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This paper is concerned with a class of stochastic differential equations with Markovian switching. The Malliavin calculus is used to study the smoothness of the density of the solution under a H\"{o}rmander type condition. Furthermore, we…

Probability · Mathematics 2017-10-20 Yaozhong Hu , David Nualart , Xiaobin Sun , Yingchao Xie

We consider a class of stochastic optimal control problems for discrete-time stochastic linear systems which seek for control policies that will steer the probability distribution of the terminal state of the system close to a desired…

Optimization and Control · Mathematics 2020-10-01 Isin M. Balci , Efstathios Bakolas

We present a backward diffusion flow (i.e. a backward-in-time stochastic differential equation) whose marginal distribution at any (earlier) time is equal to the smoothing distribution when the terminal state (at a latter time) is…

Probability · Mathematics 2021-10-04 Brian D. O. Anderson , Adrian N. Bishop , Pierre Del Moral , Camille Palmier

We prove the existence of a unique Malliavin differentiable strong solution to a stochastic differential equation on the plane with merely integrable coefficients driven by the fractional Brownian sheet with Hurst parameters less than 1/2.…

Probability · Mathematics 2025-12-16 Antoine-Marie Bogso , Olivier Menoukeu Pamen , Frank Proske

We consider a stochastic control problem, where the control domain is convex and the system is governed by a nonlinear backward stochastic differential equation. With a L1 terminal data, we derive necessary optimality conditions in the form…

Probability · Mathematics 2008-07-23 Seid Bahlali

Malliavin calculus is a powerful and general framework for the analysis of square-integrable random variables, but it often suffers from a lack of tractability and explicit representations. To address this limitation, we focus on a subclass…

Probability · Mathematics 2026-04-28 Eduardo Abi Jaber , Clément Rey , Dimitri Sotnikov

In this article, we consider a stochastic partial differential equation (SPDE) driven by a L\'evy white noise, with Lipschitz multiplicative term $\sigma$. We prove that under some conditions, this equation has a unique random field…

Probability · Mathematics 2016-05-10 Raluca M. Balan , Cheikh B. Ndongo

We study the optimal liquidation problems in target zone models using dynamic programming methods. Such control problems allow for stochastic differential equations with reflections and random coefficients. The value function is…

Optimization and Control · Mathematics 2019-12-17 Robert Elliott , Jinniao Qiu , Wenning Wei

The aim of the present paper is to study the regularity properties of the solution of a backward stochastic differential equation with a monotone generator in infinite dimension. We show some applications to the nonlinear Kolmogorov…

Probability · Mathematics 2008-04-10 Philippe Briand , Fulvia Confortola

In this paper we study properties of solutions to stochastic differential equations with Sobolev diffusion coefficients and singular drifts. The properties we study include stability with respect to the coefficients, weak differentiability…

Probability · Mathematics 2015-11-25 Xicheng Zhang

In this paper we discuss backward stochastic differential equations with Markov chain noise, having continuous drivers. We obtain the existence of a solution which is possibly not unique. Moreover, we show there is a minimal solution for…

Probability · Mathematics 2014-12-01 Dimbinirina Ramarimbahoaka , Zhe Yang , Robert J. Elliott

In this work, we analyze the properties of the solution to the covariance steering problem for discrete time Gaussian linear systems with a squared Wasserstein distance terminal cost. In our previous work, we have shown that by utilizing…

Optimization and Control · Mathematics 2021-03-26 Isin M. Balci , Abhishek Halder , Efstathios Bakolas

We study the causal distributionally robust optimization (DRO) in both discrete- and continuous- time settings. The framework captures model uncertainty, with potential models penalized in function of their adapted Wasserstein distance to a…

Probability · Mathematics 2025-05-29 Yifan Jiang , Jan Obloj

We study existence and uniqueness of solutions for second order ordinary stochastic differential equations with Dirichlet boundary conditions on a given interval. In the first part of the paper we provide sufficient conditions to ensure…

Classical Analysis and ODEs · Mathematics 2009-10-16 Anna Capietto , Enrico Priola

The discrete-time approximation for nonlinear filtering problems is related to both of strong and weak approximations of stochastic differential equations. In this paper, we propose a new method of proof for the convergence of approximate…

Probability · Mathematics 2014-05-26 Hideyuki Tanaka

We study backward stochastic differential equations (BSDEs) in infinite horizon and design efficient numerical schemes for solving them. We establish a probabilistic representation of the solution of the BSDE using Malliavin derivative and…

Probability · Mathematics 2026-04-28 Emmanuel Gobet , Adrien Richou , Charu Shardul

We study a multi-dimensional optimal execution problem in illiquid markets with both instantaneous and persistent price impact and stochastic resilience. In our model the value function can be described by a multi-dimensional backward…

Optimization and Control · Mathematics 2018-09-07 Ulrich Horst , Xiaonyu Xia

Suppose $B$ is a Brownian motion and $B^n$ is an approximating sequence of rescaled random walks on the same probability space converging to $B$ pointwise in probability. We provide necessary and sufficient conditions for weak and strong…

Probability · Mathematics 2016-03-01 Christian Bender , Peter Parczewski

In this paper we derive tractable formulae for price sensitivities of two-dimensional spread options using Malliavin calculus. In particular, we consider spread options with asset dynamics driven by geometric Brownian motion and stochastic…

Optimization and Control · Mathematics 2021-06-10 Farai Julius Mhlanga , Shadrack Makwena Kgomo

We provide an algebraic unification of the spectral gap proofs of the convergence of the renormalised model for regularity structures. We show that the key recentering map used in the literature for adjusting the recentering of the model is…

Probability · Mathematics 2026-03-04 Yvain Bruned , Aurélien Minguella
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