We consider an agent interacting with an unmodeled environment. At each time, the agent makes an observation, takes an action, and incurs a cost. Its actions can influence future observations and costs. The goal is to minimize the long-term average cost. We propose a novel algorithm, known as...

We consider the problem of execution timing in optimal execution. Specifically, we formulate the optimal execution problem of an infinitesimal order as an optimal stopping problem. By using a novel neural network architecture, we develop two versions of data-driven approaches for this problem,...