This paper proposes and studies an optimal placement problem in a limit order book. To gain some analytical insights, a simple correlated random walk model with mean-reversion is proposed for the best ask price. Optimal placement strategies for both single-period and multi-period cases are...

Entropy regularization has been extensively adopted to improve the efficiency, the stability, and the convergence of algorithms in reinforcement learning. This paper analyzes both quantitatively and qualitatively the impact of entropy regularization for Mean Field Game (MFG) with learning in a...