Source code for tensortrade.rewards.simple_profit_strategy

# Copyright 2019 The TensorTrade Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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import pandas as pd
import numpy as np

from tensortrade.rewards import RewardStrategy
from tensortrade.trades import TradeType, Trade


[docs]class SimpleProfitStrategy(RewardStrategy): """A reward strategy that rewards the agent for profitable trades and prioritizes trading over not trading. This strategy supports simple action strategies that trade a single position in a single instrument at a time. """
[docs] def reset(self): """Necessary to reset the last purchase price and state of open positions.""" self._purchase_price = -1 self._is_holding_instrument = False
[docs] def get_reward(self, current_step: int, trade: Trade) -> float: """Reward -1 for not holding a position, 1 for holding a position, 2 for opening a position, and 1 + 5^(log_10(profit)) for closing a position. The 5^(log_10(profit)) function simply slows the growth of the reward as trades get large. """ if trade.is_hold and self._is_holding_instrument: return 1 elif trade.is_buy and trade.amount > 0: self._purchase_price = trade.price self._is_holding_instrument = True return 2 elif trade.is_sell and trade.amount > 0: self._is_holding_instrument = False profit_per_instrument = trade.price - self._purchase_price profit = trade.amount * profit_per_instrument profit_sign = np.sign(profit) return profit_sign * (1 + (5 ** np.log10(abs(profit)))) return -1