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0f8b1a7c22
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0f8b1a7c22 | ||
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b25d6f5759 | ||
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a26460cf10 | ||
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074205cc09 |
@@ -104,19 +104,23 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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},
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"subplots": {
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"Rsi": {
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"rsi_1h": {
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"color": "red"
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},
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"rsi_1d": {
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"max_rsi_24": {
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"color": "blue"
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}
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# "rsi_1h": {
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# "color": "red"
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# },
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# "rsi_1d": {
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# "color": "blue"
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# }
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},
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"Rsi_deriv1": {
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"rsi_deriv1_1h": {
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"color": "red"
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},
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"rsi_deriv1_1d": {
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"color": "blue"
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},
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# "rsi_deriv1_1h": {
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# "color": "red"
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# },
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# "rsi_deriv1_1d": {
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# "color": "blue"
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# },
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"sma60_deriv1": {
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"color": "green"
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}
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@@ -131,34 +135,6 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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"sma60_deriv2": {
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"color": "green"
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}
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},
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# "Down": {
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# "down_count_1h": {
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# "color": "green"
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# },
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# "up_count_1h": {
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# "color": "blue"
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# }
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# },
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# "Diff": {
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# "sma10_deriv1": {
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# "color": "#74effc"
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# }
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# },
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# "smooth": {
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# 'sma60_deriv1': {
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# "color": "blue"
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# },
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# # 'mid_smooth_1h_deriv1': {
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# # "color": "red"
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# # },
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# 'sma5_deriv2_1h': {
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# "color": "pink"
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# },
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# # 'mid_smooth_1h_deriv2': {
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# # "color": "#da59a6"
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# # }
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# }
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}
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}
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}
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@@ -199,10 +175,10 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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# 50 50 50 100 100 150 200 250 350 450 600 1050
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fibo = [1, 1, 1, 2, 2, 3, 4, 5, 7, 9, 12, 16, 21]
