space decimals increased,sell spaces removed
This commit is contained in:
Masoud Azizi
@@ -9,7 +9,7 @@
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# },
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# IMPORTANT: INSTALL TA BEFOUR RUN(pip install ta)
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#
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# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --spaces roi buy sell --strategy Heracles
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# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --spaces roi buy --strategy Heracles
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# ######################################################################
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# --- Do not remove these libs ---
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from freqtrade.strategy.hyper import IntParameter, DecimalParameter
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@@ -28,48 +28,41 @@ import numpy as np
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class Heracles(IStrategy):
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########################################## RESULT PASTE PLACE ##########################################
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# 18/100: 111 trades. 77/23/11 Wins/Draws/Losses. Avg profit 3.81%. Median profit 4.40%. Total profit 2114.06222218 USDT ( 42.28Σ%). Avg duration 3 days, 3:04:00 min. Objective: -16.78579
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# 10/100: 25 trades. 18/4/3 Wins/Draws/Losses. Avg profit 5.92%. Median profit 6.33%. Total profit 0.04888306 BTC ( 48.88Σ%). Avg duration 4 days, 6:24:00 min. Objective: -11.42103
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# Buy hyperspace params:
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buy_params = {
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"buy_crossed_indicator_shift": 5,
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"buy_div": 3.61,
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"buy_indicator_shift": 1,
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"buy_crossed_indicator_shift": 9,
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"buy_div_max": 0.75,
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"buy_div_min": 0.16,
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"buy_indicator_shift": 15,
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}
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# Sell hyperspace params:
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sell_params = {
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"sell_atol": 0.30989,
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"sell_crossed_indicator_shift": 2,
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"sell_indicator_shift": 5,
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"sell_rtol": 0.19449,
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}
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# ROI table:
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minimal_roi = {
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"0": 0.725,
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"889": 0.171,
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"2776": 0.044,
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"5299": 0
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"0": 0.598,
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"644": 0.166,
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"3269": 0.115,
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"7289": 0
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}
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# Stoploss:
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stoploss = -0.312
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stoploss = -0.256
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# Optimal timeframe use it in your config
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timeframe = '4h'
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########################################## END RESULT PASTE PLACE ######################################
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# buy params
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buy_div = DecimalParameter(-5, 5, default=0.51844, decimals=4, space='buy')
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buy_indicator_shift = IntParameter(-5, 5, default=4, space='buy')
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buy_crossed_indicator_shift = IntParameter(-5, 5, default=1, space='buy')
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# sell params
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sell_rtol = DecimalParameter(1.e-10, 1.e-0, default=0.05468, decimals=10, space='sell')
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sell_atol = DecimalParameter(1.e-16, 1.e-0, default=0.00019, decimals=10, space='sell')
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sell_indicator_shift = IntParameter(-5, 5, default=4, space='sell')
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sell_crossed_indicator_shift = IntParameter(-5, 5, default=1, space='sell')
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# Optimal timeframe use it in your config
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timeframe = '4h'
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buy_div_min = DecimalParameter(0, 1, default=0.16, decimals=2, space='buy')
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buy_div_max = DecimalParameter(0, 1, default=0.75, decimals=2, space='buy')
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buy_indicator_shift = IntParameter(0, 20, default=16, space='buy')
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buy_crossed_indicator_shift = IntParameter(0, 20, default=9, space='buy')
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe = dropna(dataframe)
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@@ -93,26 +86,6 @@ class Heracles(IStrategy):
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fillna=False
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)
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dataframe['trend_macd_signal'] = ta.trend.macd_signal(
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dataframe['close'],
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window_slow=26,
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window_fast=12,
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window_sign=9,
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fillna=False
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)
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dataframe['trend_ema_fast'] = ta.trend.EMAIndicator(
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close=dataframe['close'], window=12, fillna=False
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).ema_indicator()
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# for checking crossovers!
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# but we dont need to crossovers we just calculate dividation
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# import matplotlib.pyplot as plt
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# dataframe.iloc[:,6:].plot(subplots=False)
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# plt.tight_layout()
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# plt.show()
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return dataframe
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def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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@@ -126,16 +99,17 @@ class Heracles(IStrategy):
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DFIND = dataframe[IND]
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DFCRS = dataframe[CRS]
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d = DFIND.shift(self.buy_indicator_shift.value).div(
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DFCRS.shift(self.buy_crossed_indicator_shift.value))
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# print(d.min(), "\t", d.max())
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conditions.append(
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DFIND.shift(self.buy_indicator_shift.value).div(
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DFCRS.shift(self.buy_crossed_indicator_shift.value)
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) <= self.buy_div.value
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)
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d.between(self.buy_div_min.value, self.buy_div_max.value))
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if conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, conditions),
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'buy'] = 1
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'buy']=1
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return dataframe
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@@ -143,25 +117,5 @@ class Heracles(IStrategy):
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"""
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Sell strategy Hyperopt will build and use.
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"""
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conditions = []
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IND = 'trend_ema_fast'
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CRS = 'trend_macd_signal'
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DFIND = dataframe[IND]
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DFCRS = dataframe[CRS]
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conditions.append(
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np.isclose(
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DFIND.shift(self.sell_indicator_shift.value),
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DFCRS.shift(self.sell_crossed_indicator_shift.value),
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rtol=self.sell_rtol.value,
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atol=self.sell_rtol.value
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)
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)
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if conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, conditions),
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'sell']=1
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return dataframe
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