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2 Commits
42832df325
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123804b5f3
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123804b5f3 | ||
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f5bf4a4ac1 |
@@ -1,30 +0,0 @@
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from freqtrade.optimize.hyperopt import IHyperOptLoss
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from math import sqrt
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class CustomPerformanceLoss(IHyperOptLoss):
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@staticmethod
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def hyperopt_loss_function(results, trade_count, *args, **kwargs):
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total_profit = results['profit_total_abs']
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max_dd = results['max_drawdown']
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profit_factor = results['profit_factor']
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sqn = results['sqn']
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# Sécurité minimale
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if trade_count < 30:
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return 1000
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# Éviter division par zéro
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if max_dd == 0:
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max_dd = 0.0001
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# Score principal
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performance_score = (
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(profit_factor * sqn * total_profit)
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/ (max_dd ** 1.5)
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)
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# On retourne l'inverse car hyperopt minimise
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return -performance_score
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39
Empty.json
39
Empty.json
@@ -2,7 +2,7 @@
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"strategy_name": "Empty",
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"strategy_name": "Empty",
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"params": {
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"params": {
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"roi": {
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"roi": {
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"0": 10
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"0": 5
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},
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},
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"stoploss": {
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"stoploss": {
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"stoploss": -1.0
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"stoploss": -1.0
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@@ -14,26 +14,33 @@
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"trailing_only_offset_is_reached": false
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"trailing_only_offset_is_reached": false
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},
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},
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"max_open_trades": {
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"max_open_trades": {
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"max_open_trades": 1
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"max_open_trades": 20
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},
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"buy": {
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"buy_deriv1_sma12d": -0.05,
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"buy_deriv1_sma5d": -0.03,
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"buy_deriv1_sma60": 0.0,
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"buy_deriv2_sma12d": 0.0,
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"buy_deriv2_sma5d": -0.07,
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"buy_deriv2_sma60": -0.003,
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"buy_longue": 200
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},
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},
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"protection": {
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"protection": {
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"drop_from_last_entry": 0.0
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"b30_indicateur": "sma36",
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"baisse": 0.33,
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"drop_from_last_entry": -0.03
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},
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"buy": {
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"buy_deriv1_sma12d": -0.04,
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"buy_deriv1_sma5d": -0.02,
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"buy_deriv1_sma60": 0.001,
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"buy_deriv2_sma12d": -0.02,
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"buy_deriv2_sma5d": 0.0,
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"buy_deriv2_sma60": -0.001,
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"buy_longue": 160,
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"buy_longue_derive": "sma80_deriv1_1d",
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"start_bear_deriv1": -0.004,
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"start_bear_deriv2": 0.002,
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"start_bear_indicator": "sma80",
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"start_bull_deriv1": 0.001,
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"start_bull_deriv2": -0.002,
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"start_bull_indicator": "sma120"
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},
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},
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"sell": {
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"sell": {
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"sell_crossed_sma_indicators": "sma60",
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"sell_score_indicator": "sma24_score"
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"sell_score_indicator": "sma60_score",
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"sell_sma_indicators": "sma48_1d"
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}
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}
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},
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},
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"ft_stratparam_v": 1,
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"ft_stratparam_v": 1,
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"export_time": "2026-02-26 20:23:41.717021+00:00"
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"export_time": "2026-02-28 17:28:20.867470+00:00"
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}
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}
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561
Empty.py
561
Empty.py
@@ -39,19 +39,24 @@ timeperiods = [3, 5, 12, 24, 36, 48, 60]
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long_timeperiods = [80, 100, 120, 140, 160, 180, 200]
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long_timeperiods = [80, 100, 120, 140, 160, 180, 200]
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sma_indicators = list()
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sma_indicators = list()
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sma_indicators_h = list()
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sma_indicators_d = list()
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score_indicators = list()
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score_indicators = list()
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stop_buying_indicators = list()
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stop_buying_indicators = list()
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god_genes_with_timeperiod = list()
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sma_deriv1_indicators = list()
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for timeperiod in timeperiods:
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for timeperiod in timeperiods:
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sma_indicators.append(f"sma{timeperiod}")
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sma_indicators.append(f"sma{timeperiod}")
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sma_indicators_h.append(f"sma{timeperiod}")
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sma_indicators_d.append(f"sma{timeperiod}")
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sma_indicators.append(f"sma{timeperiod}_1d")
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sma_indicators.append(f"sma{timeperiod}_1d")
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# god_genes_with_timeperiod.append(f'max{timeperiod}')
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# god_genes_with_timeperiod.append(f'max{timeperiod}')
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# god_genes_with_timeperiod.append(f'min{timeperiod}')
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# god_genes_with_timeperiod.append(f'min{timeperiod}')
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# god_genes_with_timeperiod.append(f"percent{timeperiod}")
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# god_genes_with_timeperiod.append(f"percent{timeperiod}")
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# god_genes_with_timeperiod.append(f"sma{timeperiod}")
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# god_genes_with_timeperiod.append(f"sma{timeperiod}")
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god_genes_with_timeperiod.append(f"sma{timeperiod}_deriv1")
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# sma_deriv1_indicators.append(f"sma{timeperiod}_deriv1")
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god_genes_with_timeperiod.append(f"sma{timeperiod}_deriv2")
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sma_deriv1_indicators.append(f"sma{timeperiod}_deriv1")
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god_genes_with_timeperiod.append(f"sma{timeperiod}_score")
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# sma_deriv1_indicators.append(f"sma{timeperiod}_deriv2")
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# sma_deriv1_indicators.append(f"sma{timeperiod}_score")
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# stoploss_indicators.append(f"stop_buying{timeperiod}")
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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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stop_buying_indicators.append(f"stop_buying{timeperiod}_1d")
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@@ -63,29 +68,10 @@ for timeperiod in timeperiods:
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# god_genes_with_timeperiod.append(f"sma{timeperiod}_trend_down")
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# god_genes_with_timeperiod.append(f"sma{timeperiod}_trend_down")
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# god_genes_with_timeperiod.append(f"sma{timeperiod}_trend_change_up")
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# god_genes_with_timeperiod.append(f"sma{timeperiod}_trend_change_up")
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# god_genes_with_timeperiod.append(f"sma{timeperiod}_trend_change_down")
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# god_genes_with_timeperiod.append(f"sma{timeperiod}_trend_change_down")
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for timeperiod in long_timeperiods:
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sma_deriv1_indicators.append(f"sma{timeperiod}_deriv1_1d")
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sma_indicators_d.append(f"sma{timeperiod}")
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operators = [
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"D", # Disabled gene
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">", # Indicator, bigger than cross indicator
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"<", # Indicator, smaller than cross indicator
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"=", # Indicator, equal with cross indicator
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"C", # Indicator, crossed the cross indicator
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"CA", # Indicator, crossed above the cross indicator
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"CB", # Indicator, crossed below the cross indicator
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# ">R", # Normalized indicator, bigger than real number
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# "=R", # Normalized indicator, equal with real number
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# "<R", # Normalized indicator, smaller than real number
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# "/>R", # Normalized indicator devided to cross indicator, bigger than real number
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# "/=R", # Normalized indicator devided to cross indicator, equal with real number
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# "/<R", # Normalized indicator devided to cross indicator, smaller than real number
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# "UT", # Indicator, is in UpTrend status
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# "DT", # Indicator, is in DownTrend status
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# "OT", # Indicator, is in Off trend status(RANGE)
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# "CUT", # Indicator, Entered to UpTrend status
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# "CDT", # Indicator, Entered to DownTrend status
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# "COT" # Indicator, Entered to Off trend status(RANGE)
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]
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# number of candles to check up,don,off trend.
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# number of candles to check up,don,off trend.
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TREND_CHECK_CANDLES = 4
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TREND_CHECK_CANDLES = 4
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DECIMALS = 1
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DECIMALS = 1
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@@ -94,169 +80,6 @@ def normalize(df):
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df = (df-df.min())/(df.max()-df.min())
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df = (df-df.min())/(df.max()-df.min())
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return df
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return df
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def gene_calculator(dataframe, indicator):
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# print(indicator)
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# Cuz Timeperiods not effect calculating CDL patterns recognations
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if 'CDL' in indicator:
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splited_indicator = indicator.split('-')
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splited_indicator[1] = "0"
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new_indicator = "-".join(splited_indicator)
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# print(indicator, new_indicator)
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indicator = new_indicator
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gene = indicator.split("-")
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gene_name = gene[0]
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gene_len = len(gene)
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# print(f"GENE {gene_name} {gene_len} {indicator}")
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if gene_name in dataframe.keys():
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# print(f"{indicator}, calculated befoure")
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# print(len(dataframe.keys()))
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return dataframe[gene_name]
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if indicator in dataframe.keys():
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# print(f"{indicator}, calculated befoure")
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# print(len(dataframe.keys()))
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return dataframe[indicator]
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else:
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result = None
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# For Pattern Recognations
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if gene_len == 1:
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# print('gene_len == 1\t', indicator)
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result = getattr(talib, gene_name)(
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dataframe
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)
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return normalize(result)
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elif gene_len == 2:
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# print('gene_len == 2\t', indicator)
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gene_timeperiod = int(gene[1])
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result = getattr(talib, gene_name)(
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dataframe,
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timeperiod=gene_timeperiod,
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)
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return normalize(result)
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# For
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elif gene_len == 3:
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# print('gene_len == 3\t', indicator)
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gene_timeperiod = int(gene[2])
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gene_index = int(gene[1])
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result = getattr(talib, gene_name)(
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dataframe,
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timeperiod=gene_timeperiod,
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).iloc[:, gene_index]
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return normalize(result)
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# For trend operators(MA-5-SMA-4)
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elif gene_len == 4:
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# print('gene_len == 4\t', indicator)
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gene_timeperiod = int(gene[1])
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sharp_indicator = f'{gene_name}-{gene_timeperiod}'
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dataframe[sharp_indicator] = getattr(talib, gene_name)(
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dataframe,
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timeperiod=gene_timeperiod,
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)
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return normalize(talib.SMA(dataframe[sharp_indicator].fillna(0), TREND_CHECK_CANDLES))
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# For trend operators(STOCH-0-4-SMA-4)
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elif gene_len == 5:
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# print('gene_len == 5\t', indicator)
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gene_timeperiod = int(gene[2])
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gene_index = int(gene[1])
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sharp_indicator = f'{gene_name}-{gene_index}-{gene_timeperiod}'
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dataframe[sharp_indicator] = getattr(talib, gene_name)(
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dataframe,
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timeperiod=gene_timeperiod,
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).iloc[:, gene_index]
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return normalize(talib.SMA(dataframe[sharp_indicator].fillna(0), TREND_CHECK_CANDLES))
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def condition_generator(dataframe, operator, indicator, crossed_indicator, real_num):
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condition = (dataframe['volume'] > 10)
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# TODO : it ill callculated in populate indicators.
