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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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1.0%2.0%3.0%4.0% · Jul 201819922001200920172026
48 results for N-player games

Study NN-player and mean-field games in Itô-diffusion markets with competitive or homophilous interactions.

problem Optimal portfolio choice in a common market with NN interacting players.
method Analyzes NN-player and mean-field games in incomplete and complete markets with CARA utilities and random risk tolerances.
result Derives explicit or closed-form solutions for equilibrium processes and game values.

Deep neural network solves large multi-agent games for Markovian Nash equilibrium.

problem Finding Markovian Nash equilibrium in large multi-agent stochastic differential games.
method Reformulate as decoupled decision problems, solve iteratively using deep BSDE method.
result Proposed algorithm accurately finds Nash equilibrium in large games.

We study the convergence of Nash equilibria in a game of optimal stopping. If the associated mean field game has a unique equilibrium, any sequence of nn-player equilibria converges to it as nn\to\infty. However, both the finite and infinite player versions of the game often admit multiple equilibria. We show that me…

2018-06-03abs ↗pdf ↗

New methods learn correlated equilibria in large games without structural assumptions.

problem Learning correlated equilibria in large, anonymous games with exponential player count.
method Developed Mean-Field correlated and coarse-correlated equilibria, and used classical algorithms to learn them efficiently.
result Efficiently learned correlated equilibria in all games without structural assumptions.

Study explores optimal strategies in games with multiple players and mean-field interactions.

problem Optimal strategies in games with multiple players and mean-field interactions.
method Exploration of three different notions of optimality, including mean-field control solution, mean-field coarse correlated equilibria, and mean-field Nash equilibria.
result Approximation of cooperative and competitive equilibria in large NN-player games by mean-field control and mean-field equilibria.

Expands MFGs to handle real-world asymmetric multi-agent games efficiently.

problem Applying mean-field games to real-world, heterogeneous multi-agent systems.
method Develops a method to symmetrize and extend finite-player games to infinite-player MFGs, proving approximation bounds and convergence guarantees.
result TD learning converges to approximate Nash equilibria in finite-sample settings, enabling symmetrized learning without explicit MFG models.

The paper analyzes competition among fund managers using excess logarithmic returns and constructs games to find optimal allocations.

problem Optimal allocation strategies among fund managers considering excess logarithmic returns.
method Constructs both nn-player and mean field games to address the competition problem.
result The MFE of the MFG represents the limit of nn-player game's equilibrium as nn approaches infinity.

Deep learning theory for Nash equilibrium in stochastic games.

problem Computing Nash equilibrium in non-zero-sum stochastic differential games.
method Fictitious play applied to deep neural networks for solving NN-player optimization problems.
result Deep learning algorithm converges to open-loop Nash equilibrium under appropriate assumptions.

The paper analyzes optimal investment strategies in a game with jump risk, deriving mean field equilibria.

problem Optimal investment strategies in a game with jump risk and peer competition.
method Formulated mean field game and n-player game models, characterized equilibrium states, and derived approximation errors.
result Explicit mean field equilibrium and approximate Nash equilibrium for large n-player games.

Study of LQ MFGs in infinite-dimensional Hilbert spaces.

problem Mean field games in infinite-dimensional settings with stochastic dynamics.
method Analysis of coupled semilinear infinite-dimensional stochastic evolution equations, development of Nash equilibrium.
result Characterization of unique Nash equilibrium in the limit of many agents.

New tools understand and control dynamics in n-player differentiable games.

problem Understanding and controlling the behavior of gradient-based methods in games.
method Developed new tools to understand and control the dynamics in n-player differentiable games, decomposing the game Jacobian into symmetric and antisymmetric components.
result Motivated Symplectic Gradient Adjustment (SGA) algorithm for finding stable fixed points in differentiable games.

Study on market entry timing in stock liquidation with trading constraints.

problem Optimal timing of market entry and exit in portfolio liquidation with trading restrictions.
method Mean-field game approach to model NN-player and mean-field games of optimal portfolio liquidation.
result Existence of unique equilibrium in both mean-field and NN-player games.

