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Browse Source 
┃ Strategy ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃     Avg Duration ┃  Win  Draw  Loss  Win% ┃             Drawdown ┃
┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩
│    Empty │     92 │         1.62 │        2474.507 │       247.45 │ 3 days, 23:07:00 │   45     0    47  48.9 │ 359.078 USDT  10.66% │
└──────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┴──────────────────────┘
This commit is contained in:
Jérôme Delacotte
2026-02-26 23:15:00 +01:00
parent 26aa1ea32b
commit 42832df325
3 changed files with 198 additions and 106 deletions
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35
Empty.py
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@@ -36,6 +36,7 @@ CYAN = "\033[36m"
RESET = "\033[0m"
timeperiods = [3, 5, 12, 24, 36, 48, 60]
long_timeperiods = [80, 100, 120, 140, 160, 180, 200]
sma_indicators = list()
score_indicators = list()
@@ -256,9 +257,6 @@ def condition_generator(dataframe, operator, indicator, crossed_indicator, real_
return condition, dataframe
# #########################################################################################################################
# This class is a sample. Feel free to customize it.
class Empty(IStrategy):
@@ -366,13 +364,15 @@ class Empty(IStrategy):
}
}
buy_deriv1_sma60 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy')
buy_deriv1_sma5d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy')
buy_deriv1_sma12d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy')
buy_deriv1_sma60 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy', optimize=False, load=True)
buy_deriv1_sma5d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy', optimize=False, load=True)
buy_deriv1_sma12d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy', optimize=False, load=True)
buy_deriv2_sma60 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy')
buy_deriv2_sma5d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy')
buy_deriv2_sma12d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy')
buy_deriv2_sma60 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy', optimize=False, load=True)
buy_deriv2_sma5d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy', optimize=False, load=True)
buy_deriv2_sma12d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy', optimize=False, load=True)
buy_longue = CategoricalParameter(long_timeperiods, default=120, space='buy')
# Buy Hyperoptable Parameters/Spaces.
# buy_crossed_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="ADD-20", space='buy')
@@ -851,7 +851,8 @@ class Empty(IStrategy):
informative[f"sma{timeperiod}"] = informative['mid'].ewm(span=timeperiod, adjust=False).mean()
self.calculeDerivees(informative, f"sma{timeperiod}", timeframe=self.timeframe, ema_period=timeperiod)
informative[f"sma200"] = informative['mid'].ewm(span=200, adjust=False).mean()
for timeperiod in long_timeperiods:
informative[f"sma{timeperiod}"] = informative['mid'].ewm(span=timeperiod, adjust=False).mean()
informative['rsi'] = talib.RSI(informative['close'], timeperiod=14)
self.calculeDerivees(informative, f"rsi", timeframe=self.timeframe, ema_period=14)
informative['max_rsi_12'] = talib.MAX(informative['rsi'], timeperiod=12)
@@ -874,6 +875,11 @@ class Empty(IStrategy):
dataframe['max_rsi_12'] = talib.MAX(dataframe['rsi'], timeperiod=12)
dataframe['max_rsi_24'] = talib.MAX(dataframe['rsi'], timeperiod=24)
dataframe["dist_sma200_1d"] = (
(dataframe["close_1d"] - dataframe["sma200_1d"])
/ dataframe["sma200_1d"]
)
# récupérer le dernier trade fermé
trades = Trade.get_trades_proxy(pair=pair,is_open=False)
if trades:
@@ -953,7 +959,9 @@ class Empty(IStrategy):
# conditions.append(dataframe['percent12'] < 0.01)
# conditions.append(dataframe['percent5'] < 0.01)
conditions.append(dataframe['max_rsi_24'] < 80)
conditions.append((dataframe['max_rsi_12_1d'] < 65))\
dynamic_rsi_threshold = 70 + 15 * np.tanh(dataframe["dist_sma200_1d"] * 5)
conditions.append((dataframe['max_rsi_12_1d'] < dynamic_rsi_threshold))
# | (
# (dataframe['sma5_deriv1'] > 0) & (dataframe['sma12_deriv1'] > 0) & (dataframe['sma24_deriv1'] > 0) & (
# dataframe['sma48_deriv1'] > 0) & (dataframe['sma60_deriv1'] > 0) & (dataframe['sma5_deriv1_1d'] > 0))
@@ -962,7 +970,10 @@ class Empty(IStrategy):
conditions.append(dataframe[f"close"] > dataframe['sma60'])
conditions.append(((dataframe[f"range_pos"] < 0.05) ) | ((dataframe['sma12_deriv1'] > 0) & (dataframe['sma12_deriv2'] > 0)))
conditions.append(dataframe['close_1d'] > dataframe['sma200_1d'])
conditions.append(
(dataframe['close_1d'] > dataframe[f'sma{self.buy_longue.value}_1d'])
| (dataframe['sma60_inv_1d'] == -1)
)
# print(f"BUY indicators tested \n"
# f"{self.buy_indicator0.value} {self.buy_crossed_indicator0.value} {self.buy_operator0.value} {self.buy_real_num0.value} \n"