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In this work, we consider the optimal portfolio selection problem under hard constraints on trading volume amounts when the dynamics of the risky asset returns are governed by a discrete-time approximation of the Markov-modulated geometric…

Portfolio Management · Quantitative Finance 2014-10-07 Vladimir Dombrovskii , Tatyana Obyedko

We are interested in risk constraints for infinite horizon discrete time Markov decision processes (MDPs). Starting with average reward MDPs, we show that increasing concave stochastic dominance constraints on the empirical distribution of…

Optimization and Control · Mathematics 2012-06-21 William B. Haskell , Rahul Jain

Overconservatism has long been recognized as a major issue with robust optimization, despite its key advantages of tractability, performance guarantee, and limited information. To address this issue, a new criterion is proposed that can…

Optimization and Control · Mathematics 2026-03-20 Yingjie Lan

We study nonzero-sum stochastic games for continuous time Markov decision processes on a denumerable state space with risk-sensitive ergodic cost criterion. Transition rates and cost rates are allowed to be unbounded. Under a Lyapunov type…

Optimization and Control · Mathematics 2022-07-18 Mrinal K Ghosh , Subrata Golui , Chandan Pal , Somnath Pradhan

This study introduces a dynamic investment framework to enhance portfolio management in volatile markets, offering clear advantages over traditional static strategies. Evaluates four conventional approaches : equal weighted, minimum…

Portfolio Management · Quantitative Finance 2025-04-07 Jinhui Li , Wenjia Xie , Luis Seco

The objective of this work is to study continuous-time Markov decision processes on a general Borel state space with both impulsive and continuous controls for the infinite-time horizon discounted cost. The continuous-time controlled…

Optimization and Control · Mathematics 2019-08-17 François Dufour , Alexei Piunovskiy

An unconventional approach for optimal stopping under model ambiguity is introduced. Besides ambiguity itself, we take into account how ambiguity-averse an agent is. This inclusion of ambiguity attitude, via an $\alpha$-maxmin nonlinear…

Mathematical Finance · Quantitative Finance 2021-07-15 Yu-Jui Huang , Xiang Yu

Most decision theories, including expected utility theory, rank dependent utility theory and cumulative prospect theory, assume that investors are only interested in the distribution of returns and not in the states of the economy in which…

Portfolio Management · Quantitative Finance 2014-07-03 Carole Bernard , Franck Moraux , Ludger Rueschendorf , Steven Vanduffel

We present a learning model predictive control (MPC) scheme for chance-constrained Markov jump systems with unknown switching probabilities. Using samples of the underlying Markov chain, ambiguity sets of transition probabilities are…

Optimization and Control · Mathematics 2023-01-06 Mathijs Schuurmans , Panagiotis Patrinos

We study a robust optimal stopping problem with respect to a set $\cP$ of mutually singular probabilities. This can be interpreted as a zero-sum controller-stopper game in which the stopper is trying to maximize its pay-off while an adverse…

Probability · Mathematics 2016-04-12 Erhan Bayraktar , Song Yao

We consider an investor faced with the utility maximization problem in which the risky asset price process has pure-jump dynamics affected by an unobservable continuous-time finite-state Markov chain, the intensity of which can also be…

Mathematical Finance · Quantitative Finance 2017-06-13 Sühan Altay , Katia Colaneri , Zehra Eksi

This paper considers a newly delayed reinsurance and investment optimization problem incorporating random risk aversion, in which an insurer pursues maximization of the expected certainty equivalent of her/his terminal wealth and the…

Optimization and Control · Mathematics 2026-01-23 Jian-hao Kang , Zhun Gou , Nan-jing Huang

Group Relative Policy Optimization (GRPO) has proven effective in RLVR by using outcome-based rewards. While fine-grained dense rewards can theoretically improve performance, we reveal that under practical sampling budgets, Monte Carlo…

Machine Learning · Computer Science 2026-04-13 Fengwei Teng , Jinyi Bai , Xinhao Yao , Demi Ruohan Wang , Jiahao Zhao , Zhijiang Guo

This study presents a rigorous mathematical approach to the optimization of round and betting policies in Blackjack, using Markov Decision Processes (MDP) and Expected Utility Theory. The analysis considers a direct confrontation between a…

Optimization and Control · Mathematics 2025-05-05 Lucas Bordeu , Javier Castro

We introduce a new non-zero-sum game of optimal stopping with asymmetric exercise opportunities. Given a stochastic process modelling the value of an asset, one player observes and can act on the process continuously, while the other player…

Probability · Mathematics 2024-05-16 José Luis Pérez , Neofytos Rodosthenous , Kazutoshi Yamazaki

Algorithmic trading in modern financial markets is widely acknowledged to exhibit strategic, game-theoretic behaviors whose complexity can be difficult to model. A recent series of papers (Chriss, 2024b,c,a, 2025) has made progress in the…

Computer Science and Game Theory · Computer Science 2025-06-10 Michael Kearns , Mirah Shi

For an exponential utility maximizing investment strategy in a Black-Scholes Setting, fixed upper and lower constraints are introduced on the terminal wealth. This is equivalent to combining the optimal strategy with options. The resulting…

Portfolio Management · Quantitative Finance 2017-12-05 Lena Schutte

This article examines arbitrage investment in a mispriced asset when the mispricing follows the Ornstein-Uhlenbeck process and a credit-constrained investor maximizes a generalization of the Kelly criterion. The optimal differentiable and…

Optimization and Control · Mathematics 2008-12-02 Vladislav Kargin

We consider a nonzero-sum N-player Markov game on an abstract measurable state space with compact metric action spaces. The payoff functions are bounded Carath\'eodory functions and the transitions of the system are assumed to have a…

Optimization and Control · Mathematics 2023-05-09 François Dufour , Tomás Prieto-Rumeau

We study a two-player discounted zero-sum stochastic game model for dynamic operational planning in military campaigns. At each stage, the players manage multiple commanders who order military actions on objectives that have an open line of…

Computer Science and Game Theory · Computer Science 2024-03-04 Joseph E. McCarthy , Mathieu Dahan , Chelsea C. White