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pd.set_option('display.max_rows', None)
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pd.set_option('display.max_columns', None)
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pd.set_option("display.width", 200)
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# print(f"{indicator} {crossed_indicator} {real_num}")
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dataframe[indicator] = gene_calculator(dataframe, indicator)
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dataframe[crossed_indicator] = gene_calculator(dataframe, crossed_indicator)
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indicator_trend_sma = f"{indicator}-SMA-{TREND_CHECK_CANDLES}"
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if operator in ["UT", "DT", "OT", "CUT", "CDT", "COT"]:
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dataframe[indicator_trend_sma] = gene_calculator(dataframe, indicator_trend_sma)
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if operator == ">":
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condition = (dataframe[indicator] > dataframe[crossed_indicator])
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elif operator == "=":
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condition = (np.isclose(dataframe[indicator], dataframe[crossed_indicator]))
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elif operator == "<":
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condition = (dataframe[indicator] < dataframe[crossed_indicator])
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elif operator == "C":
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condition = (
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(qtpylib.crossed_below(dataframe[indicator], dataframe[crossed_indicator])) |
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(qtpylib.crossed_above(
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dataframe[indicator], dataframe[crossed_indicator]))
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)
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elif operator == "CA":
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condition = (qtpylib.crossed_above(dataframe[indicator], dataframe[crossed_indicator]))
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elif operator == "CB":
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condition = (qtpylib.crossed_below(dataframe[indicator], dataframe[crossed_indicator]))
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elif operator == ">R":
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condition = (dataframe[indicator] > real_num)
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elif operator == "=R":
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condition = (np.isclose(dataframe[indicator], real_num))
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elif operator == "<R":
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condition = (dataframe[indicator] < real_num)
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elif operator == "/>R":
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condition = (dataframe[indicator].div(dataframe[crossed_indicator]) > real_num)
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elif operator == "/=R":
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condition = (np.isclose(dataframe[indicator].div(dataframe[crossed_indicator]), real_num))
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elif operator == "/<R":
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condition = (dataframe[indicator].div(dataframe[crossed_indicator]) < real_num)
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elif operator == "UT":
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condition = (dataframe[indicator] > dataframe[indicator_trend_sma])
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elif operator == "DT":
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condition = (dataframe[indicator] < dataframe[indicator_trend_sma])
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elif operator == "OT":
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condition = (np.isclose(dataframe[indicator], dataframe[indicator_trend_sma]))
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elif operator == "CUT":
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condition = (
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(
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qtpylib.crossed_above(dataframe[indicator],dataframe[indicator_trend_sma])
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) & (
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dataframe[indicator] > dataframe[indicator_trend_sma]
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)
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)
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elif operator == "CDT":
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condition = (
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(
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qtpylib.crossed_below(dataframe[indicator], dataframe[indicator_trend_sma])
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) &
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(
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dataframe[indicator] < dataframe[indicator_trend_sma]
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)
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)
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elif operator == "COT":
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condition = (
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(
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(
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qtpylib.crossed_below(dataframe[indicator], dataframe[indicator_trend_sma])
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) |
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(
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qtpylib.crossed_above(dataframe[indicator], dataframe[indicator_trend_sma])
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)
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) &
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(
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np.isclose(dataframe[indicator], dataframe[indicator_trend_sma])
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)
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)
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return condition, dataframe
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# #########################################################################################################################
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# This class is a sample. Feel free to customize it.
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# This class is a sample. Feel free to customize it.
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||||||
class Empty(IStrategy):
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class Empty(IStrategy):
|
||||||
|
|
||||||
@@ -364,6 +187,14 @@ class Empty(IStrategy):
|
|||||||
}
|
}
|
||||||
}
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}
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||||||
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||||||
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start_bull_indicator = CategoricalParameter(sma_indicators_d, default='sma100', space='buy', optimize=True, load=True)
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||||||
|
start_bull_deriv1 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy', optimize=True, load=True)
|
||||||
|
start_bull_deriv2 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy', optimize=True, load=True)
|
||||||
|
|
||||||
|
start_bear_indicator = CategoricalParameter(sma_indicators_d, default='sma100', space='buy', optimize=True, load=True)
|
||||||
|
start_bear_deriv1 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy', optimize=True, load=True)
|
||||||
|
start_bear_deriv2 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy', optimize=True, load=True)
|
||||||
|
|
||||||
buy_deriv1_sma60 = DecimalParameter(-0.005, 0.005, decimals=3, default=0, space='buy', optimize=False, load=True)
|
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_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_deriv1_sma12d = DecimalParameter(-0.07, 0.07, decimals=2, default=0, space='buy', optimize=False, load=True)
|
||||||
@@ -372,48 +203,24 @@ class Empty(IStrategy):
|
|||||||
buy_deriv2_sma5d = DecimalParameter(-0.07, 0.07, decimals=2, 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_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_longue = CategoricalParameter(long_timeperiods, default=120, space='buy', optimize=False, load=True)
|
||||||
|
buy_longue_derive = CategoricalParameter(sma_deriv1_indicators, default="sma60_deriv1_1d", space='buy', optimize=False, load=True)
|
||||||
# Buy Hyperoptable Parameters/Spaces.
|
|
||||||
# buy_crossed_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="ADD-20", space='buy')
|
|
||||||
# buy_crossed_indicator1 = CategoricalParameter(god_genes_with_timeperiod, default="ASIN-6", space='buy')
|
|
||||||
# buy_crossed_indicator2 = CategoricalParameter(god_genes_with_timeperiod, default="CDLEVENINGSTAR-50", space='buy')
|
|
||||||
#
|
|
||||||
# buy_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="SMA-100", space='buy')
|
|
||||||
# buy_indicator1 = CategoricalParameter(god_genes_with_timeperiod, default="WILLR-50", space='buy')
|
|
||||||
# buy_indicator2 = CategoricalParameter(god_genes_with_timeperiod, default="CDLHANGINGMAN-20", space='buy')
|
|
||||||
#
|
|
||||||
# buy_operator0 = CategoricalParameter(operators, default="/<R", space='buy')
|
|
||||||
# buy_operator1 = CategoricalParameter(operators, default="<R", space='buy')
|
|
||||||
# buy_operator2 = CategoricalParameter(operators, default="CB", space='buy')
|
|
||||||
#
|
|
||||||
# buy_real_num0 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='buy')
|
|
||||||
# buy_real_num1 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='buy')
|
|
||||||
# buy_real_num2 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='buy')
|
|
||||||
|
|
||||||
# Sell Hyperoptable Parameters/Spaces.
|
|
||||||
# sell_crossed_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="CDLSHOOTINGSTAR-150", space='sell')
|
|
||||||
# sell_crossed_indicator1 = CategoricalParameter(god_genes_with_timeperiod, default="MAMA-1-100", space='sell')
|
|
||||||
# sell_crossed_indicator2 = CategoricalParameter(god_genes_with_timeperiod, default="CDLMATHOLD-6", space='sell')
|
|
||||||
#
|
|
||||||
# sell_indicator0 = CategoricalParameter(god_genes_with_timeperiod, default="CDLUPSIDEGAP2CROWS-5", space='sell')
|
|
||||||
# sell_indicator1 = CategoricalParameter(god_genes_with_timeperiod, default="CDLHARAMICROSS-150", space='sell')
|
|
||||||
# sell_indicator2 = CategoricalParameter(god_genes_with_timeperiod, default="CDL2CROWS-5", space='sell')
|
|
||||||
#
|
|
||||||
# sell_operator0 = CategoricalParameter(operators, default="<R", space='sell')
|
|
||||||
# sell_operator1 = CategoricalParameter(operators, default="D", space='sell')
|
|
||||||
# sell_operator2 = CategoricalParameter(operators, default="/>R", space='sell')
|
|
||||||
#
|
|
||||||
# sell_real_num0 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='sell')
|
|
||||||
# sell_real_num1 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='sell')
|
|
||||||
