English
Related papers

Related papers: Robust Ergodic Control of Jump-Diffusion Systems u…

200 papers

We consider a stochastic control problem with the assumption that the system is controlled until the state process breaks the fixed barrier. Assuming some general conditions, it is proved that the resulting Hamilton Jacobi Bellman equations…

Optimization and Control · Mathematics 2025-03-24 Dariusz Zawisza

In this paper, we extend the jump-diffusion model proposed by Davis and Lleo to include jumps in asset prices as well as valuation factors. The criterion, following earlier work by Bielecki, Pliska, Nagai and others, is risk-sensitive…

Portfolio Management · Quantitative Finance 2010-03-15 Mark Davis , Sebastien Lleo

In this paper we study model reduction of linear and bilinear quadratic stochastic control problems with parameter uncertainties. Specifically, we consider slow-fast systems with unknown diffusion coefficient and study the convergence of…

Optimization and Control · Mathematics 2021-02-10 Hafida Bouanani , Carsten Hartmann , Omar Kebiri

We study an optimal control problem in which both the objective function and the dynamic constraint contain an uncertain parameter. Since the distribution of this uncertain parameter is not exactly known, the objective function is taken as…

Optimization and Control · Mathematics 2016-11-29 Jianxiong Ye , Lei Wang , Changzhi Wu , Jie Sun , Kok Lay Teo , Xiangyu Wang

We consider the infinite horizon risk-sensitive problem for nondegenerate diffusions with a compact action space, and controlled through the drift. We only impose a structural assumption on the running cost function, namely…

Optimization and Control · Mathematics 2019-03-20 Ari Arapostathis , Anup Biswas

In an equity market model with "Knightian" uncertainty regarding the relative risk and covariance structure of its assets, we characterize in several ways the highest return relative to the market that can be achieved using nonanticipative…

Probability · Mathematics 2012-02-15 Daniel Fernholz , Ioannis Karatzas

We study the problem of optimal portfolio selection under stochastic volatility within a continuous time reinforcement learning framework with portfolio constraints. Exploration is modeled through entropy-regularized relaxed controls, where…

Mathematical Finance · Quantitative Finance 2026-04-27 Thai Nguyen , Pertiny Nkuize

The ergodic control problem for a non-degenerate controlled diffusion controlled through its drift is considered under a uniform stability condition that ensures the well-posedness of the associated Hamilton-Jacobi-Bellman (HJB) equation. A…

Optimization and Control · Mathematics 2019-03-20 Ari Arapostathis , Vivek S. Borkar

In this work, we focus on an infinite horizon mean-field linear-quadratic stochastic control problem with jumps. Firstly, the infinite horizon linear mean-field stochastic differential equations and backward stochastic differential…

Optimization and Control · Mathematics 2023-11-14 Qingmeng Wei , Yaqi Xu , Zhiyong Yu

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

Contemporary electricity distribution systems are being challenged by the variability of renewable energy sources. Slow response times and long energy management periods cannot efficiently integrate intermittent renewable generation and…

Systems and Control · Computer Science 2016-02-02 Gang Wang , Vassilis Kekatos , Antonio J. Conejo , Georgios B. Giannakis

General theorems for existence and uniqueness of viscosity solutions for Hamilton-Jacobi-Bellman quasi-variational inequalities (HJBQVI) with integral term are established. Such nonlinear partial integro-differential equations (PIDE) arise…

Optimization and Control · Mathematics 2011-01-04 Roland C. Seydel

In this article we study ergodic problems in the whole space $\mathbb{R}^N$ for weakly coupled systems of viscous Hamilton-Jacobi equations with coercive right-hand sides. The Hamiltonians are assumed to have a fairly general structure and…

Analysis of PDEs · Mathematics 2022-01-20 Ari Arapostathis , Anup Biswas , Prasun Roychowdhury

This paper studies optimal control problems of unknown linear systems subject to stochastic disturbances of uncertain distribution. Uncertainty about the stochastic disturbances is usually described via ambiguity sets of probability…

Systems and Control · Electrical Eng. & Systems 2023-06-30 Guanru Pan , Timm Faulwasser

In this paper, we guarantee the existence and uniqueness (in the almost everywhere sense) of the solution to a Hamilton-Jacobi-Bellman (HJB) equation with gradient constraint and a partial integro-differential operator whose L\'evy measure…

Analysis of PDEs · Mathematics 2019-03-26 Mark Kelbert , Harold A. Moreno-Franco

We investigate a numerical behaviour of robust deterministic optimal control problem subject to a convection diffusion equation containing uncertain inputs. Stochastic Galerkin approach, turning the original optimization problem containing…

Numerical Analysis · Mathematics 2023-03-01 Pelin Çiloğlu , Hamdullah Yücel

A classical problem in ergodic continuous time control consists of studying the limit behavior of the optimal value of a discounted cost functional with infinite horizon as the discount factor $\lambda$ tends to zero. In the literature,…

Optimization and Control · Mathematics 2024-01-23 Piermarco Cannarsa , Stephane Gaubert , Cristian Mendico , Marc Quincampoix

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 class of exit time stochastic control problems for diffusion processes with discounted criterion, where the controller can utilize a given amount of resource, called "fuel". In contrast to the vast majority of existing…

Optimization and Control · Mathematics 2015-01-30 Dmitry B. Rokhlin , Georgii Mironenko

In this paper, we introduce a model-based deep-learning approach to solve finite-horizon continuous-time stochastic control problems with jumps. We iteratively train two neural networks: one to represent the optimal policy and the other to…

Machine Learning · Computer Science 2026-01-16 Patrick Cheridito , Jean-Loup Dupret , Donatien Hainaut