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Recent Advances in Reinforcement Learning in Finance
In contrast to classical stochastic control theory and other analytical approaches for solving financial decision-making problems that heavily reply on model assumptions, new developments from reinforcement learning (RL) are able to make full use of the large amount of financial data with fewer model assumptions and to improve decisions in complex financial environments.
Policy Gradient Methods Find the Nash Equilibrium in N-player General-sum Linear-quadratic Games
We consider a general-sum N-player linear-quadratic game with stochastic dynamics over a finite horizon and prove the global convergence of the natural policy gradient method to the Nash equilibrium.
Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon
In particular, we consider the convergence of policy gradient methods in the setting of known and unknown parameters.
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