Paper tackles multiplayer symmetric games, securing equal share for n players.

problem Multiplayer games lack unique equilibria, making guarantees unreliable.
method Identifies conditions for equal share, designs efficient algorithms inspired by no-regret learning.
result Proves algorithms achieve approximate equal share across various settings.

Policy mirror ascent achieves Nash equilibrium in mean field games without a population generative model.

problem Achieving Nash equilibrium in mean field games without a population generative model.
method Policy mirror ascent, contractive operator, single-path TD learning.
result Policy mirror ascent converges to Nash equilibrium within O~(ε2)\widetilde{\mathcal{O}}(\varepsilon^{-2}) samples.

Paper studies optimal tracking portfolio in mean field game of large fund competition.

problem Optimal tracking portfolio in large fund competition with relative performance benchmark.
method Formulated mean field game problem, established existence of mean field equilibrium using PDE approach, constructed approximate Nash equilibrium.
result Existence of mean field equilibrium and consistency condition verified.

In this paper we propose and analyze a class of NN-player stochastic games that include finite fuel stochastic games as a special case. We first derive sufficient conditions for the Nash equilibrium (NE) in the form of a verification theorem. The associated Quasi-Variational-Inequalities include an essential game comp…

2018-09-10abs ↗pdf ↗

Study on mean field games with singular controls and their applications.

problem Optimal productivity expansion in dynamic oligopolies.
method Existence and uniqueness of mean field equilibria through nonlinear equations, Abelian limit for discounted and ergodic games.
result Valid connection between discounted and ergodic games, approximation of Nash equilibria.

Decentralised optimisation tasks are important components of multi-agent systems. These tasks can be interpreted as n-player potential games: therefore game-theoretic learning algorithms can be used to solve decentralised optimisation tasks. Fictitious play is the canonical example of these algorithms. Nevertheless fic…

2013-01-15abs ↗pdf ↗

Study equilibrium consumption habits in a large population using mean field games.

problem Equilibrium consumption under external habit formation in a large population.
method Formulated and solved mean field games for linear and multiplicative habit formation preferences, constructed approximate Nash equilibria for large n-player games.
result Characterized mean field equilibrium strategies and derived financial implications.

This work provides lower bounds for differentiable games and defines a new condition number.

problem Understanding the fundamental limits of convergence in differentiable games.
method The authors cast saddle-point and min-max problems as 2-player games and use tools from single-objective convex optimization to derive linear lower bounds for convex-concave games. They also introduce a new condition number for games.
result The authors provide linear lower bounds for differentiable games, including nn-player games, and introduce a new condition number that captures the possibility of linear rates in games without strong convexity or concavity.

Game theory models how agents trade in a risky asset considering price impact and a common signal.

problem Modeling how financial agents liquidate assets in a risky market with price impact and a common signal.
method Formulated and solved a multi-player stochastic differential game and mean field game.
result Equilibrium strategies reveal how agents adjust the predictive trading signal to price impact.

We consider a symmetric multi-players zero-sum game with two strategic variables. There are nn players, n3n\geq 3. Each player is denoted by ii. Two strategic variables are tit_i and sis_i, i{1,,n}i\in \{1, \dots, n\}. They are related by invertible functions. Using the minimax theorem by \cite{sion} we will show that Nas…

2018-06-17abs ↗pdf ↗

Novel approach to Nash equilibrium in mean-field stochastic games with operator resolvents.

problem Finding Nash equilibrium in mean-field stochastic games with mean-field interaction.
method Proposed a novel approach to derive Nash equilibrium semi-explicitly using operator resolvents and stochastic Fredholm equations.
result Equilibrium of the NN-player game converges to mean-field equilibrium, and ε\varepsilon-Nash equilibrium derived as a by-product.