# sell_real_num2 = DecimalParameter(-1, 1, decimals=DECIMALS, default=0, space='sell')
|
|
||||||
|
|
||||||
sell_score_indicator = CategoricalParameter(score_indicators, default="sma24_score", space='sell')
|
sell_score_indicator = CategoricalParameter(score_indicators, default="sma24_score", space='sell')
|
||||||
|
|
||||||
sell_sma_indicators = CategoricalParameter(sma_indicators, default="sma24_score", space='sell')
|
# sell_sma_indicators = CategoricalParameter(sma_indicators, default="sma24_score", space='sell')
|
||||||
sell_crossed_sma_indicators = CategoricalParameter(sma_indicators, default="sma24_score", space='sell')
|
# sell_crossed_sma_indicators = CategoricalParameter(sma_indicators, default="sma24_score", space='sell')
|
||||||
|
|
||||||
|
drop_from_last_entry = DecimalParameter(-0.1, 0, decimals=2, default=-0.025, space='protection', optimize=False, load=True)
|
||||||
|
|
||||||
|
# baisses = list()
|
||||||
|
# for i in range(0, 0.5, 0.05):
|
||||||
|
# baisses.append(i)
|
||||||
|
baisse = DecimalParameter(0, 0.5, decimals=2, default=0.3, space='protection', optimize=True, load=True)
|
||||||
|
b30_indicateur = CategoricalParameter(sma_indicators_h, default="sma36", space='protection', optimize=True, load=True)
|
||||||
|
|
||||||
|
# lost_indicator = CategoricalParameter(sma_deriv1_indicators, default="sma5_deriv1", space='protection')
|
||||||
|
|
||||||
drop_from_last_entry = DecimalParameter(-0.1, 0, decimals=2, default=-0.025, space='protection')
|
|
||||||
# range_pos_stoploss = DecimalParameter(0, 0.1, decimals=2, default=0.05, space='protection')
|
# range_pos_stoploss = DecimalParameter(0, 0.1, decimals=2, default=0.05, space='protection')
|
||||||
# stoploss_force = DecimalParameter(-0.2, 0, decimals=2, default=-0.05, space='protection')
|
# stoploss_force = DecimalParameter(-0.2, 0, decimals=2, default=-0.05, space='protection')
|
||||||
|
|
||||||
@@ -438,12 +245,23 @@ class Empty(IStrategy):
|
|||||||
#
|
#
|
||||||
# range_pos = (last_candle['close'] - range_min) / (range_max - range_min)
|
# range_pos = (last_candle['close'] - range_min) / (range_max - range_min)
|
||||||
|
|
||||||
range_pos = last_candle[f"range_pos"]
|
# range_pos = last_candle[f"range_pos"]
|
||||||
sl_min = self.wallets.get_available_stake_amount() / 6
|
# sl_min = self.wallets.get_available_stake_amount() / 6
|
||||||
sl_max = self.wallets.get_available_stake_amount() / 2
|
# sl_max = self.wallets.get_available_stake_amount() / 2
|
||||||
|
#
|
||||||
|
# amount = sl_min + (1 - range_pos) * (sl_max - sl_min)
|
||||||
|
if last_candle['enter_tag'] == 'fall':
|
||||||
|
amount = self.wallets.get_available_stake_amount() / 5
|
||||||
|
else:
|
||||||
|
amount = self.wallets.get_available_stake_amount() # / (2 * self.pairs[pair]['count_of_lost'] + 1)
|
||||||
|
|
||||||
amount = sl_min + (1 - range_pos) * (sl_max - sl_min)
|
# factor = 1
|
||||||
amount = self.wallets.get_available_stake_amount()
|
#
|
||||||
|
# if self.pairs[pair]['last_trade'] is not None \
|
||||||
|
# and self.pairs[pair]['last_trade'].close_profit is not None \
|
||||||
|
# and self.pairs[pair]['last_trade'].close_profit > 0.01:
|
||||||
|
# factor = self.pairs[pair]['last_trade'].close_profit / 0.01
|
||||||
|
# amount = amount / factor
|
||||||
|
|
||||||
return min(amount, self.wallets.get_available_stake_amount())
|
return min(amount, self.wallets.get_available_stake_amount())
|
||||||
|
|
||||||
@@ -546,6 +364,9 @@ class Empty(IStrategy):
|
|||||||
last_candle_2 = dataframe.iloc[-2].squeeze()
|
last_candle_2 = dataframe.iloc[-2].squeeze()
|
||||||
last_candle_3 = dataframe.iloc[-3].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 \
|
condition = False if self.pairs[pair]['count_of_lost'] >= 1 \
|
||||||
and (last_candle['sma12_deriv1_1d'] < 0.001 \
|
and (last_candle['sma12_deriv1_1d'] < 0.001 \
|
||||||
or last_candle['sma12_deriv2_1d'] < 0.001) else True
|
or last_candle['sma12_deriv2_1d'] < 0.001) else True
|
||||||
@@ -619,19 +440,19 @@ class Empty(IStrategy):
|
|||||||
buys=1,
|
buys=1,
|
||||||
stake=round(stake_amount, 2)
|
stake=round(stake_amount, 2)
|
||||||
)
|
)
|
||||||
else:
|
# else:
|
||||||
self.log_trade(
|
# self.log_trade(
|
||||||
last_candle=last_candle,
|
# last_candle=last_candle,
|
||||||
date=current_time,
|
# date=current_time,
|
||||||
action=("🟩Buy" if allow_to_buy else "Canceled") + " " + reason,
|
# action=("🟩Buy" if allow_to_buy else "Canceled") + " " + reason,
|
||||||
pair=pair,
|
# pair=pair,
|
||||||
rate=rate,
|
# rate=rate,
|
||||||
dispo=dispo,
|
# dispo=dispo,
|
||||||
profit=0,
|
# profit=0,
|
||||||
trade_type=entry_tag,
|
# trade_type=entry_tag,
|
||||||
buys=1,
|
# buys=1,
|
||||||
stake=0
|
# stake=0
|
||||||
)
|
# )
|
||||||
return allow_to_buy
|
return allow_to_buy
|
||||||
|
|
||||||
def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float, rate: float,
|
def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float, rate: float,
|
||||||
@@ -701,6 +522,8 @@ class Empty(IStrategy):
|
|||||||
self.pairs[pair]['max_profit'] = max(self.pairs[pair]['max_profit'], profit)
|
self.pairs[pair]['max_profit'] = max(self.pairs[pair]['max_profit'], profit)
|
||||||
max_profit = self.pairs[pair]['max_profit']
|
max_profit = self.pairs[pair]['max_profit']
|
||||||
|
|
||||||
|
# baisse_min = last_candle['close'] - last_candle['min12']
|
||||||
|
|
||||||
baisse = 0
|
baisse = 0
|
||||||
if profit > 0:
|
if profit > 0:
|
||||||
baisse = 1 - (profit / max_profit)
|
baisse = 1 - (profit / max_profit)
|
||||||
@@ -722,19 +545,19 @@ class Empty(IStrategy):
|
|||||||
# buys=count_of_buys,
|
# buys=count_of_buys,
|
||||||
# stake=0
|
# stake=0
|
||||||
# )
|
# )
|
||||||
|
# if self.pairs[pair]['current_trade'].enter_tag == 'fall':
|
||||||
|
# if current_profit < - 0.02 and last_candle[f"close"] <= last_candle['sma60'] and self.wallets.get_available_stake_amount() < 50:
|
||||||
|
# self.pairs[pair]['force_sell'] = True
|
||||||
|
# return 'sma60'
|
||||||
|
# else:
|
||||||
|
|
||||||
if current_profit < - 0.02 and last_candle[f"close"] <= last_candle['sma60']:
|
if current_profit < - 0.02 and last_candle[f"close"] <= last_candle['sma60']:
|
||||||
self.pairs[pair]['force_sell'] = True
|
self.pairs[pair]['force_sell'] = True
|
||||||
return 'sma60'
|
return 'sma60'
|
||||||
|
|
||||||
cross = qtpylib.crossed_below(dataframe[self.sell_sma_indicators.value], dataframe[self.sell_crossed_sma_indicators.value])
|
if profit > max(5, expected_profit) and \
|
||||||
|
(baisse > self.baisse.value and last_candle[f"close"] <= last_candle[self.b30_indicateur.value]) \
|
||||||
# if profit > 0 and cross.iloc[-1]:
|
and last_candle['hapercent'] <0 :
|
||||||
# self.pairs[pair]['force_sell'] = True
|
|
||||||
# return 'Cross'
|
|
||||||
|
|
||||||
if profit > max(5, expected_profit) and baisse > 0.30 and last_candle[f"close"] <= last_candle['sma36']:
|
|
||||||
# and last_candle['percent3'] < 0 and last_candle['percent5'] < 0:
|
|
||||||
self.pairs[pair]['force_sell'] = True
|
self.pairs[pair]['force_sell'] = True
|
||||||
return 'B30'
|
return 'B30'
|
||||||
|
|
||||||
@@ -827,7 +650,9 @@ class Empty(IStrategy):
|
|||||||
dataframe['mid'] = dataframe['haopen'] + (dataframe['haclose'] - dataframe['haopen']) / 2
|
dataframe['mid'] = dataframe['haopen'] + (dataframe['haclose'] - dataframe['haopen']) / 2
|
||||||
dataframe['zero'] = 0
|
dataframe['zero'] = 0
|
||||||
|
|
||||||
|
dataframe[f"percent"] = dataframe['close'].pct_change()
|
||||||
for timeperiod in timeperiods:
|
for timeperiod in timeperiods:
|
||||||
|
dataframe[f"mid_smooth{timeperiod}"] = dataframe['mid'].rolling(timeperiod).mean()
|
||||||
dataframe[f'max{timeperiod}'] = talib.MAX(dataframe['close'], timeperiod=timeperiod)
|
dataframe[f'max{timeperiod}'] = talib.MAX(dataframe['close'], timeperiod=timeperiod)
|
||||||
dataframe[f'min{timeperiod}'] = talib.MIN(dataframe['close'], timeperiod=timeperiod)
|
dataframe[f'min{timeperiod}'] = talib.MIN(dataframe['close'], timeperiod=timeperiod)
|
||||||
dataframe[f"percent{timeperiod}"] = dataframe['close'].pct_change(timeperiod)
|
dataframe[f"percent{timeperiod}"] = dataframe['close'].pct_change(timeperiod)
|
||||||
@@ -853,11 +678,27 @@ class Empty(IStrategy):
|
|||||||
|
|
||||||
for timeperiod in long_timeperiods:
|
for timeperiod in long_timeperiods:
|
||||||
informative[f"sma{timeperiod}"] = informative['mid'].ewm(span=timeperiod, adjust=False).mean()
|
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['rsi'] = talib.RSI(informative['close'], timeperiod=14)
|
informative['rsi'] = talib.RSI(informative['close'], timeperiod=14)
|
||||||
self.calculeDerivees(informative, f"rsi", timeframe=self.timeframe, ema_period=14)
|
self.calculeDerivees(informative, f"rsi", timeframe=self.timeframe, ema_period=14)
|
||||||
informative['max_rsi_12'] = talib.MAX(informative['rsi'], timeperiod=12)
|
informative['max_rsi_12'] = talib.MAX(informative['rsi'], timeperiod=12)
|
||||||
informative['max_rsi_24'] = talib.MAX(informative['rsi'], timeperiod=24)
|
informative['max_rsi_24'] = talib.MAX(informative['rsi'], timeperiod=24)
|
||||||
|
|
||||||
|
informative[f'stop_buying_deb'] = qtpylib.crossed_below(informative[f"sma12"], informative['sma36']) & (informative['close'] < informative['sma100'])
|
||||||
|
informative[f'stop_buying_end'] = qtpylib.crossed_above(informative[f"sma12"], informative['sma36']) & (informative['close'] > informative['sma100'])
|
||||||
|
|
||||||
|
latched = np.zeros(len(informative), dtype=bool)
|
||||||
|
|
||||||
|
for i in range(1, len(informative)):
|
||||||
|
if informative['stop_buying_deb'].iloc[i]:
|
||||||
|
latched[i] = True
|
||||||
|
elif informative['stop_buying_end'].iloc[i]:
|
||||||
|
latched[i] = False
|
||||||
|
else:
|
||||||
|
latched[i] = latched[i - 1]
|
||||||
|
informative['stop_buying'] = latched
|
||||||
|
|
||||||
dataframe = merge_informative_pair(dataframe, informative, self.timeframe, "1d", ffill=True)
|
dataframe = merge_informative_pair(dataframe, informative, self.timeframe, "1d", ffill=True)
|
||||||
# ######################################################################################################
|
# ######################################################################################################
|
||||||
|
|
||||||
@@ -868,7 +709,8 @@ class Empty(IStrategy):
|
|||||||
|
|
||||||
# dataframe['cross_sma60'] = qtpylib.crossed_below(dataframe[self.sell_sma_indicators.value], dataframe[self.sell_crossed_sma_indicators.value])
|
# dataframe['cross_sma60'] = qtpylib.crossed_below(dataframe[self.sell_sma_indicators.value], dataframe[self.sell_crossed_sma_indicators.value])
|
||||||
|
|
||||||
dataframe[f'stop_buying'] = qtpylib.crossed_below(dataframe[f"sma12"], dataframe['sma48'])
|
dataframe[f'has_cross_min'] = qtpylib.crossed_above(dataframe[f"close"], dataframe['min60_1d'])
|
||||||
|
dataframe[f'has_cross_min_6'] = (dataframe['has_cross_min'].rolling(6).max() == 1)
|
||||||
|
|
||||||
dataframe['atr'] = talib.ATR(dataframe)
|
dataframe['atr'] = talib.ATR(dataframe)
|
||||||
dataframe['rsi'] = talib.RSI(dataframe['close'], timeperiod=14)
|
dataframe['rsi'] = talib.RSI(dataframe['close'], timeperiod=14)
|
||||||
@@ -891,62 +733,13 @@ class Empty(IStrategy):
|
|||||||
|
|
||||||
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||||
|
|
||||||
# dataframe.loc[
|
|
||||||
# (
|
|
||||||
# (dataframe['sma24_score'].shift(2) <= dataframe['zero'])
|
|
||||||
# & (dataframe['sma5'].shift(1) <= dataframe['sma5'])
|
|
||||||
# & (dataframe['sma5_inv'] == -1)
|
|
||||||
# & (dataframe['min24'].shift(3) == dataframe['min24'])
|
|
||||||
# ),
|
|
||||||
# 'buy'] = 1
|
|
||||||
|
|
||||||
conditions = list()
|
conditions = list()
