Merge pull request #217 from mablue/diamond
negative Shift removed, forloop removed to speedup hyperoptio
This commit is contained in:
Matthias
@@ -9,18 +9,36 @@
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# 𝒲𝒽𝑒𝓇𝑒 𝒽𝒶𝓈 𝑜𝓊𝓇 𝒽𝓊𝓂𝒶𝓃𝒾𝓉𝓎 𝑔𝑜𝓃𝑒?
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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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# * freqtrade backtesting --strategy Diamond
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# 𝓁𝑒𝓉𝓈 𝓅𝒾𝓅 𝓊𝓃𝒾𝓃𝓈𝓉𝒶𝓁𝓁 𝓉𝒶-𝓁𝒾𝒷 𝑜𝓃 𝒜𝒻𝑔𝒽𝒶𝓃𝒾𝓈𝓉𝒶𝓃
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# IMPORTANT: Diamond strategy is designed to be pure and
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# cuz of that it have not any indicator population. idea is that
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# It is just use the pure dataframe ohlcv data for calculation
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# of buy/sell signals, But you can add your indicators and add
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# your key names inside catagorical hyperoptable params and
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# than you be able to hyperopt them as well.
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# thanks to: @Kroissan, @drakes00 And @xmatthias for his patience and helps
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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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# * freqtrade backtesting --strategy Diamond
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# freqtrade hyperopt --hyperopt-loss ShortTradeDurHyperOptLoss --spaces buy sell roi trailing stoploss --strategy Diamond -j 2 -e 10
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# * 3/10: 76 trades. 51/18/7 Wins/Draws/Losses. Avg profit 1.92%. Median profit 2.40%. Total profit 0.04808472 BTC ( 48.08%). Avg duration 5:06:00 min. Objective: 1.75299
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# freqtrade hyperopt --hyperopt-loss OnlyProfitHyperOptLoss --spaces buy sell roi trailing stoploss --strategy Diamond -j 2 -e 10
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# * 10/10: 76 trades. 39/34/3 Wins/Draws/Losses. Avg profit 0.61%. Median profit 0.05%. Total profit 0.01528359 BTC ( 15.28%). Avg duration 17:32:00 min. Objective: -0.01528
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# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --spaces buy sell roi trailing stoploss --strategy Diamond -j 2 -e 10
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# * 4/10: 15 trades. 10/2/3 Wins/Draws/Losses. Avg profit 1.52%. Median profit 7.99%. Total profit 0.00754274 BTC ( 7.54%). Avg duration 1 day, 0:04:00 min. Objective: -0.90653
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# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces buy sell roi trailing stoploss --strategy Diamond -j 2 -e 10
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# * 7/10: 130 trades. 68/54/8 Wins/Draws/Losses. Avg profit 0.71%. Median profit 0.06%. Total profit 0.03050369 BTC ( 30.50%). Avg duration 10:07:00 min. Objective: -11.08185
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# freqtrade hyperopt --hyperopt-loss SortinoHyperOptLoss --spaces buy sell roi trailing stoploss --strategy Diamond -j 2 -e 10
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# * 2/10: 10 trades. 7/0/3 Wins/Draws/Losses. Avg profit 5.50%. Median profit 7.05%. Total profit 0.01817970 BTC ( 18.18%). Avg duration 0:27:00 min. Objective: -11.72450
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# freqtrade hyperopt --hyperopt-loss SortinoHyperOptLossDaily --spaces buy sell roi trailing stoploss --strategy Diamond -j 2 -e 10
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# | * Best | 3/10 | 165 | 98 63 4 | 1.00% | 0.05453885 BTC (54.54%) | 0 days 08:02:00 | 0.00442974 BTC (13.41%) | -41.371 |
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# | * Best | 7/10 | 101 | 56 42 3 | 0.73% | 0.02444518 BTC (24.45%) | 0 days 13:08:00 | 0.00107122 BTC (3.24%) | -66.7687 |
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# * 7/10: 101 trades. 56/42/3 Wins/Draws/Losses. Avg profit 0.73%. Median profit 0.13%. Total profit 0.02444518 BTC ( 24.45%). Avg duration 13:08:00 min. Objective: -66.76866
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# freqtrade hyperopt --hyperopt-loss OnlyProfitHyperOptLoss --spaces buy sell roi trailing stoploss --strategy Diamond -j 2 -e 10
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# * 7/10: 117 trades. 74/41/2 Wins/Draws/Losses. Avg profit 1.91%. Median profit 1.50%. Total profit 0.07370921 BTC ( 73.71%). Avg duration 9:26:00 min. Objective: -0.07371
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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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@@ -32,81 +50,85 @@ 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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# Config: 5 x UNLIMITED STOCK costume pair list,
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# hyperopt : 5000 x SortinoHyperOptLossDaily,
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# 34/5000: 297 trades. 136/156/5 Wins/Draws/Losses. Avg profit 0.49%. Median profit 0.00%. Total profit 45.84477237 USDT ( 33.96Σ%). Avg duration 11:54:00 min. Objective: -46.50379
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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_key": "high",
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"buy_horizontal_push": 7,
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"buy_slow_key": "volume",
