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This paper considers robust Markov decision processes under parametric transition distributions. We assume that the true transition distribution is uniquely specified by some parametric distribution, and explicitly enforce that the…

Optimization and Control · Mathematics 2022-11-24 Ben Black , Trivikram Dokka , Christopher Kirkbride

In this paper, we consider the gradual-impulse control problem of continuous-time Markov decision processes, where the system performance is measured by the expectation of the exponential utility of the total cost. We prove, under very…

Optimization and Control · Mathematics 2023-11-16 Xin Guo , Aiko Kurushima , Alexey Piunovskiy , Yi Zhang

A method for calculating multi-portfolio time consistent multivariate risk measures in discrete time is presented. Market models for $d$ assets with transaction costs or illiquidity and possible trading constraints are considered on a…

Risk Management · Quantitative Finance 2017-01-27 Zachary Feinstein , Birgit Rudloff

This paper studies function approximation for finite horizon discrete time Markov decision processes under certain convexity assumptions. Uniform convergence of these approximations on compact sets is proved under several sampling schemes…

Optimization and Control · Mathematics 2018-02-21 Jeremy Yee

We study the optimal control of discrete time mean filed dynamical systems under partial observations. We express the global law of the filtered process as a controlled system with its own dynamics. Following a dynamic programming approach,…

Optimization and Control · Mathematics 2023-03-13 Jeremy Chichportich , Idris Kharroubi

In this paper, we consider risk-sensitive Markov Decision Processes (MDPs) with Borel state and action spaces and unbounded cost under both finite and infinite planning horizons. Our optimality criterion is based on the recursive…

Optimization and Control · Mathematics 2025-10-16 Nicole Bäuerle , Alexander Glauner

This paper investigates the optimal control problems for the finite-horizon continuous-time Markov decision processes with delay-dependent control policies. We develop compactification methods in decision processes, and show that the…

Probability · Mathematics 2023-07-06 Zhong-Wei Liao , Jinghai Shao

This is a follow up of our previous paper - Trybu{\l}a and Zawisza \cite{TryZaw}, where we considered a modification of a monotone mean-variance functional in continuous time in stochastic factor model. In this article we address the…

Portfolio Management · Quantitative Finance 2014-04-23 Jakub Trybuła , Dariusz Zawisza

This paper discusses a nonlinear integral equation arising from portfolio selection with a class of time-inconsistent preferences. We propose a unified framework requiring minimal assumptions, such as right-continuity of market coefficients…

Mathematical Finance · Quantitative Finance 2025-01-20 Zongxia Liang , Sheng Wang , Jianming Xia

We study time-consistency questions for processes of monetary risk measures that depend on bounded discrete-time processes describing the evolution of financial values. The time horizon can be finite or infinite. We call a process of…

Probability · Mathematics 2008-12-10 Patrick Cheridito , Freddy Delbaen , Michael Kupper

In this paper, we consider the portfolio optimization problem in a financial market where the underlying stochastic volatility model is driven by n-dimensional Brownian motions. At first, we derive a Hamilton-Jacobi-Bellman equation…

Mathematical Finance · Quantitative Finance 2024-12-20 Minglian Lin , Indranil SenGupta

We solve non-Markovian optimal switching problems in discrete time on an infinite horizon, when the decision maker is risk aware and the filtration is general, and establish existence and uniqueness of solutions for the associated reflected…

Optimization and Control · Mathematics 2022-08-09 Randall Martyr , John Moriarty , Magnus Perninge

This paper investigates a time-inconsistent portfolio selection problem in the incomplete mar ket model, integrating expected utility maximization with risk control. The objective functional balances the expected utility and variance on log…

Portfolio Management · Quantitative Finance 2025-12-02 Yue Cao , Zongxia Liang , Sheng Wang , Xiang Yu

We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the…

Portfolio Management · Quantitative Finance 2017-01-04 Istvan Varga-Haszonits , Fabio Caccioli , Imre Kondor

We study a counterfactual mean-variance optimization, where the mean and variance are defined as functionals of counterfactual distributions. The optimization problem defines the optimal resource allocation under various constraints in a…

Methodology · Statistics 2025-04-15 Kwangho Kim , Alan Mishler , José R. Zubizarreta

We propose a solution to a time-varying variant of Markov Decision Processes which can be used to address decision-theoretic planning problems for autonomous systems operating in unstructured outdoor environments. We explore the time…

Robotics · Computer Science 2019-05-28 Junhong Xu , Kai Yin , Lantao Liu

Dynamic optimization of mean and variance in Markov decision processes (MDPs) is a long-standing challenge caused by the failure of dynamic programming. In this paper, we propose a new approach to find the globally optimal policy for…

Optimization and Control · Mathematics 2023-02-28 Li Xia , Shuai Ma

Under mean-variance-utility framework, we propose a new portfolio selection model, which allows wealth and time both have influences on risk aversion in the process of investment. We solved the model under a game theoretic framework and…

Portfolio Management · Quantitative Finance 2020-08-11 Ben-Zhang Yang , Xin-Jiang He , Song-Ping Zhu

This paper considers consumption and portfolio optimization problems with recursive preferences in both infinite and finite time regions. Specially, the financial market consists of a risk-free asset and a risky asset that follows a general…

Optimization and Control · Mathematics 2024-12-30 Jian-hao Kang , Zhun Gou , Nan-jing Huang

Learning and optimal control under robust Markov decision processes (MDPs) have received increasing attention, yet most existing theory, algorithms, and applications focus on finite-horizon or discounted models. Long-run average-reward…

Optimization and Control · Mathematics 2025-12-12 Shengbo Wang , Nian Si