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baisse = [1, 2, 3, 5, 7, 10, 14, 19, 26, 35, 47, 63, 84]
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# Ma suite 1 1 1 2 2 3 4 5 7 9 12 16 21
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# Mise 50 50 50 100 100 150 200 250 350 450 600 800 1050
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# Somme Mises 50 100 150 250 350 500 700 950 1300 1750 2350 3150 4200
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# baisse 1 2 3 5 7 10 14 19 26 35 47 63 84
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# Ma suite 1 1 1 2 2 3 4 5 7 9 12 16 21
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# Mise 50 50 50 100 100 150 200 250 350 450 600 800 1050
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# Somme Mises 50 100 150 250 350 500 700 950 1300 1750 2350 3150 4200
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# baisse 1 2 3 5 7 10 14 19 26 35 47 63 84
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# factors = [1, 1.1, 1.25, 1.5, 2.0, 3]
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# thresholds = [2, 5, 10, 20, 30, 50]
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@@ -216,27 +192,28 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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# sma20_deriv1_1d_stop_protection = DecimalParameter(-0.2, 0.2, default=0.05, decimals=2, space='protection',
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# optimize=True, load=True)
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sma5_deriv1_1d_stop_protection = DecimalParameter(-5, 0, default=0.5, decimals=1, space='protection',
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optimize=True, load=True)
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optimize=True, load=True)
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sma5_deriv2_1d_stop_protection = DecimalParameter(-5, 0, default=0.5, decimals=1, space='protection', optimize=True,
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load=True)
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load=True)
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# sma20_deriv1_1d_start_protection = DecimalParameter(-0.2, 0.2, default=0.05, decimals=2, space='protection',
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# optimize=True, load=True)
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sma5_deriv1_1d_restart_protection = DecimalParameter(0, 5, default=0.5, decimals=1, space='protection',
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optimize=True, load=True)
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sma5_deriv2_1d_restart_protection = DecimalParameter(0, 5, default=0.5, decimals=1, space='protection', optimize=True,
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load=True)
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optimize=True, load=True)
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sma5_deriv2_1d_restart_protection = DecimalParameter(0, 5, default=0.5, decimals=1, space='protection',
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optimize=True,
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load=True)
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mise_factor_buy = DecimalParameter(0.01, 0.2, default=0.05, decimals=2, space='buy', optimize=True, load=True)
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sma5_deriv1_1d_stop_sell = DecimalParameter(-5, 5, default=0.5, decimals=1, space='sell',
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optimize=True, load=True)
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optimize=True, load=True)
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sma5_deriv2_1d_stop_sell = DecimalParameter(-5, 5, default=0.5, decimals=1, space='sell', optimize=True,
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load=True)
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load=True)
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sma5_deriv1_1h_stop_sell = DecimalParameter(-5, 5, default=0.5, decimals=1, space='sell',
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optimize=True, load=True)
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optimize=True, load=True)
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sma5_deriv2_1h_stop_sell = DecimalParameter(-5, 5, default=0.5, decimals=1, space='sell', optimize=True,
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load=True)
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load=True)
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# Récupération des labels ordonnés
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# labels = ['B5', 'B4', 'B3', 'B2', 'B1', 'N0', 'H1', 'H2', 'H3', 'H4', 'H5']
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# index_labels = ['B5', 'B4', 'B3', 'B2', 'B1', 'N0', 'H1', 'H2', 'H3', 'H4', 'H5']
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@@ -320,7 +297,8 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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# val = self.getProbaHausse144(last_candle)
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# allow_to_buy = True #(not self.stop_all) #& (not self.all_down)