|
||||||
|
|
||||||
# # print(dataframe.columns)
|
# #####################################################################################
|
||||||
#
|
# CA MONTE !!
|
||||||
# buy_indicator = self.buy_indicator0.value
|
# #####################################################################################
|
||||||
# buy_crossed_indicator = self.buy_crossed_indicator0.value
|
# conditions.append(dataframe[f"{self.start_bull_indicator.value}_deriv1_1d" ] > self.start_bull_deriv1.value)
|
||||||
# buy_operator = self.buy_operator0.value
|
# conditions.append(dataframe[f"{self.start_bull_indicator.value}_deriv2_1d"] > self.start_bull_deriv2.value)
|
||||||
# buy_real_num = self.buy_real_num0.value
|
|
||||||
# condition, dataframe = condition_generator(
|
|
||||||
# dataframe,
|
|
||||||
# buy_operator,
|
|
||||||
# buy_indicator,
|
|
||||||
# buy_crossed_indicator,
|
|
||||||
# buy_real_num
|
|
||||||
# )
|
|
||||||
# conditions.append(condition)
|
|
||||||
# # backup
|
|
||||||
# buy_indicator = self.buy_indicator1.value
|
|
||||||
# buy_crossed_indicator = self.buy_crossed_indicator1.value
|
|
||||||
# buy_operator = self.buy_operator1.value
|
|
||||||
# buy_real_num = self.buy_real_num1.value
|
|
||||||
#
|
|
||||||
# condition, dataframe = condition_generator(
|
|
||||||
# dataframe,
|
|
||||||
# buy_operator,
|
|
||||||
# buy_indicator,
|
|
||||||
# buy_crossed_indicator,
|
|
||||||
# buy_real_num
|
|
||||||
# )
|
|
||||||
# conditions.append(condition)
|
|
||||||
#
|
|
||||||
# buy_indicator = self.buy_indicator2.value
|
|
||||||
# buy_crossed_indicator = self.buy_crossed_indicator2.value
|
|
||||||
# buy_operator = self.buy_operator2.value
|
|
||||||
# buy_real_num = self.buy_real_num2.value
|
|
||||||
# condition, dataframe = condition_generator(
|
|
||||||
# dataframe,
|
|
||||||
# buy_operator,
|
|
||||||
# buy_indicator,
|
|
||||||
# buy_crossed_indicator,
|
|
||||||
# buy_real_num
|
|
||||||
# )
|
|
||||||
# conditions.append(condition)
|
|
||||||
# conditions.append((dataframe[self.stop_buying_indicator.value] == False) | (dataframe['range_pos'] < 0))
|
|
||||||
|
|
||||||
#conditions.append((dataframe[self.stop_buying_indicator.value] == False) | (dataframe['range_pos'] < 0))
|
|
||||||
|
|
||||||
conditions.append(dataframe['sma12_deriv1'] > self.buy_deriv1_sma60.value)
|
conditions.append(dataframe['sma12_deriv1'] > self.buy_deriv1_sma60.value)
|
||||||
conditions.append(dataframe['sma5_deriv1_1d'] > self.buy_deriv1_sma5d.value)
|
conditions.append(dataframe['sma5_deriv1_1d'] > self.buy_deriv1_sma5d.value)
|
||||||
conditions.append(dataframe['sma12_deriv1_1d'] > self.buy_deriv1_sma12d.value)
|
conditions.append(dataframe['sma12_deriv1_1d'] > self.buy_deriv1_sma12d.value)
|
||||||
@@ -962,11 +755,6 @@ class Empty(IStrategy):
|
|||||||
|
|
||||||
dynamic_rsi_threshold = 70 + 15 * np.tanh(dataframe["dist_sma200_1d"] * 5)
|
dynamic_rsi_threshold = 70 + 15 * np.tanh(dataframe["dist_sma200_1d"] * 5)
|
||||||
conditions.append((dataframe['max_rsi_12_1d'] < dynamic_rsi_threshold))
|
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))
|
|
||||||
# )
|
|
||||||
|
|
||||||
conditions.append(dataframe[f"close"] > dataframe['sma60'])
|
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[f"range_pos"] < 0.05) ) | ((dataframe['sma12_deriv1'] > 0) & (dataframe['sma12_deriv2'] > 0)))
|
||||||
|
|
||||||
@@ -975,17 +763,84 @@ class Empty(IStrategy):
|
|||||||
| (dataframe['sma60_inv_1d'] == -1)
|
| (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"
|
|
||||||
# f"{self.buy_indicator1.value} {self.buy_crossed_indicator1.value} {self.buy_operator1.value} {self.buy_real_num1.value} \n"
|
|
||||||
# f"{self.buy_indicator2.value} {self.buy_crossed_indicator2.value} {self.buy_operator2.value} {self.buy_real_num2.value} \n"
|
|
||||||
# )
|
|
||||||
|
|
||||||
if conditions:
|
if conditions:
|
||||||
dataframe.loc[
|
dataframe.loc[
|
||||||
reduce(lambda x, y: x & y, conditions),
|
reduce(lambda x, y: x & y, conditions),
|
||||||
['enter_long', 'enter_tag']
|
['enter_long', 'enter_tag']
|
||||||
] = (1, 'god')
|
] = (1, 'bull')
