negative Shift removed, forloop removed to speedup hyperoptio
This commit is contained in:
Masoud Azizi
@@ -10,17 +10,11 @@
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# 𝒲𝒽𝑒𝓇𝑒 𝒽𝒶𝓈 𝒽𝓊𝓂𝒶𝓃𝒾𝓉𝓎 𝑔𝑜𝓃𝑒?
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# 𝒲𝒽𝓎 𝓃𝑜𝓉 𝒽𝑒𝓁𝓅 𝓌𝒽𝑒𝓃 𝓌𝑒 𝒸𝒶𝓃?
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# IMPORTANT: This strategy
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# designed for "ZERO" loss and "UNDER"
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# 15 minuts avg duration.So if you have more
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# loss and more avg, Its "NOT" normal result, and
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# you will change config.json variables and hyperoption commands
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# Thanks To @xmatthias if he was approve the last version of This strategy
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# That just a lazy code. I never can reach to this strategy(Now its really a diamond.)
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# * freqtrade hyperopt --hyperopt-loss ShortTradeDurHyperOptLoss --spaces all --strategy Diamond -e 700 -j 2 --timerange 20210810-20210813
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# thanks to: @Kroissan, @drakes00 And @xmatthias for his patience and helps
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# * freqtrade hyperopt --hyperopt-loss ShortTradeDurHyperOptLoss --spaces buy sell roi trailing --strategy Diamond -e 700 -j 2
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# * freqtrade backtesting --strategy Diamond
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# Author: @Mablue (Masoud Azizi)
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# github: https://github.com/mablue/
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# (First Hyperopt it.A hyperopt file is available)
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# --- Do not remove these libs ---
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from freqtrade.strategy.hyper import CategoricalParameter, DecimalParameter, IntParameter
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from freqtrade.strategy.interface import IStrategy
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@@ -32,82 +26,65 @@ import talib.abstract as ta
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from functools import reduce
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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##### SETINGS #####
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# It hyperopt just one set of params for all buy and sell strategies if true.
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DUALFIT = False
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COUNT = 10
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GAP = 3
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### END SETINGS ###
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class Diamond(IStrategy):
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# ###################### RESULT PLACE ######################
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# * 6/700: 1 trades. 1/0/0 Wins/Draws/Losses. Avg profit 17.68%. Median profit 17.68%. Total profit 58.94100000 USDT ( 5.89Σ%). Avg duration 0:00:00 min. Objective: 1.79949
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# 1/700: 20 trades. 13/4/3 Wins/Draws/Losses. Avg profit 6.30%. Median profit 7.19%. Total profit 0.04159258 BTC ( 41.59%). Avg duration 2 days, 22:24:00 min. Objective: 1.83361
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# Buy hyperspace params:
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buy_params = {
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"buy_fast": 31,
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"buy_push": 0.72,
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"buy_shift": -7,
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"buy_slow": 2,
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"buy_fast": 22,
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"buy_push": 1.65,
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"buy_slow": 16,
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}
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# Sell hyperspace params:
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sell_params = {
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"sell_fast": 17,
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"sell_push": 1.493,
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"sell_shift": -7,
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"sell_slow": 28,
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"sell_fast": 10,
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"sell_push": 1.53,
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"sell_slow": 50,
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}
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# ROI table:
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minimal_roi = {
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"0": 0.177,
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"31": 0.059,
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"61": 0.021,
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"170": 0
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"0": 0.647,
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"992": 0.285,
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"2659": 0.072,
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"7323": 0
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}
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# Stoploss:
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stoploss = -0.241
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stoploss = -0.259
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# Trailing stop:
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trailing_stop = True
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trailing_stop_positive = 0.13
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trailing_stop_positive_offset = 0.189
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trailing_stop_positive = 0.222
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trailing_stop_positive_offset = 0.284
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trailing_only_offset_is_reached = True
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# Buy hypers
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timeframe = '5m'
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timeframe = '4h'
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# #################### END OF RESULT PLACE ####################
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buy_push = DecimalParameter(0, 2, decimals=3, default=1, space='buy')
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buy_shift = IntParameter(-10, 0, default=-6, space='buy')
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buy_fast = IntParameter(2, 50, default=9, space='buy')
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buy_slow = IntParameter(2, 50, default=18, space='buy')
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if not DUALFIT:
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sell_push = DecimalParameter(
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0, 2, decimals=3, default=1, space='sell')
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sell_shift = IntParameter(-10, 0, default=-6, space='sell')
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sell_fast = IntParameter(2, 50, default=9, space='sell')
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sell_slow = IntParameter(2, 50, default=18, space='sell')
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buy_push = DecimalParameter(1, 2, decimals=2, default=1, space='buy')
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sell_push = DecimalParameter(1, 2, decimals=2, default=1, space='sell')
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buy_fast = IntParameter(2, 30, default=1, space='buy')
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buy_slow = IntParameter(2, 50, default=1, space='buy')
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sell_fast = IntParameter(2, 30, default=1, space='sell')
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sell_slow = IntParameter(2, 50, default=1, space='sell')
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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return dataframe
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def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe['buy_ema_fast'] = ta.SMA(
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dataframe['buy_ma_fast'] = ta.SMA(
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dataframe, timeperiod=int(self.buy_fast.value))
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dataframe['buy_ema_slow'] = ta.SMA(
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dataframe['buy_ma_slow'] = ta.SMA(
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dataframe, timeperiod=int(self.buy_slow.value))
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conditions = []
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conditions.append(
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qtpylib.crossed_above(
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dataframe['buy_ema_fast'].shift(self.buy_shift.value),
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dataframe['buy_ema_slow'].shift(
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self.buy_shift.value)*self.buy_push.value
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)
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(dataframe['buy_ma_fast']/dataframe['buy_ma_slow']
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).between(1, self.buy_push.value)
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)
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if conditions:
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@@ -118,28 +95,16 @@ class Diamond(IStrategy):
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return dataframe
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def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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push = self.buy_push.value
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shift = self.buy_shift.value
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ema_fast = dataframe['buy_ema_fast']
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ema_slow = dataframe['buy_ema_slow']
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if not DUALFIT:
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push = self.sell_push.value
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shift = self.sell_shift.value
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ema_fast = dataframe['sell_ema_fast'] = ta.SMA(
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dataframe, timeperiod=int(self.buy_fast.value))
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ema_slow = dataframe['sell_ema_slow'] = ta.SMA(
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dataframe, timeperiod=int(self.buy_slow.value))
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dataframe['sell_ma_fast'] = ta.SMA(
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dataframe, timeperiod=int(self.sell_fast.value))
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dataframe['sell_ma_slow'] = ta.SMA(
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dataframe, timeperiod=int(self.sell_slow.value))
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conditions = []
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conditions.append(
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qtpylib.crossed_below(
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ema_fast.shift(shift),
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ema_slow.shift(shift)*push
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)
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(dataframe['sell_ma_slow']/dataframe['sell_ma_fast']
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).between(1, self.sell_push.value)
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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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