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To investigate a time-consistent optimal strategy for the continuous time mean-variance model, we develop a new method to establish the Bellman principle. Based on this new method, we obtain a time-consistent dynamic optimal strategy that…

Portfolio Management · Quantitative Finance 2020-07-24 Shuzhen Yang

This paper deals with N-person nonzero-sum discrete-time Markov games under a probability criterion, in which the transition probabilities and reward functions are allowed to vary with time. Differing from the existing works on the expected…

Probability · Mathematics 2025-05-16 Xin Guo , Xin Wen

We consider continuous-time stochastic optimal control problems featuring Conditional Value-at-Risk (CVaR) in the objective. The major difficulty in these problems arises from time-inconsistency, which prevents us from directly using…

Optimization and Control · Mathematics 2020-05-27 Christopher W. Miller , Insoon Yang

Modeling the purposeful behavior of imperfect agents from a small number of observations is a challenging task. When restricted to the single-agent decision-theoretic setting, inverse optimal control techniques assume that observed behavior…

Computer Science and Game Theory · Computer Science 2015-03-19 Kevin Waugh , Brian D. Ziebart , J. Andrew Bagnell

This paper concerns the numerical solution of a fully nonlinear parabolic double obstacle problem arising from a finite portfolio selection with proportional transaction costs. We consider the optimal allocation of wealth among multiple…

Portfolio Management · Quantitative Finance 2017-11-06 Arash Fahim , Wan-Yu Tsai

We study an optimal investment/consumption problem in a model capturing market and credit risk dependencies. Stochastic factors drive both the default intensity and the volatility of the stocks in the portfolio. We use the martingale…

Mathematical Finance · Quantitative Finance 2018-06-20 Lijun Bo , Agostino Capponi

Multi-agent learning is a challenging problem in machine learning that has applications in different domains such as distributed control, robotics, and economics. We develop a prescriptive model of multi-agent behavior using Markov games.…

Artificial Intelligence · Computer Science 2020-05-27 Jalal Etesami , Christoph-Nikolas Straehle

We consider a zero-sum stochastic game for continuous-time Markov chain with countable state space and unbounded transition and pay-off rates. The additional feature of the game is that the controllers together with taking actions are also…

Optimization and Control · Mathematics 2020-09-01 Chandan Pal , Subhamay Saha

Preferences play a key role in determining what goals/constraints to satisfy when not all constraints can be satisfied simultaneously. In this work, we study preference-based planning in a stochastic system modeled as a Markov decision…

Formal Languages and Automata Theory · Computer Science 2022-03-28 Abhishek Ninad Kulkarni , Jie Fu

We study the interaction between strategy, heterogeneity and growth in a two-agent model of capital accumulation. Preferences are represented by recursive utility functions with decreasing marginal impatience. The stationary equilibria of…

Optimization and Control · Mathematics 2016-08-26 Luis Alcala , Fernando Tohme , Carlos Dabus

This paper studies a continuous-time market {under stochastic environment} where an agent, having specified an investment horizon and a target terminal mean return, seeks to minimize the variance of the return with multiple stocks and a…

Portfolio Management · Quantitative Finance 2013-02-28 Wan-Kai Pang , Yuan-Hua Ni , Xun Li , Ka-Fai Cedric Yiu

In this paper, we consider the problem of maximizing the expected discounted utility of dividend payments for an insurance company that controls risk exposure by purchasing proportional reinsurance. We assume the preference of the insurer…

Portfolio Management · Quantitative Finance 2017-05-08 Xiaoqing Liang , Zbigniew Palmowski

This paper considers an infinite-horizon Markov decision process (MDP) that allows for general non-exponential discount functions, in both discrete and continuous time. Due to the inherent time inconsistency, we look for a randomized…

Optimization and Control · Mathematics 2024-12-10 Erhan Bayraktar , Yu-Jui Huang , Zhenhua Wang , Zhou Zhou

In this paper, we continue our study on a general time-inconsistent stochastic linear--quadratic (LQ) control problem originally formulated in [6]. We derive a necessary and sufficient condition for equilibrium controls via a flow of…

Portfolio Management · Quantitative Finance 2015-05-27 Ying Hu , Hanqing Jin , Xun Yu Zhou

We consider a Mean Field Games model where the dynamics of the agents is subdiffusive. According to the optimal control interpretation of the problem, we get a system involving fractional time-derivatives for the Hamilton-Jacobi-Bellman and…

Analysis of PDEs · Mathematics 2018-01-23 Fabio Camilli , Raul De Maio

In game theory, mechanism design is concerned with the design of incentives so that a desired outcome of the game can be achieved. In this paper, we study the design of incentives so that a desirable equilibrium is obtained, for instance,…

Computer Science and Game Theory · Computer Science 2021-06-21 Julian Gutierrez , Muhammad Najib , Giuseppe Perelli , Michael Wooldridge

In this paper, we study a class of stochastic time-inconsistent linear-quadratic (LQ) control problems with control input constraints. These problems are investigated within the more general framework associated with random coefficients.…

Optimization and Control · Mathematics 2017-03-29 Ying Hu , Jianhui Huang , Xun Li

In academic literature portfolio risk management and hedging are often versed in the language of stochastic control and Hamilton--Jacobi--Bellman~(HJB) equations in continuous time. In practice the continuous-time framework of stochastic…

Portfolio Management · Quantitative Finance 2023-09-28 Paul Alexander Bilokon

In Demand Response programs, price incentives might not be sufficient to modify residential consumers load profile. Here, we consider that each consumer has a preferred profile and a discomfort cost when deviating from it. Consumers can…

Optimization and Control · Mathematics 2017-12-01 Paulin Jacquot , Olivier Beaude , Nadia Oudjane , Stephane Gaubert

Modeling the purposeful behavior of imperfect agents from a small number of observations is a challenging task. When restricted to the single-agent decision-theoretic setting, inverse optimal control techniques assume that observed behavior…

Computer Science and Game Theory · Computer Science 2013-08-19 Kevin Waugh , Brian D. Ziebart , J. Andrew Bagnell