Deep Reinforcement Learning in High Frequency Trading

The ability to give a precise and fast prediction for the price movement of stocks is the key to profitability in High Frequency Trading. The main objective of this paper is to propose a novel way of modeling the high frequency trading problem using Deep Reinforcement Learning and to argue why Deep RL can have a lot of potential in the field of High Frequency Trading. We have analyzed the model's performance based on it's prediction accuracy as well as prediction speed across full-day trading simulations.