┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┓
┃ Strategy ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃ Drawdown ┃ ┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩ │ Empty │ 55 │ 1.51 │ 400.599 │ 40.06 │ 13 days, 3:00:00 │ 54 0 1 98.2 │ 648.572 USDT 31.65% │ └──────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┴──────────────────────┘
This commit is contained in:
Jérôme Delacotte
30
Empty.json
30
Empty.json
@@ -16,30 +16,22 @@
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"max_open_trades": {
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"max_open_trades": 20
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},
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"buy": {
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"buy_crossed_indicator0": "sma24_deriv2",
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"buy_crossed_indicator1": "sma48_deriv2",
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"buy_crossed_indicator2": "sma60_deriv1",
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"buy_indicator0": "sma12_deriv1",
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"buy_indicator1": "sma3_score",
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"buy_indicator2": "sma5_deriv2",
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"buy_operator0": ">",
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"buy_operator1": "D",
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"buy_operator2": "D",
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"buy_real_num0": -0.7,
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"buy_real_num1": 1.0,
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"buy_real_num2": -0.4
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"protection": {
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"drop_from_last_entry": -0.015,
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"range_pos_stoploss": 0.1,
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"stop_buying_indicator": "stop_buying48_1d",
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"stoploss_force": -0.01,
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"stoploss_indicator": "sma3_deriv2"
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},
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"sell": {
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"sell_score_indicator": "sma48_score"
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},
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"protection": {
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"range_pos_stoploss": 0.1,
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"stop_buying_indicator": "stop_buying60_1d",
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"stoploss_force": -0.01,
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"stoploss_indicator": "sma3_deriv2"
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"buy": {
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"buy_deriv_sma12d": -0.01,
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"buy_deriv_sma5d": -0.06,
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"buy_deriv_sma60": -0.001
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}
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},
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"ft_stratparam_v": 1,
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"export_time": "2026-02-21 17:38:15.366827+00:00"
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"export_time": "2026-02-23 21:02:56.692173+00:00"
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}
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151
Empty.py
151
Empty.py
@@ -25,6 +25,7 @@ from random import shuffle
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import logging
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logger = logging.getLogger(__name__)
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timeperiods = [3, 5, 12, 24, 36, 48, 60]
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# Couleurs ANSI de base
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RED = "\033[31m"
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GREEN = "\033[32m"
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@@ -34,9 +35,10 @@ MAGENTA = "\033[35m"
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CYAN = "\033[36m"
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RESET = "\033[0m"
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timeperiods = [3, 5, 12, 24, 48, 60]
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timeperiods = [3, 5, 12, 24, 36, 48, 60]
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score_indicators = list()
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stop_buying_indicators = list()
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god_genes_with_timeperiod = list()
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for timeperiod in timeperiods:
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# god_genes_with_timeperiod.append(f'max{timeperiod}')
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@@ -46,6 +48,10 @@ for timeperiod in timeperiods:
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god_genes_with_timeperiod.append(f"sma{timeperiod}_deriv1")
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god_genes_with_timeperiod.append(f"sma{timeperiod}_deriv2")
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god_genes_with_timeperiod.append(f"sma{timeperiod}_score")
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# stoploss_indicators.append(f"stop_buying{timeperiod}")
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stop_buying_indicators.append(f"stop_buying{timeperiod}_1d")
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score_indicators.append(f"sma{timeperiod}_score")
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# score_indicators.append(f"sma{timeperiod}_score_1d")
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@@ -317,7 +323,8 @@ class Empty(IStrategy):
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'force_sell': False,
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'force_buy': False,
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'current_trade': None,
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'last_trade': None
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'last_trade': None,
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'force_stop': False
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}
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for pair in ["BTC/USDC", "BTC/USDT"]
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}
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@@ -355,22 +362,26 @@ class Empty(IStrategy):
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}
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}
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buy_deriv_sma60 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy')
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buy_deriv_sma5d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy')
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buy_deriv_sma12d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy')
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# Buy Hyperoptable Parameters/Spaces.
