Hands-On Machine Learning for Algorithmic Trading

Dynamic programming – Value and Policy iteration

Finite MDPs are a simple yet fundamental framework. We introduce the trajectories of rewards that the agent aims to optimize, and define the policy and value functions they are used to formulate the optimization problem and the Bellman equations that form the basis for the solution methods.