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11-deep-rl-trader

README.md

Deep RL Trader (Duel DQN) Implemented using Keras-RL

I could not get this example to run due to issues with versions in requirements.txt

  1. Trading environment(OpenAI Gym) for trading crypto currency
  2. Duel Deep Q Network

Agent is implemented using keras-rl(https://github.com/keras-rl/keras-rl)

Agent is expected to learn useful action sequences to maximize profit in a given environment.
Environment limits agent to either buy, sell, hold stock(coin) at each step.
If an agent decides to take a

  • LONG position it will initiate sequence of action such as buy- hold- hold- sell
  • for a SHORT position vice versa (e.g.) sell - hold -hold -buy.

Only a single position can be opened per trade.

  • Thus invalid action sequence like buy - buy will be considered buy- hold.
  • Default transaction fee is : 0.0005

Reward is given

  • when the position is closed or
  • an episode is finished.

Dependencies

Install this: brew install ta-lib

Create a virtual environment and install requirements:

python3 -m venv env_deep_rl_trader
source env_deep_rl_trader/bin/activate
pip3 install -r requirements.txt

Add new virtual environment to jupyter:

python -m ipykernel install --user --name=deep_rl_trader

Open the Jupyter Notebook and select the kernel from above.

Sources