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buy_crossed_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="ADD-20", space='buy')
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buy_crossed_indicator1 = CategoricalParameter(god_genes_with_timeperiod, default="ASIN-6", space='buy')
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buy_crossed_indicator2 = CategoricalParameter(god_genes_with_timeperiod, default="CDLEVENINGSTAR-50", space='buy')
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buy_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="SMA-100", space='buy')
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buy_indicator1 = CategoricalParameter(god_genes_with_timeperiod, default="WILLR-50", space='buy')
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buy_indicator2 = CategoricalParameter(god_genes_with_timeperiod, default="CDLHANGINGMAN-20", space='buy')
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buy_operator0 = CategoricalParameter(operators, default="/<R", space='buy')
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buy_operator1 = CategoricalParameter(operators, default="<R", space='buy')
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buy_operator2 = CategoricalParameter(operators, default="CB", space='buy')
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buy_real_num0 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='buy')
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buy_real_num1 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='buy')
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buy_real_num2 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='buy')
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# buy_crossed_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="ADD-20", space='buy')
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# buy_crossed_indicator1 = CategoricalParameter(god_genes_with_timeperiod, default="ASIN-6", space='buy')
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# buy_crossed_indicator2 = CategoricalParameter(god_genes_with_timeperiod, default="CDLEVENINGSTAR-50", space='buy')
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#
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# buy_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="SMA-100", space='buy')
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# buy_indicator1 = CategoricalParameter(god_genes_with_timeperiod, default="WILLR-50", space='buy')
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# buy_indicator2 = CategoricalParameter(god_genes_with_timeperiod, default="CDLHANGINGMAN-20", space='buy')
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#
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# buy_operator0 = CategoricalParameter(operators, default="/<R", space='buy')
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# buy_operator1 = CategoricalParameter(operators, default="<R", space='buy')
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# buy_operator2 = CategoricalParameter(operators, default="CB", space='buy')
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#
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# buy_real_num0 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='buy')
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# buy_real_num1 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='buy')
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# buy_real_num2 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='buy')
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# Sell Hyperoptable Parameters/Spaces.
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# sell_crossed_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="CDLSHOOTINGSTAR-150", space='sell')
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@@ -457,7 +468,7 @@ class Empty(IStrategy):
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profit = trade.calc_profit(current_rate) #round(current_profit * trade.stake_amount, 1)
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# last_lost = self.getLastLost(last_candle, pair)
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# pct_first = 0
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stake_amount = self.adjust_stake_amount(pair, last_candle)
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stake_amount = min(self.wallets.get_available_stake_amount(), self.adjust_stake_amount(pair, last_candle))
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# if (last_candle['enter_long'] == 1 and current_profit < -0.05 and stake_amount > 10) :
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#
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# print(f"adjust {current_time} {stake_amount}")
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@@ -482,10 +493,11 @@ class Empty(IStrategy):
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drop_from_last_entry = (current_rate - last_entry_price) / last_entry_price
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if drop_from_last_entry <= self.drop_from_last_entry.value and last_candle['min60'] == last_candle_3['min60'] \
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and (last_candle['range_pos'] < 0)\
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and last_candle['hapercent'] > 0:
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and last_candle['range_pos'] < 0.03 and last_candle['hapercent'] > 0:
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# stake_amount = trade.stake_amount
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self.pairs[trade.pair]['last_buy'] = current_rate
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self.pairs[trade.pair]['total_amount'] += stake_amount
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print(f"adjust {pair} drop={drop_from_last_entry} {current_time} dispo={dispo} amount={stake_amount} rate={current_rate}")
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# print(f"adjust {pair} {current_time} dispo={dispo} amount={stake_amount} rate={current_rate}")
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trade_type = last_candle['enter_tag'] if last_candle['enter_long'] == 1 else 'pct48'
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@@ -495,7 +507,7 @@ class Empty(IStrategy):
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last_candle=last_candle,
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date=current_time,
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action="🟧 Loss -",
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dispo=dispo,
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dispo=round(dispo,0),
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pair=trade.pair,
