arturbeg/reinforcement_learning_oe

The work aims to explore Value based, Deep Reinforcment Learning (Deep Q-Learning and Double Deep Q-Learning) for the problem of Optimal Trade Execution. The problem of Optimal Trade Execution aims to find the the optimal "path" of executing a stock order, or in other words the number of shares to be executed at different steps given a time constraint, such that the price impact from the market is minimised and consequently revenue from executing a stock order maximised.

Python