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.
The ability to give 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 Neural Networks at its heart and to argue why Deep Learning methods can have a lot of potential in the field of High Frequency Trading. The paper goes on to analyze the model's performance based on it's prediction accuracy as well as prediction speed across full-day trading simulations.
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Reinforcement Learning
Neural Networks at its heart
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RL
Learning methods
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We have analyzed
The paper goes on to analyze