The Forex environment is a forex trading simulator featuring: configurable initial capital, multiple currency pair trading, dynamic or dataset-based spread, CSV history timeseries for trading currencies and observations for the agent, fixed or agent-controlled take-profit, stop-loss and order volume.
The environment features discrete action spaces and optionally continuous action spaces if the orders dont have fixed take-profit/stop-loss and order volume.
A concatenation of num_ticks vectors for the lastest: vector of values from timeseries, equity and its variation, order_status( -1=closed,1=opened),time_opened (normalized with max_order_time), order_profit and its variation, order_drawdown /order_volume_pips, consecutive_drawdown/max_consecutive_dd
discrete action 0: 0=nop,1=close,2=buy,3=sell discrete action 0 parameter: symbol (optional) continuous action 0 parameter: percent_tp, percent_sl,percent_max
TODO: Describe the Reward Function
Install openAI gym, tensorflow and keras.
Copy as a new directory inside the gym/env and update the init.py on gym/env to include the new wnvironment.
Work In Progress. Proper documentation commming soon.