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allow_to_buy = not self.pairs[pair]['stop'] # and val > self.buy_val.value #not last_candle['tendency'] in ('B-', 'B--') # (rate <= float(limit)) | (entry_tag == 'force_entry')
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allow_to_buy = not self.pairs[pair][
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'stop'] # and val > self.buy_val.value #not last_candle['tendency'] in ('B-', 'B--') # (rate <= float(limit)) | (entry_tag == 'force_entry')
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# if allow_to_buy:
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# poly_func, x_future, y_future, count = self.polynomial_forecast(
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@@ -381,7 +359,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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last_candle = dataframe.iloc[-1].squeeze()
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force = self.pairs[pair]['force_sell']
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allow_to_sell = (last_candle['percent'] < 0) #or force
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allow_to_sell = (last_candle['percent'] < 0) # or force
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minutes = int(round((current_time - trade.date_last_filled_utc).total_seconds() / 60, 0))
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@@ -457,7 +435,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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max_profit = self.pairs[pair]['max_profit']
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baisse = 0
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if profit > 0:
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baisse = max_profit - profit
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baisse = 1 - (profit / max_profit)
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mx = max_profit / 5
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self.pairs[pair]['count_of_buys'] = count_of_buys
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self.pairs[pair]['current_profit'] = profit
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@@ -500,11 +478,9 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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# self.pairs[pair]['force_sell'] = False
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# return 'Force' + pair_name + '_' + str(count_of_buys) + '_' + str(self.pairs[pair]['has_gain'])
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# if profit > - 2 and last_candle['rsi_1h'] < 50 \
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# and (last_candle['sma20'] - before_last_candle['sma20'] < 0) \
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# and (last_candle['rsi_deriv1_1h'] < -4 and last_candle['rsi_deriv2_1h'] < -4) :
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# self.pairs[pair]['force_sell'] = False
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# return 'stoploss_' + pair_name + '_' + str(count_of_buys) + '_' + str(self.pairs[pair]['has_gain'])
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if profit > 0.5 * count_of_buys and baisse > 0.15:
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self.pairs[pair]['force_sell'] = False
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return str(count_of_buys) + '_' + 'Bas_' + pair_name + '_' + str(self.pairs[pair]['has_gain'])
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factor = 1
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if (self.getShortName(pair) == 'BTC'):
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@@ -515,14 +491,14 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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# return 'Baisse_' + pair_name + '_' + str(count_of_buys) + '_' + str(self.pairs[pair]['has_gain'])
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#
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# if 1 <= count_of_buys <= 3:
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if last_candle['max_rsi_24'] > 75 and profit > expected_profit and (last_candle['hapercent'] < 0) :
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if last_candle['max_rsi_24'] > 75 and profit > expected_profit and (last_candle['hapercent'] < 0) and last_candle['sma60_deriv1'] < 0:
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self.pairs[pair]['force_sell'] = False
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return str(count_of_buys) + '_' + 'Rsi_' + pair_name + '_' + str(self.pairs[pair]['has_gain'])
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if last_candle['mid_smooth_1h_deriv1'] < 0 and last_candle['rsi_1h'] < 50 and profit > expected_profit:
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self.pairs[pair]['force_sell'] = False
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self.pairs[pair]['force_buy'] = (self.pairs[pair]['count_of_buys'] - self.pairs[pair]['has_gain'] > 5)
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return str(count_of_buys) + '_' + 'Drv3_' + pair_name + '_' + str(self.pairs[pair]['has_gain'])
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# if last_candle['mid_smooth_1h_deriv1'] < 0 and profit > expected_profit:
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# self.pairs[pair]['force_sell'] = False