|
||||||
|
|
||||||
|
# #####################################################################################
|
||||||
|
# CA BAISSE !!
|
||||||
|
# "buy": {
|
||||||
|
# "buy_deriv1_sma12d": 0.0,
|
||||||
|
# "buy_deriv1_sma5d": 0.0,
|
||||||
|
# "buy_deriv1_sma60": 0.003,
|
||||||
|
# "buy_deriv2_sma12d": -0.03,
|
||||||
|
# "buy_deriv2_sma5d": 0.0,
|
||||||
|
# "buy_deriv2_sma60": -0.002,
|
||||||
|
# "buy_longue": 200,
|
||||||
|
# "buy_longue_derive": "sma160_deriv1_1d"
|
||||||
|
# },
|
||||||
|
# "protection": {
|
||||||
|
# "drop_from_last_entry": -0.03,
|
||||||
|
# "b30_indicateur": "sma3",
|
||||||
|
# "baisse": 0.31
|
||||||
|
# },
|
||||||
|
# #####################################################################################
|
||||||
|
conditions = list()
|
||||||
|
conditions.append(dataframe[f"{self.start_bear_indicator.value}_deriv1_1d" ] < self.start_bear_deriv1.value)
|
||||||
|
conditions.append(dataframe[f"{self.start_bear_indicator.value}_deriv2_1d"] < self.start_bear_deriv2.value)
|
||||||
|
|
||||||
|
conditions.append(dataframe['sma12_deriv1'] > 0.003)
|
||||||
|
conditions.append(dataframe['sma5_deriv1_1d'] > 0.0)
|
||||||
|
conditions.append(dataframe['sma12_deriv1_1d'] > 0.0)
|
||||||
|
|
||||||
|
conditions.append(dataframe['sma12_deriv2'] > -0.002)
|
||||||
|
conditions.append(dataframe['sma5_deriv2_1d'] > 0)
|
||||||
|
conditions.append(dataframe['sma12_deriv2_1d'] > -0.03)
|
||||||
|
|
||||||
|
conditions.append(dataframe['hapercent'] > 0)
|
||||||
|
# conditions.append(dataframe['percent12'] < 0.01)
|
||||||
|
# conditions.append(dataframe['percent5'] < 0.01)
|
||||||
|
conditions.append(dataframe['max_rsi_24'] < 80)
|
||||||
|
|
||||||
|
dynamic_rsi_threshold = 70 + 15 * np.tanh(dataframe["dist_sma200_1d"] * 5)
|
||||||
|
conditions.append((dataframe['max_rsi_12_1d'] < dynamic_rsi_threshold))
|
||||||
|
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[f'sma{self.buy_longue.value}_1d'])
|
||||||
|
| (dataframe['sma60_inv_1d'] == -1)
|
||||||
|
)
|
||||||
|
|
||||||
|
# if conditions:
|
||||||
|
# dataframe.loc[
|
||||||
|
# reduce(lambda x, y: x & y, conditions),
|
||||||
|
# ['enter_long', 'enter_tag']
|
||||||
|
# ] = (1, 'bear')
|
||||||
|
|
||||||
|
# conditions = list()
|
||||||
|
# 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['hapercent'] > 0)
|
||||||
|
# conditions.append(dataframe['percent5'] < 0.01)
|
||||||
|
# dataframe.loc[
|
||||||
|
# reduce(lambda x, y: x & y, conditions),
|
||||||
|
# ['enter_long', 'enter_tag']
|
||||||
|
# ] = (1, 'cross_min')
|
||||||
|
|
||||||
|
# conditions = list()
|
||||||
|
# # 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, 'fall')
|
||||||
|
|
||||||
return dataframe
|
return dataframe
|
||||||
|
|
||||||
@@ -1087,35 +942,35 @@ class Empty(IStrategy):
|
|||||||
|
|
||||||
# ####################################################################
|
# ####################################################################
|
||||||
# Calcul de la pente lissée
|
# Calcul de la pente lissée
|
||||||
d1 = series.diff()
|
# d1 = series.diff()
|
||||||
d1_smooth = d1.rolling(5).mean()
|
# d1_smooth = d1.rolling(5).mean()
|
||||||
# Normalisation
|
# # Normalisation
|
||||||
z = (d1_smooth - d1_smooth.rolling(ema_period).mean()) / d1_smooth.rolling(ema_period).std()
|
# z = (d1_smooth - d1_smooth.rolling(ema_period).mean()) / d1_smooth.rolling(ema_period).std()
|
||||||
|
|
||||||
dataframe[f"{name}{suffixe}_trend_up"] = (
|
# dataframe[f"{name}{suffixe}_trend_up"] = (
|
||||||
(d1_smooth.shift(1) < 0) &
|
# (d1_smooth.shift(1) < 0) &
|
||||||
(d1_smooth > 0) &
|
# (d1_smooth > 0) &
|
||||||
(z > 1.0)
|
# (z > 1.0)
|
||||||
)
|
# )
|
||||||
|
#
|
||||||
dataframe[f"{name}{suffixe}_trend_down"] = (
|
# dataframe[f"{name}{suffixe}_trend_down"] = (
|
||||||
(d1_smooth.shift(1) > 0) &
|
# (d1_smooth.shift(1) > 0) &
|
||||||
(d1_smooth < 0) &
|
# (d1_smooth < 0) &
|
||||||
(z < -1.0)
|
# (z < -1.0)
|
||||||
)
|
# )
|
||||||
|
#
|
||||||
momentum_short = d1.rolling(int(ema_period / 2)).mean()
|
# momentum_short = d1.rolling(int(ema_period / 2)).mean()
|
||||||
momentum_long = d1.rolling(ema_period * 2).mean()
|
# momentum_long = d1.rolling(ema_period * 2).mean()
|
||||||
|
#
|
||||||
dataframe[f"{name}{suffixe}_trend_change_up"] = (
|
# dataframe[f"{name}{suffixe}_trend_change_up"] = (
|
||||||
(momentum_short.shift(1) < momentum_long.shift(1)) &
|
# (momentum_short.shift(1) < momentum_long.shift(1)) &
|
||||||
(momentum_short > momentum_long)
|
# (momentum_short > momentum_long)
|
||||||
)
|
# )
|
||||||
|
#
|
||||||
dataframe[f"{name}{suffixe}_trend_change_down"] = (
|
# dataframe[f"{name}{suffixe}_trend_change_down"] = (
|
||||||
(momentum_short.shift(1) > momentum_long.shift(1)) &
|
# (momentum_short.shift(1) > momentum_long.shift(1)) &
|
||||||
(momentum_short < momentum_long)
|
# (momentum_short < momentum_long)
|
||||||
)
|
# )
|
||||||
|
|
||||||
return dataframe
|
return dataframe
|
||||||
|
|
||||||
@@ -1290,4 +1145,12 @@ class Empty(IStrategy):
|
|||||||
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)
|
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
|
self.pairs[pair]['expected_profit'] = expected_profit
|
||||||
return expected_profit
|
return expected_profit
|
||||||
|
|
||||||
|
def getLastClosedTrade(self):
|
||||||
|
# récupérer le dernier trade fermé
|
||||||
|
trades = Trade.get_trades_proxy(pair=pair,is_open=False)
|
||||||
|
if trades:
|
||||||
|
last_trade = trades[-1]
|
||||||
|
self.pairs[pair]['last_profit'] = last_trade.close_profit # ex: 0.12 = +12%
|
||||||
|
self.pairs[pair]['last_trade'] = last_trade
|
||||||
278
Empty.txt
278
Empty.txt
@@ -232,3 +232,281 @@ Backtested 2022-01-01 00:00:00 -> 2026-02-20 00:00:00 | Max open trades : 1
|
|||||||
┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩
|
┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩
|
||||||
│ Empty │ 92 │ 1.62 │ 2474.507 │ 247.45 │ 3 days, 23:07:00 │ 45 0 47 48.9 │ 359.078 USDT 10.66% │
|
│ Empty │ 92 │ 1.62 │ 2474.507 │ 247.45 │ 3 days, 23:07:00 │ 45 0 47 48.9 │ 359.078 USDT 10.66% │
|
||||||
└──────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┴──────────────────────┘
|
└──────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┴──────────────────────┘
|
||||||
|
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2023-01-10 17:00 |🟩Buy 0 | BTC | bull | 17302.55| 1000 | 0/0| - | 17302.15 | - | 17302 | 17302 | 1/1| 1000.0
|
||||||
|
| 2023-02-09 22:00 |🟥Sell 43500 | BTC | B30 | 21856.3| - |260.9/395.52| 0.263 | 17302.15 | 0.263 | 17302 | 17302 | /1| -
|
||||||
|
| 2023-02-15 00:00 |🟩Buy 7320 | BTC | bull | 22199.84| 1261 | 0/0| - | 22199.84 | - | 22199 | 17302 | 1/1| 1260.9
|
||||||
|
| 2023-02-16 23:00 |🟥Sell 2820 | BTC | B30 | 23994.76| - |99.31/160.46| 0.081 | 22199.84 | 0.081 | 22199 | 17302 | /1| -
|
||||||
|
| 2023-02-17 17:00 |🟩Buy 1080 | BTC | bull | 24091.21| 1360 | 0/0| - | 24091.21 | - | 24091 | 17302 | 1/1|1360.21
|
||||||
|
| 2023-02-19 18:00 |🟥Sell 2940 | BTC | B30 | 24361.74| - |12.69/44.15| 0.011 | 24091.21 | 0.011 | 24091 | 17302 | /1| -
|
||||||
|
| 2023-02-28 17:00 |🟩Buy 12900 | BTC | bull | 23456.05| 1373 | 0/0| - | 23456.05 | - | 24091 | 17302 | 1/1| 1372.9
|
||||||
|
| 2023-03-03 02:00 |🟥Sell 3420 | BTC | sma60 | 22150.31| - |-79.09/21.4| -0.056 | 23456.05 | -0.056 | 24091 | 17302 | /1| -
|
||||||
|
| 2023-03-16 09:00 |🟩Buy 19140 | BTC | bull | 24581.1| 1294 | 0/0| - | 24581.1 | - | 24581 | 17302 | 1/1| 1293.8
|
||||||
|
