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This paper investigates a hybrid stochastic differential reinsurance and investment game between one reinsurer and two insurers, including a stochastic Stackelberg differential subgame and a non-zero-sum stochastic differential subgame. The…

Mathematical Finance · Quantitative Finance 2019-10-23 Yanfei Bai , Zhongbao Zhou , Helu Xiao , Rui Gao , Feimin Zhong

In modern portfolio theory, the balancing of expected returns on investments against uncertainties in those returns is aided by the use of utility functions. The Kelly criterion offers another approach, rooted in information theory, that…

Risk Management · Quantitative Finance 2015-03-13 Ole Peters

This paper considers the distributed strategy design for Nash equilibrium (NE) seeking in multi-cluster games under a partial-decision information scenario. In the considered game, there are multiple clusters and each cluster consists of a…

Optimization and Control · Mathematics 2022-06-08 Min Meng , Xiuxian Li

We address the Merton problem of maximizing the expected utility of terminal wealth using techniques from variational analysis. Under a general continuous semimartingale market model with stochastic parameters, we obtain a characterization…

Portfolio Management · Quantitative Finance 2020-03-20 Ali Al-Aradi , Sebastian Jaimungal

We consider a game-theoretic model of a market where investors compete for payoffs yielded by several assets. The main result consists in a proof of the existence and uniqueness of a strategy, called relative growth optimal, such that the…

Mathematical Finance · Quantitative Finance 2020-07-24 Yaroslav Drokin , Mikhail Zhitlukhin

This paper considers an $N$-player stochastic Nash game in which the $i$th player minimizes a composite objective $f_i(x) + r_i(x_i)$, where $f_i$ is expectation-valued and $r_i$ has an efficient prox-evaluation. In this context, we make…

Optimization and Control · Mathematics 2018-10-26 Jinlong Lei , Uday V. Shanbhag

We study the problem of maximizing Nash social welfare, which is the geometric mean of agents' utilities, in two well-known models. The first model involves one-sided preferences, where a set of indivisible items is allocated among a group…

Computer Science and Game Theory · Computer Science 2025-05-19 Salil Gokhale , Harshul Sagar , Rohit Vaish , Vignesh Viswanathan , Jatin Yadav

We consider the problem of distributed load balancing in heterogenous parallel server systems, where the service rate achieved by a user at a server depends on both the user and the server. Such heterogeneity typically arises in wireless…

Computer Science and Game Theory · Computer Science 2014-12-09 Se-Young Yun , Alexandre Proutiere

This paper presents a multi-agent reinforcement learning algorithm to represent strategic bidding behavior in freight transport markets. Using this algorithm, we investigate whether feasible market equilibriums arise without any central…

Machine Learning · Computer Science 2021-02-19 Wouter van Heeswijk

In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news-driven, analytic,…

General Finance · Quantitative Finance 2016-03-30 Dimitri Kroujiline , Maxim Gusev , Dmitry Ushanov , Sergey V. Sharov , Boris Govorkov

This work proposes a policy learning algorithm for seeking generalised feedback Nash equilibria (GFNE) in $N_P$-player noncooperative dynamic games. We consider linear-quadratic games with stochastic dynamics and design a best-response…

Optimization and Control · Mathematics 2025-06-13 Otacilio B. L. Neto , Michela Mulas , Francesco Corona

We study optimal portfolio choice models in markets with partial information about the stock's drift. We solve the single agent problem for general utilities using a new approach that yields regularity of the value function and closed form…

Optimization and Control · Mathematics 2026-05-27 Panagiotis Souganidis , Thaleia Zariphopoulou

Understanding the convergence landscape of multi-agent learning is a fundamental problem of great practical relevance in many applications of artificial intelligence and machine learning. While it is known that learning dynamics converge to…

Computer Science and Game Theory · Computer Science 2025-03-21 Martin Bichler , Davide Legacci , Panayotis Mertikopoulos , Matthias Oberlechner , Bary Pradelski

We apply the theory of McKean-Vlasov-type SDEs to study several problems related to market efficiency in the context of partial information and partially observable financial markets: (i) convergence of reduced-information market price…

Mathematical Finance · Quantitative Finance 2025-11-05 Karen Grigorian , Robert Jarrow

In the context of large population symmetric games, approximate Nash equilibria are introduced through equilibrium solutions of the corresponding mean field game in the sense that the individual gain from optimal unilateral deviation under…

Computer Science and Game Theory · Computer Science 2026-01-30 Mao Fabrice Djete , Nizar Touzi

A quantum financial approach to finite games of strategy is addressed, with an extension of Nash's theorem to the quantum financial setting, allowing for an entanglement of games of strategy with two-period financial allocation problems…

General Finance · Quantitative Finance 2012-02-10 Carlos Pedro Gonçalves

We study the computation of approximate pure Nash equilibria in Shapley value (SV) weighted congestion games, introduced in [19]. This class of games considers weighted congestion games in which Shapley values are used as an alternative (to…

Computer Science and Game Theory · Computer Science 2017-11-28 Matthias Feldotto , Martin Gairing , Grammateia Kotsialou , Alexander Skopalik

In this paper, we focus on the stochastic generalized Nash equilibrium problem (SGNEP) which is an important and widely-used model in many different fields. In this model, subject to certain global resource constraints, a set of…

Systems and Control · Electrical Eng. & Systems 2022-02-01 Yuanhanqing Huang , Jianghai Hu

The maximization of Nash welfare, which equals the geometric mean of agents' utilities, is widely studied because it balances efficiency and fairness in resource allocation problems. Banerjee, Gkatzelis, Gorokh, and Jin (2022) recently…

Data Structures and Algorithms · Computer Science 2024-11-11 Zhiyi Huang , Minming Li , Xinkai Shu , Tianze Wei

We consider multi-agent decision making where each agent optimizes its convex cost function subject to individual and coupling constraints. The constraint sets are compact convex subsets of a Euclidean space. To learn Nash equilibria, we…

Optimization and Control · Mathematics 2018-10-16 Tatiana Tatarenko , Maryam Kamgarpour