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# self.pairs[pair]['force_buy'] = (self.pairs[pair]['count_of_buys'] - self.pairs[pair]['has_gain'] > 5)
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# return str(count_of_buys) + '_' + 'Drv3_' + pair_name + '_' + str(self.pairs[pair]['has_gain'])
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# if 4 <= count_of_buys <= 6:
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# if ((before_last_candle_2['mid_smooth_12_deriv1'] <= before_last_candle['mid_smooth_12_deriv1'])
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@@ -590,11 +566,11 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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if self.columns_logged % 10 == 0:
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self.printLog(
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f"| {'Date':<16} | {'Action':<10} |{'Pair':<5}| {'Trade Type':<18} |{'Rate':>8} | {'Dispo':>6} | {'Profit':>8} | {'Pct':>6} | {'max_touch':>11} | {'last_lost':>12} | {'last_max':>7}| {'last_max':>7}|{'Buys':>5}| {'Stake':>5} |"
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f"Tdc|{'val':>6}|Distmax|s201d|s5_1d|s5_2d|s51h|s52h|smt1h|smt2h|"
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f"Tdc|{'rsi':>6}|Distmax|s201d|s5_1d|s5_2d|s51h|s52h|smt1h|smt2h|"
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)
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self.printLineLog()
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df = pd.DataFrame.from_dict(self.pairs, orient='index')
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colonnes_a_exclure = ['last_candle', 'last_trade', 'last_palier_index', 'current_trade',
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colonnes_a_exclure = ['last_candle', 'last_trade', 'last_palier_index', #'current_trade',
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'trade_info', 'last_date', 'last_count_of_buys', 'base_stake_amount', 'stop_buy']
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df_filtered = df[df['count_of_buys'] > 0].drop(columns=colonnes_a_exclure)
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# df_filtered = df_filtered["first_buy", "last_max", "max_touch", "last_sell","last_buy", 'count_of_buys', 'current_profit']
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@@ -661,8 +637,10 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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color_smooth_1h = GREEN if last_candle['mid_smooth_1h_deriv1'] > 0 else RED
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color_smooth2_1h = GREEN if last_candle['mid_smooth_1h_deriv2'] > 0 else RED
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last_max = int(self.pairs[pair]['last_max']) if self.pairs[pair]['last_max'] > 1 else round(self.pairs[pair]['last_max'],3)
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last_min = int(self.pairs[pair]['last_min']) if self.pairs[pair]['last_min'] > 1 else round(self.pairs[pair]['last_min'], 3)
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last_max = int(self.pairs[pair]['last_max']) if self.pairs[pair]['last_max'] > 1 else round(
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self.pairs[pair]['last_max'], 3)
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last_min = int(self.pairs[pair]['last_min']) if self.pairs[pair]['last_min'] > 1 else round(
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self.pairs[pair]['last_min'], 3)
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profit = str(profit) + '/' + str(round(self.pairs[pair]['max_profit'], 2))
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@@ -676,10 +654,10 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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f"| {date:<16} |{action:<10} | {pair[0:3]:<3} | {trade_type or '-':<18} |{rate or '-':>9}| {dispo or '-':>6} "
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f"|{color}{profit or '-':>10}{RESET}| {pct_max or '-':>6} | {round(self.pairs[pair]['max_touch'], 2) or '-':>11} | {last_lost or '-':>12} "
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f"| {last_max or '-':>7} | {last_min or '-':>7} |{total_counts or '-':>5}|{stake or '-':>7}"
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f"|{ last_candle['tendency_12'] or '-':>3}|" # {last_candle['tendency_1h'] or '-':>3}|{last_candle['tendency_1d'] or '-':>3}"
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f"|{last_candle['tendency_12'] or '-':>3}|" # {last_candle['tendency_1h'] or '-':>3}|{last_candle['tendency_1d'] or '-':>3}"
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# f"|{round(last_candle['mid_smooth_24_deriv1'],3) or '-':>6}|{round(last_candle['mid_smooth_1h_deriv1'],3) or '-':>6}|{round(last_candle['mid_smooth_deriv1_1d'],3) or '-' :>6}|"
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# f"{round(last_candle['mid_smooth_24_deriv2'],3) or '-' :>6}|{round(last_candle['mid_smooth_1h_deriv2'],3) or '-':>6}|{round(last_candle['mid_smooth_deriv2_1d'],3) or '-':>6}|"
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f"{round(val, 1) or '-' :>6}|"
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f"{round(last_candle['max_rsi_24'], 1) or '-' :>6}|"
