This page was generated from docs/source/examples/train_and_evaluate.ipynb.

Train and Evaluate

from tensorforce.agents import Agent
from tensorforce.environments import Environment

from tensortrade.environments import TradingEnvironment
from tensortrade.exchanges.simulated import FBMExchange
from tensortrade.features.scalers import MinMaxNormalizer
from tensortrade.features.stationarity import FractionalDifference
from tensortrade.features import FeaturePipeline
from tensortrade.rewards import SimpleProfit
from tensortrade.actions import DiscreteActions
from tensortrade.strategies import TensorforceTradingStrategy

normalize = MinMaxNormalizer(inplace=True)
difference = FractionalDifference(difference_order=0.6,
                                  inplace=True)
feature_pipeline = FeaturePipeline(steps=[normalize, difference])

reward_scheme = SimpleProfit()
action_scheme = DiscreteActions(n_actions=20, instrument='ETH/BTC')

exchange = FBMExchange(base_instrument='BTC',
                       timeframe='1h',
                       should_pretransform_obs=True)

environment = TradingEnvironment(exchange=exchange,
                                 action_scheme=action_scheme,
                                 reward_scheme=reward_scheme,
                                 feature_pipeline=feature_pipeline)

agent_spec = {
    "type": "ppo_agent",
    "step_optimizer": {
        "type": "adam",
        "learning_rate": 1e-4
    },
    "discount": 0.99,
    "likelihood_ratio_clipping": 0.2,
}

network_spec = [
    dict(type='dense', size=64, activation="tanh"),
    dict(type='dense', size=32, activation="tanh")
]

strategy = TensorforceTradingStrategy(environment=environment, agent_spec=agent_spec, network_spec=network_spec)

performance = strategy.run(episodes=1, testing=True)

performance[-5:]

WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
If you depend on functionality not listed there, please file an issue.

100%|██████████| 1/1 [00:08<00:00,  8.94s/it]

Finished running strategy.
Total episodes: 1 (1666 timesteps).
Average reward: 1150.3350630537668.

	balance	net_worth
1661	9999.829222	10000.187790
1662	9997.354264	9998.232905
1663	9994.879919	9995.990028
1664	9991.169320	9992.191048
1665	9991.535304	9992.226192

from tensortrade.environments import TradingEnvironment
from tensortrade.exchanges.simulated import FBMExchange
from tensortrade.features.scalers import MinMaxNormalizer
from tensortrade.features.stationarity import FractionalDifference
from tensortrade.features import FeaturePipeline
from tensortrade.rewards import SimpleProfit
from tensortrade.actions import DiscreteActions
from tensortrade.strategies import StableBaselinesTradingStrategy

normalize = MinMaxNormalizer(inplace=True)
difference = FractionalDifference(difference_order=0.6,
                                  inplace=True)
feature_pipeline = FeaturePipeline(steps=[normalize, difference])

reward_scheme = SimpleProfit()
action_scheme = DiscreteActions(n_actions=20, instrument='ETH/BTC')

exchange = FBMExchange(base_instrument='BTC',
                       timeframe='1h',
                       should_pretransform_obs=True)

environment = TradingEnvironment(exchange=exchange,
                                 action_scheme=action_scheme,
                                 reward_scheme=reward_scheme,
                                 feature_pipeline=feature_pipeline)

strategy = StableBaselinesTradingStrategy(environment=environment)

performance = strategy.run(episodes=10)

performance[-5:]

Finished running strategy.
Total episodes: 10 (16660 timesteps).
Average reward: 1.1827063286237227.

	balance	net_worth
1660	11226.614898	11227.750341
1661	11226.686075	11227.725535
1662	11226.721664	11227.658857
1663	11226.739458	11227.908940
1664	11223.960840	11225.188709