Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
License: MIT License
Happy New Year!
In this model you set certain amounts of equities in the initial portfolio. Therefore, the agent can first start buying or selling equities. But some markets like forex, you can start buying or selling even without any position. Is it possible to design this kind of agents? Thank you very much!
Thanks for your work, I like your approach for trading stocks, could this be ported to trading cryptocurrencies instead?
What are your thoughts on this, are there any better approaches than DeepQLearning?
Thanks in advance!
As far as I understand it there is a typo in the following line:
minibatch is used instead of mini_batch so the for-loop is not called and thus the model.fit method will never be calledHow can I get the data of training you have done.
All Models are empty?
Can you re- upload?
Michael
Thanks for your great job and sharing.
I ran your code(aapl.us & amzn.us) and chose the models with good results(PnL). Then I used the same data(train data) to test the models. They almost get zero profit because of taking action two(do nothing). Do you have any idea about this problem?
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