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f"{dist_max:>7}|{color_sma20}{round(last_candle['sma20_deriv1_1d'], 2):>5}{RESET}"
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f"|{color_sma5}{round(last_candle['mid_smooth_5_deriv1_1d'], 2):>5}{RESET}|{color_sma5_2}{round(last_candle['mid_smooth_5_deriv2_1d'], 2):>5}{RESET}"
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f"|{color_sma5_1h}{round(last_candle['sma60_deriv1'], 2):>5}{RESET}|{color_sma5_2h}{round(last_candle['sma60_deriv2'], 2):>5}{RESET}"
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@@ -893,13 +871,13 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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# self.calculateStats(informative, 'sma5_deriv1', 'futur_percent_3')
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if self.dp.runmode.value in ('backtest'):
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informative['futur_percent'] = 100 * (informative['close'].shift(-1) - informative['close']) / informative['close']
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informative['futur_percent'] = 100 * (informative['close'].shift(-1) - informative['close']) / informative[
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'close']
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# informative['futur_percent_3d'] = 100 * (informative['close'].shift(-3) - informative['close']) / informative['close']
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#
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# self.calculateProbabilite2Index(informative, ['futur_percent_1d'], 'rsi_deriv1', 'rsi')
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# # self.calculateProbabilite2Index(dataframe, ['futur_percent_3d'], 'rsi_deriv1', 'sma5')
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# informative['close_smooth'] = self.conditional_smoothing(informative['mid'].dropna(), threshold=0.0015).dropna()
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# informative['smooth'], informative['deriv1'], informative['deriv2'] = self.smooth_and_derivatives(informative['close_smooth'])
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# informative['deriv1'] = 100 * informative['deriv1'] / informative['mid']
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@@ -1062,7 +1040,8 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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return dataframe
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def calculeDerivees(self, dataframe, indic, factor_1=100, factor_2=10, horizon=5):
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dataframe[f"{indic}_deriv1"] = (factor_1 * dataframe[f"{indic}"].diff() / dataframe[f"{indic}"]).rolling(horizon).mean()
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dataframe[f"{indic}_deriv1"] = (factor_1 * dataframe[f"{indic}"].diff() / dataframe[f"{indic}"]).rolling(
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horizon).mean()
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dataframe[f"{indic}_deriv2"] = (factor_2 * dataframe[f"{indic}_deriv1"].diff()).rolling(horizon).mean()
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def calculateDownAndUp(self, dataframe, limit=0.0001):
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@@ -1161,18 +1140,18 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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& (dataframe['max_rsi_24'] < 70)
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& (dataframe['open'] <= dataframe['bb_middleband'])
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# valid_inversion
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# ((dataframe['bb_cross_down'] < - 0.1)
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# | (dataframe['bb_cross_down'].shift(1) < - 0.1)
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# | (dataframe['bb_cross_down'].shift(2) < - 0.1)
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# | (dataframe['bb_cross_down'].shift(3) < - 0.1)
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# )
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# & (dataframe['hapercent'] > 0)
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# & (dataframe['close'] * factor < dataframe['bb_upperband5'])
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#
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#
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& (dataframe['mid_smooth_1h_deriv1'] >= 0)
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& (dataframe['mid_smooth_1h_deriv2'] >= 0)
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# valid_inversion
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# ((dataframe['bb_cross_down'] < - 0.1)
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# | (dataframe['bb_cross_down'].shift(1) < - 0.1)
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# | (dataframe['bb_cross_down'].shift(2) < - 0.1)
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# | (dataframe['bb_cross_down'].shift(3) < - 0.1)
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# )
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# & (dataframe['hapercent'] > 0)
