu$ prevents from…

Optimization and Control · Mathematics 2022-06-02 Alessandro Calvia , Giorgio Ferrari

In this paper, we consider a stochastic decision problem for a system governed by a stochastic differential equation, in which an optimal decision is made in such a way to minimize a vector-valued accumulated cost over a finite-time horizon…

Optimization and Control · Mathematics 2018-01-08 Getachew K. Befekadu

Finite difference schemes, using Backward Differentiation Formula (BDF), are studied for the approximation of one-dimensional diffusion equations with an obstacle term, of the form $$\min(v_t - a(t,x) v_{xx} + b(t,x) v_x + r(t,x) v, v-…

Numerical Analysis · Mathematics 2021-05-14 Olivier Bokanowski , Kristian Debrabant

We study linear stochastic partial differential equations of parabolic type with non-local in time or mixed in time boundary conditions. The standard Cauchy condition at the terminal time is replaced by a condition that mixes the random…

Probability · Mathematics 2013-08-01 Nikolai Dokuchaev

In this paper, we study the following nonlinear backward stochastic integral partial differential equation with jumps \begin{equation*} \left\{ \begin{split} -d V(t,x) =&\displaystyle\inf_{u\in U}\bigg\{H(t,x,u, DV(t,x),D \Phi(t,x), D^2…

Optimization and Control · Mathematics 2020-11-10 Qingxin Meng , Yuchao Dong , Yang Shen , Shanjian Tang

We consider a general one-dimensional overdamped diffusion model described by the It\^{o} stochastic differential equation (SDE) ${dX_t=\mu(X_t,t)dt+\sigma(X_t,t)dW_t}$, where $W_t$ is the standard Wiener process. We obtain a specific…

Statistical Mechanics · Physics 2025-07-09 Costantino Di Bello , Édgar Roldán , Ralf Metzler

Forward-backward stochastic differential equations (FBSDEs) have attracted significant attention since they were introduced almost 30 years ago, due to their wide range of applications, from solving non-linear PDEs to pricing American-type…

Probability · Mathematics 2022-09-21 Elena Issoglio , Shuai Jing

We establish the existence of weak martingale solutions to a class of second order parabolic stochastic partial differential equations. The equations are driven by multiplicative jump type noise, with a non-Lipschitz multiplicative…

Probability · Mathematics 2018-09-28 Zdzisław Brzeźniak , Erika Hausenblas , Paul Razafimandimby

In this paper we investigate classical solution of a semi-linear system of backward stochastic integral partial differential equations driven by a Brownian motion and a Poisson point process. By proving an It\^{o}-Wentzell formula for jump…

Probability · Mathematics 2010-07-20 Shaokuan Chen , Shanjian Tang

In this paper we consider stochastic optimization problems for an ambiguity averse decision maker who is uncertain about the parameters of the underlying process. In a first part we consider problems of optimal stopping under drift…

Computational Finance · Quantitative Finance 2015-03-19 Sören Christensen

Motivated by earlier work on the use of fully-coupled Forward-Backward Stochastic Differential Equations (henceforth FBSDEs) in the analysis of mathematical models for the CO2 emissions markets, the present study is concerned with the…

Probability · Mathematics 2012-10-23 Rene Carmona , Francois Delarue

This is an expository article on the score-based diffusion models, with a particular focus on the formulation via stochastic differential equations (SDE). After a gentle introduction, we discuss the two pillars in the diffusion modeling --…

Machine Learning · Computer Science 2025-07-08 Wenpin Tang , Hanyang Zhao
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