Deep fictitious play converges to Nash equilibrium in stochastic differential games.

problem Finding Nash equilibrium in large stochastic differential games.
method Decouples the game into sub-optimization problems and solves each player's optimal strategy with deep BSDE method.
result Deep fictitious play converges to the true Nash equilibrium.

We study continuous time Bertrand oligopolies in which a small number of firms producing similar goods compete with one another by setting prices. We first analyze a static version of this game in order to better understand the strategies played in the dynamic setting. Within the static game, we characterize the Nash e…

2010-04-10abs ↗pdf ↗

Study competitive agents' optimal consumption and investment strategies with relative performance criteria.

problem Optimizing consumption and investment strategies for multiple agents with relative performance considerations.
method Derived a closed-form solution for an nn-player game and mean field game, analyzing the impact of risk tolerance and competitiveness parameters.
result Unique equilibria found, showing nonlinear and non-monotone dependence on agents' risk tolerance and competitiveness parameters.

Policy-gradient algorithms fail to converge to Nash equilibria in continuous state and action space games.

problem Policy-gradient algorithms lack convergence guarantees in multi-agent continuous state and action space games.
method Analysis of gradient-play in linear quadratic games, showing non-convexity and counterexamples.
result Policy-gradient algorithms can avoid Nash equilibria in certain continuous state and action space games.

The study examines Nash equilibria in utility maximization games with multiplicative performance criteria.

problem Existence and uniqueness of Nash equilibria in multiplicative performance criteria games.
method General characterization of Nash equilibria for a large class of utility functions.
result Existence and uniqueness of Nash equilibria for arbitrary initial wealth vectors.

Study improves LL^{\infty} estimates and extreme value behavior in stochastic differential games.

problem Analyzing the mean-field limit of diffusive games through master equation.
method Using the Master Equation to approximate state processes and establishing LL^{\infty} estimates for the total error.
result Established NoN o \infty asymptotic behavior of upper order statistics of Nash states, initiating Extreme Value Theory for stochastic differential games.

The paper introduces Robust Correlated Equilibrium for games with time-varying costs and proposes an algorithm to achieve it.

problem Games with time-varying costs and disturbances.
method Proposes Robust Correlated Equilibrium and a decentralized algorithm to learn optimal strategies.
result The algorithm converges to the Robust Correlated Equilibrium, showing no regret for each controller.

We propose a model of inter-bank lending and borrowing which takes into account clearing debt obligations. The evolution of log-monetary reserves of NN banks is described by coupled diffusions driven by controls with delay in their drifts. Banks are minimizing their finite-horizon objective functions which take into a…

2016-07-21abs ↗pdf ↗

New learning dynamics achieve fast convergence in games without needing to know utility scales.

problem Fast convergence guarantees in learning games require prior knowledge of utility scales.
method Developed scale-free and scale-invariant learning dynamics using optimistic follow-the-regularized-leader with adaptive learning rates and clipping techniques.
result Achieved fast convergence rates to Nash and correlated equilibria without prior utility scale knowledge.

Study optimal execution in a transient price impact model with multiple traders.

problem Optimal execution among multiple traders with transient price impact.
method Analyzed NN-player optimal execution games in an Obizhaeva--Wang model with and without regularization. Derived equilibrium solutions and explained their behavior.
result Existence of equilibrium restored with a specific time-dependent cost on block trades, and equilibrium is tractable.

We study ranking quantilized mean-field games to select top-performing agents.

problem Selecting top-performing agents in competitive scenarios.
method Developed two formulations: target-based and threshold-based, and provided analytic and semi-explicit solutions.
result Analytic and semi-explicit solutions for quantilized mean-field consistency conditions.

Extends algorithms for computing ΦΦ-equilibria to higher polynomial dimensions.

problem Computing ΦΦ-equilibria for higher-dimensional polynomial deviations.
method Nested application of the EAH algorithm to handle polynomial dimension.
result Efficient algorithms for computing εε-approximate ΦΦ-equilibria and online ΦΦ-regret.