| 2023-03-22 20:00 |🟥Sell 9300 | BTC | B30 | 26667.33| - |107.18/211.2| 0.085 | 24581.1 | 0.085 | 24581 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2023-03-30 03:00 |🟩Buy 10500 | BTC | bull | 28964.76| 1401 | 0/0| - | 28964.76 | - | 28964 | 17302 | 1/1|1400.98
|
||||||
|
| 2023-03-30 18:00 |🟥Sell 900 | BTC | sma60 | 27839.41| - | -57.17/0| -0.039 | 28964.76 | -0.039 | 28964 | 17302 | /1| -
|
||||||
|
| 2023-03-31 15:00 |🟩Buy 1260 | BTC | bull | 28521.78| 1344 | 0/0| - | 28521.78 | - | 28964 | 17302 | 1/1|1343.81
|
||||||
|
| 2023-04-02 20:00 |🟥Sell 3180 | BTC | sma60 | 27943.85| - |-29.89/1.49| -0.02 | 28521.78 | -0.02 | 28964 | 17302 | /1| -
|
||||||
|
| 2023-04-13 04:00 |🟩Buy 14880 | BTC | bull | 30072.17| 1314 | 0/0| - | 30072.17 | - | 30072 | 17302 | 1/1|1313.92
|
||||||
|
| 2023-04-15 02:00 |🟥Sell 2760 | BTC | B30 | 30370.01| - |10.37/35.37| 0.01 | 30072.17 | 0.01 | 30072 | 17302 | /1| -
|
||||||
|
| 2023-04-26 00:00 |🟩Buy 15720 | BTC | bull | 28300.8| 1324 | 0/0| - | 28300.79 | - | 30072 | 17302 | 1/1| 1324.3
|
||||||
|
| 2023-04-28 14:00 |🟥Sell 3720 | BTC | B30 | 29029.48| - |31.41/75.16| 0.026 | 28300.79 | 0.026 | 30072 | 17302 | /1| -
|
||||||
|
| 2023-04-28 23:00 |🟩Buy 540 | BTC | bull | 29345.35| 1356 | 0/0| - | 29345.34 | - | 30072 | 17302 | 1/1|1355.71
|
||||||
|
| 2023-05-01 02:00 |🟥Sell 3060 | BTC | sma60 | 28504.36| - |-41.52/14.46| -0.029 | 29345.34 | -0.029 | 30072 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2023-05-30 12:00 |🟩Buy 42360 | BTC | bull | 28021.39| 1314 | 0/0| - | 28021.4 | - | 30072 | 17302 | 1/1|1314.19
|
||||||
|
| 2023-05-31 05:00 |🟥Sell 1020 | BTC | sma60 | 27257.7| - | -38.4/0| -0.027 | 28021.4 | -0.027 | 30072 | 17302 | /1| -
|
||||||
|
| 2023-06-19 19:00 |🟩Buy 28200 | BTC | bull | 26495.99| 1276 | 0/0| - | 26496.0 | - | 30072 | 17302 | 1/1|1275.79
|
||||||
|
| 2023-07-17 19:00 |🟥Sell 40320 | BTC | B30 | 29802.39| - |156.49/243.25| 0.125 | 26496.0 | 0.125 | 30072 | 17302 | /1| -
|
||||||
|
| 2023-07-19 05:00 |🟩Buy 2040 | BTC | bull | 30099.08| 1432 | 0/0| - | 30099.08 | - | 30099 | 17302 | 1/1|1432.28
|
||||||
|
| 2023-07-24 10:00 |🟥Sell 7500 | BTC | sma60 | 29178.01| - |-46.65/8.02| -0.031 | 30099.08 | -0.031 | 30099 | 17302 | /1| -
|
||||||
|
| 2023-09-20 03:00 |🟩Buy 83100 | BTC | bull | 27165.48| 1386 | 0/0| - | 27165.48 | - | 30099 | 17302 | 1/1|1385.64
|
||||||
|
| 2023-09-21 11:00 |🟥Sell 1920 | BTC | sma60 | 26649.89| - | -29.04/0| -0.019 | 27165.48 | -0.019 | 30099 | 17302 | /1| -
|
||||||
|
| 2023-10-01 08:00 |🟩Buy 14220 | BTC | bull | 27107.94| 1357 | 0/0| - | 27107.95 | - | 30099 | 17302 | 1/1| 1356.6
|
||||||
|
| 2023-10-02 22:00 |🟥Sell 2280 | BTC | B30 | 27472.22| - |15.5/69.08| 0.013 | 27107.95 | 0.013 | 30099 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2023-10-15 20:00 |🟩Buy 18600 | BTC | bull | 27043.75| 1372 | 0/0| - | 27043.75 | - | 30099 | 17302 | 1/1| 1372.1
|
||||||
|
| 2023-10-18 15:00 |🟥Sell 4020 | BTC | B30 | 28190.49| - |55.37/82.75| 0.042 | 27043.75 | 0.042 | 30099 | 17302 | /1| -
|
||||||
|
| 2023-10-19 12:00 |🟩Buy 1260 | BTC | bull | 28450.7| 1427 | 0/0| - | 28450.69 | - | 30099 | 17302 | 1/1|1427.47
|
||||||
|
| 2024-01-15 00:00 |🟥Sell 126000 | BTC | B30 | 41732.35| - |662.82/1005.58| 0.467 | 28450.69 | 0.467 | 30099 | 17302 | /1| -
|
||||||
|
| 2024-01-27 22:00 |🟩Buy 18600 | BTC | bull | 42150.59| 2090 | 0/0| - | 42150.59 | - | 42150 | 17302 | 1/1|2090.29
|
||||||
|
| 2024-01-31 00:00 |🟥Sell 4440 | BTC | B30 | 42941.1| - |34.98/68.37| 0.019 | 42150.59 | 0.019 | 42150 | 17302 | /1| -
|
||||||
|
| 2024-02-08 00:00 |🟩Buy 11520 | BTC | bull | 44349.6| 2125 | 0/0| - | 44349.6 | - | 44349 | 17302 | 1/1|2125.27
|
||||||
|
| 2024-03-19 09:00 |🟥Sell 58140 | BTC | B30 | 63464.0| - |910.78/1394.94| 0.431 | 44349.6 | 0.431 | 44349 | 17302 | /1| -
|
||||||
|
| 2024-03-24 11:00 |🟩Buy 7320 | BTC | bull | 65098.01| 3036 | 0/0| - | 65098.01 | - | 65098 | 17302 | 1/1|3036.05
|
||||||
|
| 2024-03-27 16:00 |🟥Sell 4620 | BTC | B30 | 68874.0| 1 |169.83/275.49| 0.058 | 65098.01 | 0.058 | 65098 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2024-03-28 07:00 |🟩Buy 900 | BTC | bull | 70363.74| 3206 | 0/0| - | 70363.74 | - | 70363 | 17302 | 1/1|3205.87
|
||||||
|
| 2024-04-01 15:00 |🟥Sell 6240 | BTC | sma60 | 68906.07| - |-72.76/47.03| -0.021 | 70363.74 | -0.021 | 70363 | 17302 | /1| -
|
||||||
|
| 2024-04-08 08:00 |🟩Buy 9660 | BTC | bull | 70698.64| 3133 | 0/0| - | 70698.63 | - | 70698 | 17302 | 1/1|3133.12
|
||||||
|
| 2024-04-09 15:00 |🟥Sell 1860 | BTC | sma60 | 69358.32| - |-65.6/69.22| -0.019 | 70698.63 | -0.019 | 70698 | 17302 | /1| -
|
||||||
|
| 2024-04-10 20:00 |🟩Buy 1740 | BTC | bull | 70084.0| 3068 | 0/0| - | 70083.99 | - | 70698 | 17302 | 1/1|3067.52
|
||||||
|
| 2024-04-12 18:00 |🟥Sell 2760 | BTC | sma60 | 68140.02| 1 |-91.12/38.98| -0.028 | 70083.99 | -0.028 | 70698 | 17302 | /1| -
|
||||||
|
| 2024-04-24 05:00 |🟩Buy 16500 | BTC | bull | 67008.0| 2976 | 0/0| - | 67008.0 | - | 70698 | 17302 | 1/1| 2976.4
|
||||||
|
| 2024-04-24 15:00 |🟥Sell 600 | BTC | sma60 | 65234.85| 1 | -84.62/0| -0.026 | 67008.0 | -0.026 | 70698 | 17302 | /1| -
|
||||||
|
| 2024-05-06 08:00 |🟩Buy 16860 | BTC | bull | 64540.75| 2892 | 0/0| - | 64540.75 | - | 70698 | 17302 | 1/1|2891.79
|
||||||
|
| 2024-05-06 15:00 |🟥Sell 420 | BTC | sma60 | 63271.97| - |-62.57/22.21| -0.02 | 64540.75 | -0.02 | 70698 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2024-05-07 10:00 |🟩Buy 1140 | BTC | bull | 64119.98| 2829 | 0/0| - | 64119.98 | - | 70698 | 17302 | 1/1|2829.22
|
||||||
|
| 2024-05-07 23:00 |🟥Sell 780 | BTC | sma60 | 62850.92| - | -61.59/0| -0.02 | 64119.98 | -0.02 | 70698 | 17302 | /1| -
|
||||||
|
| 2024-05-17 08:00 |🟩Buy 13500 | BTC | bull | 66386.93| 2768 | 0/0| - | 66386.94 | - | 70698 | 17302 | 1/1|2767.63
|
||||||
|
| 2024-05-19 15:00 |🟥Sell 3300 | BTC | B30 | 66928.0| 1 |17.0/33.73| 0.008 | 66386.94 | 0.008 | 70698 | 17302 | /1| -
|
||||||
|
| 2024-05-27 16:00 |🟩Buy 11580 | BTC | bull | 70373.86| 2785 | 0/0| - | 70373.85 | - | 70698 | 17302 | 1/1|2784.62
|
||||||
|
| 2024-05-28 02:00 |🟥Sell 600 | BTC | sma60 | 68614.11| 1 | -75.11/0| -0.025 | 70373.85 | -0.025 | 70698 | 17302 | /1| -
|
||||||
|
| 2024-06-05 01:00 |🟩Buy 11460 | BTC | bull | 70775.99| 2710 | 0/0| - | 70776.0 | - | 70776 | 17302 | 1/1|2709.51
|
||||||
|
| 2024-06-07 19:00 |🟥Sell 3960 | BTC | sma60 | 69154.43| - |-67.43/29.92| -0.023 | 70776.0 | -0.023 | 70776 | 17302 | /1| -
|
||||||
|
| 2024-07-15 00:00 |🟩Buy 53580 | BTC | bull | 60797.91| 2642 | 0/0| - | 60797.91 | - | 70776 | 17302 | 1/1|2642.08
|
||||||
|
| 2024-07-16 09:00 |🟥Sell 1980 | BTC | B30 | 62820.67| - |82.52/170.52| 0.033 | 60797.91 | 0.033 | 70776 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2024-07-16 17:00 |🟩Buy 480 | BTC | bull | 64500.0| 2725 | 0/0| - | 64500.0 | - | 70776 | 17302 | 1/1| 2724.6
|
||||||
|
| 2024-07-22 15:00 |🟥Sell 8520 | BTC | B30 | 66712.0| - |87.89/150.43| 0.034 | 64500.0 | 0.034 | 70776 | 17302 | /1| -
|
||||||
|
| 2024-07-27 00:00 |🟩Buy 6300 | BTC | bull | 67908.0| 2812 | 0/0| - | 67907.99 | - | 70776 | 17302 | 1/1|2812.49
|
||||||
|
| 2024-07-30 01:00 |🟥Sell 4380 | BTC | sma60 | 66610.0| - |-59.32/72.62| -0.019 | 67907.99 | -0.019 | 70776 | 17302 | /1| -
|
||||||
|
| 2024-08-25 23:00 |🟩Buy 38760 | BTC | bull | 64482.0| 2753 | 0/0| - | 64482.01 | - | 70776 | 17302 | 1/1|2753.17
|
||||||
|
| 2024-08-26 22:00 |🟥Sell 1380 | BTC | sma60 | 63155.81| - | -62.06/0| -0.021 | 64482.01 | -0.021 | 70776 | 17302 | /1| -
|
||||||
|
| 2024-09-14 00:00 |🟩Buy 26040 | BTC | bull | 60497.99| 2691 | 0/0| - | 60498.0 | - | 70776 | 17302 | 1/1| 2691.1
|
||||||
|
