Reinforcement Learning and Interpretability

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Faculty Mentor/s:

Prof. Patrick Zoro, Finance

 

Student names: 

Chenkai Yu

Ruxiao Qian

 

Project Description:

Take a reinforcement learning based trading strategy (Deep Q-Learning based or based on any other RL-based technique and perform the interpretability of the technique. Additionally, check whether the strategy is already able to replicate well known profitable strategies such as Fama French factor models or successful technical analysis strategies and also if it is able to come up with some new signals/techniques.

 

Month/Year Project Began:  
May 2022