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rate=current_rate,
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trade_type=trade_type,
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@@ -525,6 +537,11 @@ class Empty(IStrategy):
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condition = True
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if condition and last_candle['range_pos'] > 0.05:# and self.pairs[pair]['force_stop']:
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condition = last_candle['sma5'] > last_candle['sma60']
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# if self.pairs[pair]['force_stop'] and last_candle['range_pos'] < 0.02:
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# self.pairs[pair]['force_stop'] = False
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if False and self.pairs[pair]['last_trade'].close_date is not None:
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# base cooldown = n bougies / cooldown proportionnel au profit
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@@ -639,12 +656,61 @@ class Empty(IStrategy):
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before_last_candle = dataframe.iloc[-2]
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self.pairs[pair]['current_trade'] = trade
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momentum = last_candle[self.sell_score_indicator.value]
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profit = trade.calc_profit(current_rate) #round(current_profit * trade.stake_amount, 1)
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count_of_buys = trade.nr_of_successful_entries
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expected_profit = self.expectedProfit(pair, last_candle)
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self.pairs[pair]['max_profit'] = max(self.pairs[pair]['max_profit'], profit)
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max_profit = self.pairs[pair]['max_profit']
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baisse = 0
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if profit > 0:
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baisse = 1 - (profit / max_profit)
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mx = max_profit / 5
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self.pairs[pair]['count_of_buys'] = count_of_buys
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self.pairs[pair]['current_profit'] = profit
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dispo = round(self.wallets.get_available_stake_amount()) + self.pairs[pair]['total_amount']
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self.log_trade(
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last_candle=last_candle,
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date=current_time,
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action=("🔴 NOW" if self.pairs[pair]['stop'] else "🟢 NOW "),
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dispo=dispo,
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pair=pair,
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rate=last_candle['close'],
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trade_type='momentum' + str(round(momentum, 2)),
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profit=round(profit, 2),
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buys=count_of_buys,
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stake=0
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)
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if profit > max(5, expected_profit) and baisse > 0.30:
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self.pairs[pair]['force_sell'] = True
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self.pairs[pair]['force_buy'] = (self.pairs[pair]['count_of_buys'] - self.pairs[pair]['has_gain'] > 3)
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return str(count_of_buys) + '_' + 'B30_' + pair + '_' + str(self.pairs[pair]['has_gain'])
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# if last_candle['range_pos'] > 0.05 and current_profit < - last_candle['range_pos'] /4 : #last_candle['cross_sma60']:
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# self.pairs[pair]['force_sell'] = True
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# return 'Range'
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# if last_candle['range_pos'] > 0.05 and current_profit < - last_candle['range_pos'] /4 \
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# and last_candle['sma5_deriv1_1d'] < 0 and last_candle['sma5_deriv2_1d'] < 0 \
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# and last_candle['sma60_deriv1'] < 0 and last_candle['sma60_deriv2'] < 0:
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# self.pairs[pair]['force_sell'] = True
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# self.pairs[pair]['force_stop'] = True
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# return 'Deriv';
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if profit < - (dispo * 0.2):
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print(f'dispo={dispo} wallet={round(self.wallets.get_available_stake_amount())} limit={-dispo * 0.1}')
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self.pairs[pair]['force_sell'] = True
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self.pairs[pair]['force_stop'] = True
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return 'Force';
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# if self.pairs[pair]['force_sell'] and self.pairs[pair]['last_trade'].close_profit > 0.02:
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# return "Force"
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if last_candle['stop_buying']:
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self.pairs[pair]['force_sell'] = True
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return 'Stop'
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# if last_candle['stop_buying']:
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# self.pairs[pair]['force_sell'] = True
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# return 'Stop'
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# Si momentum fort → on laisse courir
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if momentum > 1:
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return None
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@@ -664,11 +730,10 @@ class Empty(IStrategy):
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candle_at_buy = self.pairs[pair]['last_candle']
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# if profit < - 100 :