| 2024-09-16 00:00 |🟥Sell 2880 | BTC | sma60 | 59132.0| - | -66.08/0| -0.023 | 60498.0 | -0.023 | 70776 | 17302 | /1| -
|
||||||
|
| 2024-09-19 00:00 |🟩Buy 4320 | BTC | bull | 61759.98| 2625 | 0/0| - | 61759.99 | - | 70776 | 17302 | 1/1|2625.02
|
||||||
|
| 2024-09-20 18:00 |🟥Sell 2520 | BTC | B30 | 62704.0| - |34.83/83.22| 0.015 | 61759.99 | 0.015 | 70776 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2024-09-28 04:00 |🟩Buy 10680 | BTC | bull | 66063.76| 2660 | 0/0| - | 66063.76 | - | 70776 | 17302 | 1/1|2659.86
|
||||||
|
| 2024-09-30 02:00 |🟥Sell 2760 | BTC | sma60 | 64769.99| - | -57.35/0| -0.02 | 66063.76 | -0.02 | 70776 | 17302 | /1| -
|
||||||
|
| 2024-10-14 05:00 |🟩Buy 20340 | BTC | bull | 64137.99| 2603 | 0/0| - | 64137.99 | - | 70776 | 17302 | 1/1| 2602.5
|
||||||
|
| 2024-10-21 14:00 |🟥Sell 10620 | BTC | B30 | 67312.0| - |123.44/200.4| 0.049 | 64137.99 | 0.049 | 70776 | 17302 | /1| -
|
||||||
|
| 2024-10-27 15:00 |🟩Buy 8700 | BTC | bull | 67696.0| 2726 | 0/0| - | 67695.99 | - | 70776 | 17302 | 1/1|2725.94
|
||||||
|
| 2024-10-31 14:00 |🟥Sell 5700 | BTC | B30 | 71308.0| - |139.82/214.71| 0.053 | 67695.99 | 0.053 | 70776 | 17302 | /1| -
|
||||||
|
| 2024-11-06 01:00 |🟩Buy 7860 | BTC | bull | 71096.03| 2866 | 0/0| - | 71096.04 | - | 71096 | 17302 | 1/1|2865.76
|
||||||
|
| 2024-12-20 09:00 |🟥Sell 63840 | BTC | B30 | 95473.74| 1 |975.71/1490.41| 0.343 | 71096.04 | 0.343 | 71096 | 17302 | /1| -
|
||||||
|
| 2024-12-26 00:00 |🟩Buy 8100 | BTC | bull | 99429.61| 3841 | 0/0| - | 99429.6 | - | 99429 | 17302 | 1/1|3841.47
|
||||||
|
| 2024-12-26 09:00 |🟥Sell 540 | BTC | sma60 | 95878.56| 1 | -144.72/0| -0.036 | 99429.6 | -0.036 | 99429 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2025-01-05 23:00 |🟩Buy 15240 | BTC | bull | 98695.21| 3697 | 0/0| - | 98695.21 | - | 99429 | 17302 | 1/1|3696.75
|
||||||
|
| 2025-01-07 13:00 |🟥Sell 2280 | BTC | B30 |100750.89| 1 |69.52/125.06| 0.021 | 98695.21 | 0.021 | 99429 | 17302 | /1| -
|
||||||
|
| 2025-01-13 22:00 |🟩Buy 9180 | BTC | bull | 94193.49| 3766 | 0/0| - | 94193.49 | - | 99429 | 17302 | 1/1|3766.26
|
||||||
|
| 2025-01-16 15:00 |🟥Sell 3900 | BTC | B30 | 97618.89| - |129.28/244.24| 0.036 | 94193.49 | 0.036 | 99429 | 17302 | /1| -
|
||||||
|
| 2025-01-17 02:00 |🟩Buy 660 | BTC | bull | 101659.8| 3896 | 0/0| - | 101659.8 | - | 101659 | 17302 | 1/1|3895.54
|
||||||
|
| 2025-01-19 22:00 |🟥Sell 4080 | BTC | B30 |103684.44| 1 |69.7/168.86| 0.02 | 101659.8 | 0.02 | 101659 | 17302 | /1| -
|
||||||
|
| 2025-01-23 18:00 |🟩Buy 5520 | BTC | bull |105927.78| 3965 | 0/0| - | 105927.78 | - | 105927 | 17302 | 1/1|3965.24
|
||||||
|
| 2025-01-23 20:00 |🟥Sell 120 | BTC | sma60 |103770.04| - | -88.61/0| -0.02 | 105927.78 | -0.02 | 105927 | 17302 | /1| -
|
||||||
|
| 2025-01-31 17:00 |🟩Buy 11340 | BTC | bull |105081.86| 3877 | 0/0| - | 105081.87 | - | 105927 | 17302 | 1/1|3876.63
|
||||||
|
| 2025-01-31 19:00 |🟥Sell 120 | BTC | sma60 |102627.29| - | -98.21/0| -0.023 | 105081.87 | -0.023 | 105927 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2025-04-14 04:00 |🟩Buy 104220 | BTC | bull | 84566.04| 3778 | 0/0| - | 84566.03 | - | 105927 | 17302 | 1/1|3778.41
|
||||||
|
| 2025-06-05 20:00 |🟥Sell 75840 | BTC | B30 |101914.77| - |766.81/1207.18| 0.205 | 84566.03 | 0.205 | 105927 | 17302 | /1| -
|
||||||
|
| 2025-06-08 17:00 |🟩Buy 4140 | BTC | bull | 106190.0| 4545 | 0/0| - | 106189.99 | - | 106189 | 17302 | 1/1|4545.22
|
||||||
|
| 2025-06-11 18:00 |🟥Sell 4380 | BTC | B30 |108984.72| - |110.4/165.55| 0.026 | 106189.99 | 0.026 | 106189 | 17302 | /1| -
|
||||||
|
| 2025-06-24 00:00 |🟩Buy 17640 | BTC | bull |105333.94| 4656 | 0/0| - | 105333.93 | - | 106189 | 17302 | 1/1|4655.63
|
||||||
|
| 2025-06-26 14:00 |🟥Sell 3720 | BTC | B30 |106960.01| 1 |62.47/105.0| 0.015 | 105333.93 | 0.015 | 106189 | 17302 | /1| -
|
||||||
|
| 2025-07-09 14:00 |🟩Buy 18720 | BTC | bull |109183.99| 4718 | 0/0| - | 109184.0 | - | 109184 | 17302 | 1/1| 4718.1
|
||||||
|
| 2025-07-15 03:00 |🟥Sell 7980 | BTC | B30 |118251.05| - |381.96/575.56| 0.083 | 109184.0 | 0.083 | 109184 | 17302 | /1| -
|
||||||
|
| 2025-07-23 00:00 |🟩Buy 11340 | BTC | bull |119954.43| 5100 | 0/0| - | 119954.42 | - | 119954 | 17302 | 1/1|5100.06
|
||||||
|
| 2025-07-23 14:00 |🟥Sell 840 | BTC | sma60 |117381.44| 1 | -119.47/0| -0.021 | 119954.42 | -0.021 | 119954 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2025-07-24 02:00 |🟩Buy 720 | BTC | bull | 119094.4| 4981 | 0/0| - | 119094.4 | - | 119954 | 17302 | 1/1| 4980.6
|
||||||
|
| 2025-07-25 03:00 |🟥Sell 1500 | BTC | sma60 |116353.67| - | -124.46/0| -0.023 | 119094.4 | -0.023 | 119954 | 17302 | /1| -
|
||||||
|
| 2025-08-09 11:00 |🟩Buy 22080 | BTC | bull |117424.16| 4856 | 0/0| - | 117424.16 | - | 119954 | 17302 | 1/1|4856.13
|
||||||
|
| 2025-08-11 18:00 |🟥Sell 3300 | BTC | B30 | 119500.0| 1 |76.04/191.73| 0.018 | 117424.16 | 0.018 | 119954 | 17302 | /1| -
|
||||||
|
| 2025-08-12 17:00 |🟩Buy 1380 | BTC | bull |119647.69| 4932 | 0/0| - | 119647.7 | - | 119954 | 17302 | 1/1|4932.17
|
||||||
|
| 2025-08-14 11:00 |🟥Sell 2520 | BTC | B30 | 120933.0| - |43.06/163.09| 0.011 | 119647.7 | 0.011 | 119954 | 17302 | /1| -
|
||||||
|
| 2025-09-02 03:00 |🟩Buy 26880 | BTC | bull | 110246.0| 4975 | 0/0| - | 110246.01 | - | 119954 | 17302 | 1/1|4975.23
|
||||||
|
| 2025-09-04 04:00 |🟥Sell 2940 | BTC | B30 |111148.97| 1 |30.75/83.2| 0.008 | 110246.01 | 0.008 | 119954 | 17302 | /1| -
|
||||||
|
| 2025-09-05 00:00 |🟩Buy 1200 | BTC | bull |110730.87| 5006 | 0/0| - | 110730.87 | - | 119954 | 17302 | 1/1|5005.99
|
||||||
|
| 2025-09-09 01:00 |🟥Sell 5820 | BTC | B30 |111650.03| 1 |31.49/102.15| 0.008 | 110730.87 | 0.008 | 119954 | 17302 | /1| -
|
||||||
|
| Date | Action |Pair | Trade Type | Rate | Dispo | Profit | Pct | max_touch | last_lost | last_max| last_max| Buys| Stake | rsi|
|
||||||
|
+------------------+------------+-----+--------------------+---------+--------+------------+--------+-------------+--------------+------------------+-----+-------++------+-------+-----+-----+-----+-----+-----+-----+
|
||||||
|
| 2025-09-09 09:00 |🟩Buy 480 | BTC | bull |112992.69| 5037 | 0/0| - | 112992.69 | - | 119954 | 17302 | 1/1|5037.48
|
||||||
|
| 2025-09-09 16:00 |🟥Sell 420 | BTC | sma60 |110880.76| - | -104.13/0| -0.019 | 112992.69 | -0.019 | 119954 | 17302 | /1| -
|
||||||
|
| 2025-09-10 09:00 |🟩Buy 1020 | BTC | bull |112370.07| 4933 | 0/0| - | 112370.08 | - | 119954 | 17302 | 1/1|4933.35
|
||||||
|
| 2025-09-14 16:00 |🟥Sell 6180 | BTC | B30 |115224.01| - |115.3/177.07| 0.025 | 112370.08 | 0.025 | 119954 | 17302 | /1| -
|
||||||
|
| 2025-09-18 01:00 |🟩Buy 4860 | BTC | bull |116350.65| 5049 | 0/0| - | 116350.65 | - | 119954 | 17302 | 1/1|5048.65
|
||||||
|
| 2025-09-22 03:00 |🟥Sell 5880 | BTC | sma60 |114187.81| - |-103.85/53.72| -0.019 | 116350.65 | -0.019 | 119954 | 17302 | /1| -
|
||||||
|
| 2025-10-01 01:00 |🟩Buy 12840 | BTC | bull |114239.53| 4945 | 0/0| - | 114239.53 | - | 119954 | 17302 | 1/1| 4944.8
|
||||||
|
| 2025-10-07 16:00 |🟥Sell 9540 | BTC | B30 |121846.01| 1 |318.99/499.08| 0.067 | 114239.53 | 0.067 | 119954 | 17302 | /1| -
|
||||||
|
2026-02-28 17:34:59,918 - freqtrade.misc - INFO - dumping json to
|
||||||
|
"/freqtrade/user_data/backtest_results/backtest-result-2026-02-28_17-34-59.meta.json"
|
||||||
|
Result for strategy Empty
|
||||||
|
BACKTESTING REPORT
|
||||||
|
┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
|
||||||
|
┃ Pair ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
|
||||||
|
┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
|
||||||
|
│ BTC/USDT │ 59 │ 3.3 │ 4263.790 │ 426.38 │ 6 days, 23:28:00 │ 33 0 26 55.9 │
|
||||||
|
