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Browse Source 
┃ Strategy ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃    Avg Duration ┃  Win  Draw  Loss  Win% ┃             Drawdown ┃
┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩
│    Empty │    108 │         2.03 │        5660.765 │       566.08 │ 4 days, 9:45:00 │   62     0    46  57.4 │ 757.488 USDT  17.40% │
└──────────┴────────┴──────────────┴─────────────────┴──────────────┴─────────────────┴────────────────────────┴──────────────────────┘
This commit is contained in:
Jérôme Delacotte
2026-03-01 20:56:59 +01:00
parent 1656ab695a
commit 5ce48130f4
2 changed files with 333 additions and 9 deletions
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34
Empty.py
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@@ -364,13 +364,14 @@ class Empty(IStrategy):
last_candle_2 = dataframe.iloc[-2].squeeze()
last_candle_3 = dataframe.iloc[-3].squeeze()
# if (last_candle['has_cross_min_6'] and last_candle['sma60_deriv1'] > 0) or (last_candle['sma12_inv_1d']):
# self.pairs[pair]['count_of_lost'] = 0
condition = False if self.pairs[pair]['count_of_lost'] >= 1 \
and (last_candle['sma12_deriv1_1d'] < 0.001 \
or last_candle['sma12_deriv2_1d'] < 0.001) and entry_tag != 'dist' else True
if entry_tag == 'Force':
if self.pairs[pair]['count_of_lost'] >= 1:
self.pairs[pair]['count_of_lost'] = 0
condition = False
else:
condition = False if self.pairs[pair]['count_of_lost'] >= 1 \
and (last_candle['sma12_deriv1_1d'] < 0.001 or last_candle['sma12_deriv2_1d'] < 0.001) \
and entry_tag != 'dist' else True
reason = ''
if not condition:
reason = 'lost'
@@ -858,16 +859,31 @@ class Empty(IStrategy):
# ['enter_long', 'enter_tag']
# ] = (1, 'cross_min')
# conditions = list()
conditions = list()
conditions.append(dataframe['sma12_deriv1'] > 0.00)
conditions.append(dataframe['sma60_deriv1'] > 0.0)
conditions.append(dataframe['sma5_deriv1_1d'] > 0.0)
conditions.append(dataframe['sma12_deriv1_1d'] > 0.0)
conditions.append(dataframe['sma24_deriv1_1d'] > 0.0)
conditions.append(dataframe['sma100_deriv1_1d'] > 0.0)
# conditions.append(dataframe['sma12_deriv1_1d'] > 0.0)
# # conditions.append(dataframe['close_1d'] < dataframe[f'sma{self.buy_longue.value}_1d'])
# # conditions.append(dataframe['has_cross_min'].rolling(6).max() == 1)
# # conditions.append(dataframe['mid_smooth5'] > dataframe['mid_smooth5'].shift(1))
# conditions.append(dataframe['min12'] == dataframe['min12'].shift(3))
# conditions.append((dataframe['percent24'] < -0.025) | (dataframe['percent12'] < -0.025))
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
['enter_long', 'enter_tag']
] = (1, 'Rise')
# conditions = list()
# conditions.append(dataframe['has_cross_min_6'] == True)
# conditions.append(dataframe['min36'] == dataframe['min36'].shift(3))
# dataframe.loc[
# reduce(lambda x, y: x & y, conditions),
# ['enter_long', 'enter_tag']
# ] = (1, 'fall')
# ] = (1, 'Force')
return dataframe