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"buy_vertical_push": 0.942,
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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_key": "high",
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"sell_horizontal_push": 10,
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"sell_slow_key": "low",
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"sell_vertical_push": 1.184,
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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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"0": 0.242,
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"13": 0.044,
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"51": 0.02,
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"170": 0
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}
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# Stoploss:
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stoploss = -0.241
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stoploss = -0.271
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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_only_offset_is_reached = True
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# Buy hypers
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trailing_stop_positive = 0.011
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trailing_stop_positive_offset = 0.054
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trailing_only_offset_is_reached = False
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# timeframe
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timeframe = '5m'
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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_vertical_push = DecimalParameter(0.5, 1.5, decimals=3, default=1, space='buy')
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buy_horizontal_push = IntParameter(0, 10, default=0, space='buy')
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buy_fast_key = CategoricalParameter(['open', 'high', 'low', 'close', 'volume',
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# you can not enable this lines befour you
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# populate an indicator for them and set
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# the same key name for it
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# 'ma_fast', 'ma_slow', {...}
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], default='ma_fast', space='buy')
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buy_slow_key = CategoricalParameter(['open', 'high', 'low', 'close', 'volume',
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# 'ma_fast', 'ma_slow', {...}
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], default='ma_slow', space='buy')
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sell_vertical_push = DecimalParameter(0.5, 1.5, decimals=3, default=1, space='sell')
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sell_horizontal_push = IntParameter(0, 10, default=0, space='sell')
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sell_fast_key = CategoricalParameter(['open', 'high', 'low', 'close', 'volume',
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# 'ma_fast', 'ma_slow', {...}
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], default='ma_fast', space='sell')
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sell_slow_key = CategoricalParameter(['open', 'high', 'low', 'close', 'volume',
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# 'ma_fast', 'ma_slow', {...}
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], default='ma_slow', space='sell')
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# you can add new indicators and enable them inside
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# hyperoptable categorical params on the top
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# dataframe['ma_fast'] = ta.SMA(dataframe, timeperiod=9)
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# dataframe['ma_slow'] = ta.SMA(dataframe, timeperiod=18)
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# dataframe['{...}'] = ta.{...}(dataframe, timeperiod={...})
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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, timeperiod=int(self.buy_fast.value))
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dataframe['buy_ema_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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qtpylib.crossed_above
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(
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dataframe[self.buy_fast_key.value].shift(self.buy_horizontal_push.value),
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dataframe[self.buy_slow_key.value] * self.buy_vertical_push.value
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)
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)
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@@ -118,28 +140,14 @@ 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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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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qtpylib.crossed_below
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(
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dataframe[self.sell_fast_key.value].shift(self.sell_horizontal_push.value),
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dataframe[self.sell_slow_key.value] * self.sell_vertical_push.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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