│ TOTAL │ 59 │ 3.3 │ 4263.790 │ 426.38 │ 6 days, 23:28:00 │ 33 0 26 55.9 │
|
||||||
|
└──────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┘
|
||||||
|
LEFT OPEN TRADES REPORT
|
||||||
|
┏━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
|
||||||
|
┃ Pair ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
|
||||||
|
┡━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
|
||||||
|
│ TOTAL │ 0 │ 0.0 │ 0.000 │ 0.0 │ 0:00 │ 0 0 0 0 │
|
||||||
|
└───────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────┴────────────────────────┘
|
||||||
|
ENTER TAG STATS
|
||||||
|
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
|
||||||
|
┃ Enter Tag ┃ Entries ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
|
||||||
|
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
|
||||||
|
│ bull │ 59 │ 3.3 │ 4263.790 │ 426.38 │ 6 days, 23:28:00 │ 33 0 26 55.9 │
|
||||||
|
│ TOTAL │ 59 │ 3.3 │ 4263.790 │ 426.38 │ 6 days, 23:28:00 │ 33 0 26 55.9 │
|
||||||
|
└───────────┴─────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┘
|
||||||
|
EXIT REASON STATS
|
||||||
|
┏━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
|
||||||
|
┃ Exit Reason ┃ Exits ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
|
||||||
|
┡━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
|
||||||
|
│ B30 │ 33 │ 8.0 │ 6194.610 │ 619.46 │ 11 days, 5:36:00 │ 33 0 0 100 │
|
||||||
|
│ sma60 │ 26 │ -2.67 │ -1930.820 │ -193.08 │ 1 day, 13:51:00 │ 0 0 26 0 │
|
||||||
|
│ TOTAL │ 59 │ 3.3 │ 4263.790 │ 426.38 │ 6 days, 23:28:00 │ 33 0 26 55.9 │
|
||||||
|
└─────────────┴───────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┘
|
||||||
|
MIXED TAG STATS
|
||||||
|
┏━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
|
||||||
|
┃ Enter Tag ┃ Exit Reason ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
|
||||||
|
┡━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
|
||||||
|
│ bull │ B30 │ 33 │ 8.0 │ 6194.610 │ 619.46 │ 11 days, 5:36:00 │ 33 0 0 100 │
|
||||||
|
│ bull │ sma60 │ 26 │ -2.67 │ -1930.820 │ -193.08 │ 1 day, 13:51:00 │ 0 0 26 0 │
|
||||||
|
│ TOTAL │ │ 59 │ 3.3 │ 4263.790 │ 426.38 │ 6 days, 23:28:00 │ 33 0 26 55.9 │
|
||||||
|
└───────────┴─────────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┘
|
||||||
|
MONTH BREAKDOWN
|
||||||
|
┏━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
|
||||||
|
┃ Month ┃ Trades ┃ Tot Profit USDT ┃ Profit Factor ┃ Win Draw Loss Win% ┃
|
||||||
|
┡━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
|
||||||
|
│ 28/02/2023 │ 3 │ 372.897 │ 0.0 │ 3 0 0 100 │
|
||||||
|
│ 31/03/2023 │ 3 │ -29.085 │ 0.79 │ 1 0 2 33.3 │
|
||||||
|
│ 30/04/2023 │ 3 │ 11.898 │ 1.4 │ 2 0 1 66.7 │
|
||||||
|
│ 31/05/2023 │ 2 │ -79.919 │ 0.0 │ 0 0 2 0 │
|
||||||
|
│ 30/06/2023 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 31/07/2023 │ 2 │ 109.847 │ 3.35 │ 1 0 1 50.0 │
|
||||||
|
│ 31/08/2023 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 30/09/2023 │ 1 │ -29.039 │ 0.0 │ 0 0 1 0 │
|
||||||
|
│ 31/10/2023 │ 2 │ 70.87 │ 0.0 │ 2 0 0 100 │
|
||||||
|
│ 30/11/2023 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 31/12/2023 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 31/01/2024 │ 2 │ 697.801 │ 0.0 │ 2 0 0 100 │
|
||||||
|
│ 29/02/2024 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 31/03/2024 │ 2 │ 1080.605 │ 0.0 │ 2 0 0 100 │
|
||||||
|
│ 30/04/2024 │ 4 │ -314.088 │ 0.0 │ 0 0 4 0 │
|
||||||
|
│ 31/05/2024 │ 4 │ -182.279 │ 0.09 │ 1 0 3 25.0 │
|
||||||
|
│ 30/06/2024 │ 1 │ -67.429 │ 0.0 │ 0 0 1 0 │
|
||||||
|
│ 31/07/2024 │ 3 │ 111.09 │ 2.87 │ 2 0 1 66.7 │
|
||||||
|
│ 31/08/2024 │ 1 │ -62.063 │ 0.0 │ 0 0 1 0 │
|
||||||
|
│ 30/09/2024 │ 3 │ -88.603 │ 0.28 │ 1 0 2 33.3 │
|
||||||
|
│ 31/10/2024 │ 2 │ 263.26 │ 0.0 │ 2 0 0 100 │
|
||||||
|
│ 30/11/2024 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 31/12/2024 │ 2 │ 830.987 │ 6.74 │ 1 0 1 50.0 │
|
||||||
|
│ 31/01/2025 │ 5 │ 81.667 │ 1.44 │ 3 0 2 60.0 │
|
||||||
|
│ 28/02/2025 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 31/03/2025 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 30/04/2025 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 31/05/2025 │ 0 │ 0 │ 0.0 │ 0 0 0 0 │
|
||||||
|
│ 30/06/2025 │ 3 │ 939.688 │ 0.0 │ 3 0 0 100 │
|
||||||
|
│ 31/07/2025 │ 3 │ 138.029 │ 1.57 │ 1 0 2 33.3 │
|
||||||
|
│ 31/08/2025 │ 2 │ 119.103 │ 0.0 │ 2 0 0 100 │
|
||||||
|
│ 30/09/2025 │ 5 │ -30.436 │ 0.85 │ 3 0 2 60.0 │
|
||||||
|
│ 31/10/2025 │ 1 │ 318.991 │ 0.0 │ 1 0 0 100 │
|
||||||
|
└────────────┴────────┴─────────────────┴───────────────┴────────────────────────┘
|
||||||
|
SUMMARY METRICS
|
||||||
|
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
|
||||||
|
┃ Metric ┃ Value ┃
|
||||||
|
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
|
||||||
|
│ Backtesting from │ 2023-01-01 00:00:00 │
|
||||||
|
│ Backtesting to │ 2025-10-11 00:00:00 │
|
||||||
|
│ Trading Mode │ Spot │
|
||||||
|
│ Max open trades │ 1 │
|
||||||
|
│ │ │
|
||||||
|
│ Total/Daily Avg Trades │ 59 / 0.06 │
|
||||||
|
│ Starting balance │ 1000 USDT │
|
||||||
|
│ Final balance │ 5263.79 USDT │
|
||||||
|
│ Absolute profit │ 4263.79 USDT │
|
||||||
|
│ Total profit % │ 426.38% │
|
||||||
|
│ CAGR % │ 81.82% │
|
||||||
|
│ Sortino │ 2.82 │
|
||||||
|
│ Sharpe │ 0.35 │
|
||||||
|
│ Calmar │ 42.68 │
|
||||||
|
│ SQN │ 2.37 │
|
||||||
|
│ Profit factor │ 3.21 │
|
||||||
|
│ Expectancy (Ratio) │ 72.27 (0.97) │
|
||||||
|
│ Avg. daily profit │ 4.205 USDT │
|
||||||
|
│ Avg. stake amount │ 2946.519 USDT │
|
||||||
|
│ Total trade volume │ 352657.589 USDT │
|
||||||
|
│ │ │
|
||||||
|
│ Best Pair │ BTC/USDT 426.38% │
|
||||||
|
│ Worst Pair │ BTC/USDT 426.38% │
|
||||||
|
│ Best trade │ BTC/USDT 46.39% │
|
||||||
|
│ Worst trade │ BTC/USDT -5.76% │
|
||||||
|
│ Best day │ 975.709 USDT │
|
||||||
|
│ Worst day │ -144.722 USDT │
|
||||||
|
│ Days win/draw/lose │ 32 / 914 / 26 │
|
||||||
|
│ Min/Max/Avg. Duration Winners │ 1d 09:00 / 87d 12:00 / 11d 05:36 │
|
||||||
|
│ Min/Max/Avg. Duration Losers │ 0d 02:00 / 5d 05:00 / 1d 13:51 │
|
||||||
|
│ Max Consecutive Wins / Loss │ 6 / 6 │
|
||||||
|
│ Rejected Entry signals │ 0 │
|
||||||
|
│ Entry/Exit Timeouts │ 0 / 0 │
|
||||||
|
│ │ │
|
||||||
|
│ Min balance │ 1260.898 USDT │
|
||||||
|
│ Max balance │ 5263.79 USDT │
|
||||||
|
│ Max % of account underwater │ 18.82% │
|
||||||
|
│ Absolute drawdown │ 603.373 USDT (18.82%) │
|
||||||
|
│ Drawdown duration │ 186 days 10:00:00 │
|
||||||
|
│ Profit at drawdown start │ 2205.874 USDT │
|
||||||
|
│ Profit at drawdown end │ 1602.501 USDT │
|
||||||
|
│ Drawdown start │ 2024-03-27 16:00:00 │
|
||||||
|
│ Drawdown end │ 2024-09-30 02:00:00 │
|
||||||
|
│ Market change │ 580.68% │
|
||||||
|
└───────────────────────────────┴──────────────────────────────────┘
|
||||||
|
|
||||||
|
Backtested 2023-01-01 00:00:00 -> 2025-10-11 00:00:00 | Max open trades : 1
|
||||||
|
STRATEGY SUMMARY
|
||||||
|
┏━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┓
|
||||||
|
┃ Strategy ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃ Drawdown ┃
|
||||||
|
┡━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩
|
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│ Empty │ 59 │ 3.30 │ 4263.790 │ 426.38 │ 6 days, 23:28:00 │ 33 0 26 │ 603.373 USDT 18.82% │
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│ │ │ │ │ │ │ 55.9 │ │
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└──────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴───────────────────────┴──────────────────────┘
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Reference in New Issue
Block a user