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This paper investigates a mean-field game (MFG) problem for mean-variance (MV) portfolio management, highlighting a new type of relative performance encoded by the peer-based risk aversion. Specifically, the risk aversion is formulated as a…

数理金融 · 定量金融 2026-05-26 Weilun Cheng , Zongxia Liang , Sheng Wang , Xiang Yu

We propose a simple model of inter-bank borrowing and lending where the evolution of the log-monetary reserves of $N$ banks is described by a system of diffusion processes coupled through their drifts in such a way that stability of the…

证券定价 · 定量金融 2013-08-12 Rene Carmona , Jean-Pierre Fouque , Li-Hsien Sun

We present a new combined \textit{mean field control game} (MFCG) problem which can be interpreted as a competitive game between collaborating groups and its solution as a Nash equilibrium between groups. Players coordinate their strategies…

最优化与控制 · 数学 2023-02-16 Andrea Angiuli , Nils Detering , Jean-Pierre Fouque , Mathieu Lauriere , Jimin Lin

Mean field games is a recent area of study introduced by Lions and Lasry in a series of seminal papers in 2006. Mean field games model situations of competition between large number of rational agents that play non-cooperative dynamic games…

最优化与控制 · 数学 2011-03-18 Diogo A. Gomes , Joana Mohr , Rafael R. Souza

Here, we examine a mean-field game (MFG) that models the economic growth of a population of non-cooperative rational agents. In this MFG, agents are described by two state variables - the capital and consumer goods they own. Each agent…

偏微分方程分析 · 数学 2019-07-26 Diogo Gomes , Laurent Lafleche , Levon Nurbekyan

This paper presents a general mean-field game (GMFG) framework for simultaneous learning and decision-making in stochastic games with a large population. It first establishes the existence of a unique Nash Equilibrium to this GMFG, and…

机器学习 · 计算机科学 2023-01-05 Xin Guo , Anran Hu , Renyuan Xu , Junzi Zhang

In many stochastic games stemming from financial models, the environment evolves with latent factors and there may be common noise across agents' states. Two classic examples are: (i) multi-agent trading on electronic exchanges, and (ii)…

最优化与控制 · 数学 2019-07-24 Dena Firoozi , Peter E. Caines , Sebastian Jaimungal

We consider existence and uniqueness of Nash equilibria in an $N$-player game of utility maximization under relative performance criteria of multiplicative form in complete semimartingale markets. For a large class of players' utility…

数理金融 · 定量金融 2023-03-15 Anastasiya Tanana

In this paper, we consider $n$ agents who invest in a general financial market that is free of arbitrage and complete. The aim of each investor is to maximize her expected utility while ensuring, with a specified probability, that her…

最优化与控制 · 数学 2025-07-01 Nicole Bäuerle , Tamara Göll

We develop a probabilistic approach to continuous-time finite state mean field games. Based on an alternative description of continuous-time Markov chain by means of semimartingale and the weak formulation of stochastic optimal control, our…

概率论 · 数学 2018-08-24 Rene Carmona , Peiqi Wang

In this paper, we consider discrete-time dynamic games of the mean-field type with a finite number $N$ of agents subject to an infinite-horizon discounted-cost optimality criterion. The state space of each agent is a locally compact Polish…

系统与控制 · 计算机科学 2017-01-17 Naci Saldi , Tamer Başar , Maxim Raginsky

In this paper we consider symmetric games where a large number of players can be in any one of d states. We derive a limiting mean field model and characterize its main properties. This mean field limit is a system of coupled ordinary…

最优化与控制 · 数学 2015-09-23 Diogo A. Gomes , Joana Mohr , Rafael R. Souza

We propose a new approach to mean field games with major and minor players. Our formulation involves a two player game where the optimization of the representative minor player is standard while the major player faces an optimization over…

概率论 · 数学 2014-09-26 Rene Carmona , Xiuneng Zhu

We study equilibrium feedback strategies for a family of dynamic mean-variance problems with competition among a large group of agents. We assume that the time horizon is random and each agent's risk aversion depends dynamically on the…

最优化与控制 · 数学 2026-05-05 Xiaoqing Liang , Jie Xiong , Ying Yang

We address in this paper Reinforcement Learning (RL) among agents that are grouped into teams such that there is cooperation within each team but general-sum (non-zero sum) competition across different teams. To develop an RL method that…

机器学习 · 计算机科学 2025-02-11 Muhammad Aneeq uz Zaman , Alec Koppel , Mathieu Laurière , Tamer Başar

We study an $N$-player and a mean field exponential utility game. Each player manages two stocks; one is driven by an individual shock and the other is driven by a common shock. Moreover, each player is concerned not only with her own…

最优化与控制 · 数学 2020-07-17 Guanxing Fu , Xizhi Su , Chao Zhou

We investigate a mean field game model for the production of exhaustible resources. In this model, firms produce comparable goods, strategically set their production rate in order to maximise profit, and leave the market as soon as they…

最优化与控制 · 数学 2019-02-27 P. Jameson Graber , Charafeddine Mouzouni

The recent mean field game (MFG) formalism facilitates otherwise intractable computation of approximate Nash equilibria in many-agent settings. In this paper, we consider discrete-time finite MFGs subject to finite-horizon objectives. We…

多智能体系统 · 计算机科学 2022-07-11 Kai Cui , Heinz Koeppl

We consider mean field games with discrete state spaces (called discrete mean field games in the following) and we analyze these games in continuous and discrete time, over finite as well as infinite time horizons. We prove the existence of…

最优化与控制 · 数学 2019-09-04 Josu Doncel , Nicolas Gast , Bruno Gaujal

We consider an energy system with $n$ consumers who are linked by a Demand Side Management (DSM) contract, i.e. they agreed to diminish, at random times, their aggregated power consumption by a predefined volume during a predefined…

最优化与控制 · 数学 2021-01-18 Clémence Alasseur , Luciano Campi , Roxana Dumitrescu , Jia Zeng