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switch to using FT calc_profi_pct, reverse entry/exit fees

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This commit is contained in:
robcaulk 2022-11-13 13:41:17 +01:00
parent e45d791c19
commit 81f800a79b
4 changed files with 12 additions and 19 deletions
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1
freqtrade/freqai/RL/Base4ActionRLEnv.py
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@ -74,6 +74,7 @@ class Base4ActionRLEnv(BaseEnvironment):
self._last_trade_tick = self._current_tick self._last_trade_tick = self._current_tick
elif action == Actions.Exit.value: elif action == Actions.Exit.value:
self._position = Positions.Neutral self._position = Positions.Neutral
self._update_total_profit()
trade_type = "neutral" trade_type = "neutral"
self._last_trade_tick = None self._last_trade_tick = None
else: else:

2
freqtrade/freqai/RL/Base5ActionRLEnv.py
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@ -75,8 +75,6 @@ class Base5ActionRLEnv(BaseEnvironment):
if self._current_tick == self._end_tick: if self._current_tick == self._end_tick:
self._done = True self._done = True
self.update_portfolio_log_returns(action)
self._update_unrealized_total_profit() self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action) step_reward = self.calculate_reward(action)
self.total_reward += step_reward self.total_reward += step_reward

15
freqtrade/freqai/RL/BaseEnvironment.py
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@ -165,12 +165,12 @@ class BaseEnvironment(gym.Env):
if self._position == Positions.Neutral: if self._position == Positions.Neutral:
return 0. return 0.
elif self._position == Positions.Short: elif self._position == Positions.Short:
current_price = self.add_entry_fee(self.prices.iloc[self._current_tick].open)
last_trade_price = self.add_exit_fee(self.prices.iloc[self._last_trade_tick].open)
return (last_trade_price - current_price) / last_trade_price
elif self._position == Positions.Long:
current_price = self.add_exit_fee(self.prices.iloc[self._current_tick].open) current_price = self.add_exit_fee(self.prices.iloc[self._current_tick].open)
last_trade_price = self.add_entry_fee(self.prices.iloc[self._last_trade_tick].open) last_trade_price = self.add_entry_fee(self.prices.iloc[self._last_trade_tick].open)
return (last_trade_price - current_price) / last_trade_price
elif self._position == Positions.Long:
current_price = self.add_entry_fee(self.prices.iloc[self._current_tick].open)
last_trade_price = self.add_exit_fee(self.prices.iloc[self._last_trade_tick].open)
return (current_price - last_trade_price) / last_trade_price return (current_price - last_trade_price) / last_trade_price
else: else:
return 0. return 0.
@ -210,9 +210,8 @@ class BaseEnvironment(gym.Env):
""" """
An example reward function. This is the one function that users will likely An example reward function. This is the one function that users will likely
wish to inject their own creativity into. wish to inject their own creativity into.
:params: :param action: int = The action made by the agent for the current candle.
action: int = The action made by the agent for the current candle. :return:
:returns:
float = the reward to give to the agent for current step (used for optimization float = the reward to give to the agent for current step (used for optimization
of weights in NN) of weights in NN)
""" """
@ -234,7 +233,7 @@ class BaseEnvironment(gym.Env):
def _update_total_profit(self): def _update_total_profit(self):
pnl = self.get_unrealized_profit() pnl = self.get_unrealized_profit()
if self.compound_trades: if self.compound_trades:
# assumes unite stake and compounding # assumes unitestake and compounding
self._total_profit = self._total_profit * (1 + pnl) self._total_profit = self._total_profit * (1 + pnl)
else: else:
# assumes unit stake and no compounding # assumes unit stake and no compounding

13
freqtrade/freqai/RL/BaseReinforcementLearningModel.py
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@ -180,17 +180,12 @@ class BaseReinforcementLearningModel(IFreqaiModel):
if self.data_provider._exchange is None: # type: ignore if self.data_provider._exchange is None: # type: ignore
logger.error('No exchange available.') logger.error('No exchange available.')
else: else:
current_value = self.data_provider._exchange.get_rate( # type: ignore current_rate = self.data_provider._exchange.get_rate( # type: ignore
pair, refresh=False, side="exit", is_short=trade.is_short) pair, refresh=False, side="exit", is_short=trade.is_short)
openrate = trade.open_rate
now = datetime.now(timezone.utc).timestamp() now = datetime.now(timezone.utc).timestamp()
trade_duration = int((now - trade.open_date.timestamp()) / self.base_tf_seconds) trade_duration = int((now - trade.open_date_utc) / self.base_tf_seconds)
if 'long' in str(trade.enter_tag): current_profit = trade.calc_profit_ratio(current_rate)
market_side = 1
current_profit = (current_value - openrate) / openrate
else:
market_side = 0
current_profit = (openrate - current_value) / openrate
return market_side, current_profit, int(trade_duration) return market_side, current_profit, int(trade_duration)