gym-gopherfx

A gym environment for reinforcement training on forex historical data.

Historical data is no way a predictor of future behaviour in forex, but can be used as challenging science experiment :).

How to run

Clone the repo

docker-compose up -d

Access http://127.0.0.1:8050/ to access the dashboard.

To start a random agent and see live evolutions:

docker exec -it gym-gopherfx_python_1 python random_agent.py

About the environment

Gopherfx-v0

Observation: A tuple of the current datetime and rate

The available actions are:

0 - wait
1 - buy
2 - sell

Reward:

0 - for waiting/first buy/first sell
trade_result - for closing an open position
-1 - when depleting the budget

The episodes ends when the trading day is over or the budget is depleted.

Gopherfx-v1

Observation:

A tuple of Candle rate data representing the market state at the step moment
The value for the current open position
The action required to close the current open position

Raw example:

{
  "volume": 45,
  "time": "2018-06-01T00:00:00.000000000Z",
  "bid": {
    "o": "1.16916",
    "h": "1.16929",
    "l": "1.16908",
    "c": "1.16915"
  },
  "ask": {
    "o": "1.16933",
    "h": "1.16946",
    "l": "1.16924",
    "c": "1.16930"
  }
}