Please find the project inside Zip file that contain the multiple folders
3.1 Data pre-processing 3.2 Agent is trained with 51 Episode. Input here are following parameters:
3.3 Evaluate and final program that predict the total portfolio value for one episode
To execute the program, you would need to run the Trading.IPynb file with input as stated above and then look at the result
References
MACHINE LEARNING FOR TRADING: GORDON RITTER: https://cims.nyu.edu/~ritter/ritter2017machine.pdf
Financial Trading as a Game: A Deep Reinforcement Learning Approach: Huang, Chien-Yi https://arxiv.org/pdf/1807.02787.pdf
Convergence of Q-learning: a simple proof: Francisco S. Melo: http://users.isr.ist.utl.pt/~mtjspaan/readingGroup/ProofQlearning.pdf
https://medium.com/@chinmaya.mishra1/deep-dive-in-to-reinforcement-learning-10fa30b418f9
David Silver’s lectures about deep reinforcement learning