arXiv research

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

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

Federated learning linked to mean-field games for large-scale learning.

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

Study of portfolio management under relative performance concerns using mean field games.

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

Study of a game with multiple players and common shocks using probabilistic methods.

A new method uses Mean Field Games to optimize mixture models of Bernoulli and categorical distributions.

Mean field game with defaultable agents and systemic risk quantified.

In this paper we study iterative procedures for stationary equilibria in games with large number of players. Most of learning algorithms for games with continuous action spaces are limited to strict contraction best reply maps in which the Banach-Picard iteration converges with geometrical convergence rate. When the be…

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

Existence of strong randomized equilibria in mean-field games with common noise.

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

Mean Field Games applied to finance and economics.

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 $n$-player equilibria converges to it as $n\to\infty$. However, both the finite and infinite player versions of the game often admit multiple equilibria. We show that me…

Study Nash equilibrium in mean field portfolio games with random market parameters.

Deep learning enhances solving complex mean field games in finance.

We discuss a natural game of competition and solve the corresponding mean field game with \emph{common noise} when agents' rewards are \emph{rank dependent}. We use this solution to provide an approximate Nash equilibrium for the finite player game and obtain the rate of convergence.

Study Nash equilibria in mean field portfolio games with consumption.

Study on liquidation games with market drop-out, proving unique equilibria.

Study optimal investment and consumption strategies for competitive agents with habit formation.

Mean field game theory studies the behavior of a large number of interacting individuals in a game theoretic setting and has received a lot of attention in the past decade (Lasry and Lions, Japanese journal of mathematics, 2007). In this work, we derive mean field game partial differential equation systems from determi…

Study policy gradient for large-agent mean-field control and game in continuous time.

Study analyzes portfolio liquidation games influenced by self-exciting order flow.

Modeling pollution from competing firms using mean-field games.

Paper proposes a mean-field gradient descent for zero-sum games, proving convergence to Nash equilibrium.

Study optimal investment strategies for competitive agents using Mean Field Games.

Game-theoretic models predict asset prices in financial markets.

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

New approach finds solutions to games with unbounded controls.

We analyze an $N+1$-player game and the corresponding mean field game with state space $\{0,1\}$. The transition rate of $j$-th player is the sum of his control $α^j$ plus a minimum jumping rate $η$. Instead of working under monotonicity conditions, here we consider an anti-monotone running cost. We show that the mean …

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

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

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

Paper studies convergence of Mean-Field GDA dynamics for MNE of continuous games.

We study discrete-time mean-field Markov games with infinite numbers of agents where each agent aims to minimize its ergodic cost. We consider the setting where the agents have identical linear state transitions and quadratic cost functions, while the aggregated effect of the agents is captured by the population mean o…

Entropy regularization improves MFG learning efficiency and stability.

Solves a game between brokers and informed traders using stochastic differential equations.

Study uses Mean Field Game to analyze Bitcoin mining hashpower dynamics.

New algorithm reduces MFGs with common noise complexity.

In this work, we systematically investigate mean field games and mean field type control problems with multiple populations using a coupled system of forward-backward stochastic differential equations of McKean-Vlasov type stemming from Pontryagin's stochastic maximum principle. Although the same cost functions as well…

New MFG model for MV portfolio management with peer-based risk aversion.

Unified q-learning for mean-field jump-diffusion models with unobservable population distribution.

Stochastic games provide a framework for interactions among multiple agents and enable a myriad of applications. In these games, agents decide on actions simultaneously, the state of every agent moves to the next state, and each agent receives a reward. However, finding an equilibrium (if exists) in this game is often …

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

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

The paper models asset pricing in a partially observed market using mean field game theory and exponential quadratic Gaussian framework.

Study on convergence of Langevin dynamics for zero-sum games in probability distributions.