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# print("stop loss detected")
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# self.pairs[pair]['force_sell'] = True
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# return 0
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# if candle_at_buy['range_pos'] > self.range_pos_stoploss.value and candle_at_buy[self.stoploss_indicator.value] < 0:
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# return self.stoploss_force.value
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# # print(f'test stop loss {self.stoploss} {last_candle["stop_buying12_1d"]}')
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# if last_candle[self.stoploss_indicator.value] and (trade.nr_of_successful_entries >= 4 or self.wallets.get_available_stake_amount() < 300): # and profit < - 30 :
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# range_min = last_candle[f"min{self.stoploss_timeperiod.value}_1d"]
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# range_max = last_candle[f"max{self.stoploss_timeperiod.value}_1d"]
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@@ -740,11 +805,11 @@ class Empty(IStrategy):
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dataframe = merge_informative_pair(dataframe, informative, self.timeframe, "1d", ffill=True)
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# ######################################################################################################
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range_min = dataframe[f"min24_1d"]
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range_min = dataframe[f"min12_1d"]
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range_max = dataframe[f"max48"]
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dataframe[f"range_pos"] = ((dataframe['mid'] - range_min) / (range_max)).rolling(5).mean()
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dataframe['cross_sma60'] = qtpylib.crossed_above(dataframe['sma5'], dataframe['sma60'])
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dataframe[f'stop_buying'] = qtpylib.crossed_below(dataframe[f"sma12"], dataframe['sma48'])
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# récupérer le dernier trade fermé
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@@ -812,15 +877,20 @@ class Empty(IStrategy):
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# conditions.append(condition)
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# conditions.append((dataframe[self.stop_buying_indicator.value] == False) | (dataframe['range_pos'] < 0))
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#conditions.append((dataframe[self.stop_buying_indicator.value] == False) | (dataframe['range_pos'] < 0))
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conditions.append(dataframe['sma60_deriv1'] > self.buy_deriv_sma60.value)
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conditions.append(dataframe['sma5_deriv1_1d'] > self.buy_deriv_sma5d.value)
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conditions.append(dataframe['sma12_deriv1_1d'] > self.buy_deriv_sma12d.value)
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conditions.append(dataframe['hapercent'] > 0)
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# # conditions.append(dataframe[f"range_pos"] <= 0.5)
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conditions.append(((dataframe[f"range_pos"] < 0.05) ) | ((dataframe['sma12_deriv1'] > 0) & (dataframe['sma12_deriv2'] > 0)))
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print(f"BUY indicators tested \n"
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f"{self.buy_indicator0.value} {self.buy_crossed_indicator0.value} {self.buy_operator0.value} {self.buy_real_num0.value} \n"
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f"{self.buy_indicator1.value} {self.buy_crossed_indicator1.value} {self.buy_operator1.value} {self.buy_real_num1.value} \n"
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f"{self.buy_indicator2.value} {self.buy_crossed_indicator2.value} {self.buy_operator2.value} {self.buy_real_num2.value} \n"
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)
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# print(f"BUY indicators tested \n"
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# f"{self.buy_indicator0.value} {self.buy_crossed_indicator0.value} {self.buy_operator0.value} {self.buy_real_num0.value} \n"
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# f"{self.buy_indicator1.value} {self.buy_crossed_indicator1.value} {self.buy_operator1.value} {self.buy_real_num1.value} \n"
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# f"{self.buy_indicator2.value} {self.buy_crossed_indicator2.value} {self.buy_operator2.value} {self.buy_real_num2.value} \n"
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# )
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if conditions:
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dataframe.loc[
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@@ -965,7 +1035,7 @@ class Empty(IStrategy):
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return [
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{
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"method": "CooldownPeriod",
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"stop_duration_candles": 12
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"stop_duration_candles": 6
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},
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# {
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# "method": "MaxDrawdown",
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@@ -1123,3 +1193,12 @@ class Empty(IStrategy):
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def getPctLastBuy(self, pair, last_candle):
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return round((last_candle['close'] - self.pairs[pair]['last_buy']) / self.pairs[pair]['last_buy'], 4)
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def expectedProfit(self, pair: str, last_candle: DataFrame):
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lim = 0.005
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pct = 0.001
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pct_to_max = lim + pct * self.pairs[pair]['count_of_buys']
|
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expected_profit = lim * self.pairs[pair]['total_amount'] # min(3 * lim, max(lim, pct_to_max)) # 0.004 + 0.002 * self.pairs[pair]['count_of_buys'] #min(0.01, first_max)
|
||||
|
||||
self.pairs[pair]['expected_profit'] = expected_profit
|
||||
return expected_profit
|
||||
Reference in New Issue
Block a user