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# & (dataframe['close'] * factor < dataframe['bb_upperband5'])
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#
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#
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& (dataframe['mid_smooth_1h_deriv1'] >= 0)
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& (dataframe['mid_smooth_1h_deriv2'] >= 0)
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# & (dataframe['mid_smooth_1h_deriv1'].shift(1) <= 0)
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# & (dataframe['mid_smooth_1h_deriv1'] >= dataframe['mid_smooth_1h_deriv1'].shift(1))
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), ['enter_long', 'enter_tag']] = (1, 'smth')
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@@ -1483,7 +1462,8 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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max_amount = self.config.get('stake_amount') * 2.5
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# stake_amount = min(stake_amount, self.wallets.get_available_stake_amount())
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stake_amount = min(min(max_amount, self.wallets.get_available_stake_amount()),
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self.adjust_stake_amount(pair, last_candle) - 10 * pct_first / self.mise_factor_buy.value) # min(200, self.adjust_stake_amount(pair, last_candle) * self.fibo[count_of_buys])
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self.adjust_stake_amount(pair,
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last_candle) - 10 * pct_first / self.mise_factor_buy.value) # min(200, self.adjust_stake_amount(pair, last_candle) * self.fibo[count_of_buys])
|
||||
|
||||
if self.wallets.get_available_stake_amount() > stake_amount:
|
||||
trade_type = last_candle['enter_tag'] if last_candle['enter_long'] == 1 else 'pct48'
|
||||
@@ -1539,7 +1519,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
|
||||
|
||||
last_lost = self.getLastLost(last_candle, pair)
|
||||
|
||||
if (hours > 6
|
||||
if (current_profit > 0 and hours > 6
|
||||
# and last_candle['sma60_deriv1'] > 0
|
||||
and last_candle['rsi_1h'] < 65
|
||||
and last_candle['rsi_deriv1_1h'] > 0
|
||||
@@ -1728,7 +1708,10 @@ class Zeus_8_3_2_B_4_2(IStrategy):
|
||||
# if last_candle['close'] < max_60:
|
||||
# pct_to_max = 0.25 * (max_60 - last_candle['close']) / max_60
|
||||
# pct_to_max = pct_to_max * (2 - pctClose60)
|
||||
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
|
||||
|
||||
@@ -2257,7 +2240,8 @@ class Zeus_8_3_2_B_4_2(IStrategy):
|
||||
# if not pair.startswith('BTC'):
|
||||
dispo = round(self.wallets.get_available_stake_amount())
|
||||
|
||||
if self.pairs[pair]['stop'] and last_candle['mid_smooth_5_deriv1_1d'] > -0.9 and last_candle['sma5_deriv1_1d'] > 0 and last_candle['sma5_deriv2_1d'] > 0:
|
||||
if self.pairs[pair]['stop'] and last_candle['mid_smooth_5_deriv1_1d'] > -0.9 and last_candle[
|
||||
'sma5_deriv1_1d'] > 0 and last_candle['sma5_deriv2_1d'] > 0:
|
||||
self.pairs[pair]['stop'] = False
|
||||
self.log_trade(
|
||||
last_candle=last_candle,
|
||||
@@ -2272,7 +2256,8 @@ class Zeus_8_3_2_B_4_2(IStrategy):
|
||||
stake=0
|
||||
)
|
||||
else:
|
||||
if self.pairs[pair]['stop'] == False and (last_candle['sma5_deriv1_1d'] < -0.2 or last_candle['sma5_deriv2_1d'] < -3):
|
||||
if self.pairs[pair]['stop'] == False and (
|
||||
last_candle['sma5_deriv1_1d'] < -0.2 or last_candle['sma5_deriv2_1d'] < -3):
|
||||
self.pairs[pair]['stop'] = True
|
||||
# if self.pairs[pair]['current_profit'] > 0:
|
||||
# self.pairs[pair]['force_sell'] = True
|
||||
@@ -2301,13 +2286,14 @@ class Zeus_8_3_2_B_4_2(IStrategy):
|
||||
if last_candle['sma5_deriv1_1h'] < 0.0 and last_candle['sma5_deriv2_1h'] < -0.0:
|
||||
return False
|
||||
|
||||
if last_candle['mid_smooth_1h_deriv1'] < 0.0 and last_candle['mid_smooth_1h_deriv2'] < -0.0 and last_candle['sma5_deriv2_1h'] < 0:
|
||||
if last_candle['mid_smooth_1h_deriv1'] < 0.0 and last_candle['mid_smooth_1h_deriv2'] < -0.0 and last_candle[
|
||||
'sma5_deriv2_1h'] < 0:
|
||||
return False
|
||||
|
||||
# if pair.startswith('BTC'):
|
||||
# return True # BTC toujours autorisé
|
||||
|
||||
#return True
|
||||
# return True
|
||||
|
||||
# Filtrer les paires non-BTC
|
||||
non_btc_pairs = [p for p in self.pairs if not p.startswith('BTC')]
|
||||
@@ -2346,7 +2332,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
|
||||
# or last_candle['sma5_deriv2_1d'] < -0.2:
|
||||
# return False
|
||||
|
||||
if last_candle['mid_smooth_1h_deriv1'] < -0.02: # and last_candle['mid_smooth_1h_deriv2'] > 0):
|
||||
if last_candle['mid_smooth_1h_deriv1'] < -0.02: # and last_candle['mid_smooth_1h_deriv2'] > 0):
|
||||
return False
|
||||
|
||||
# if self.pairs[pair]['count_of_buys'] >= 3:
|
||||
@@ -2371,7 +2357,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
|
||||
pct_max_max = self.getPctFirstBuy(max_pair, last_candle)
|
||||
# print(f"days_since_open {days_since_open} max_pair={max_pair} pair={pair}")
|
||||
return max_pair == pair or pct_max < - 0.25 or (
|
||||
pct_max_max < - 0.15 and max_pair != pair and days_since_open > 30)
|
||||
pct_max_max < - 0.15 and max_pair != pair and days_since_open > 30)
|
||||
else:
|
||||
return True
|
||||
|
||||
|
||||
Reference in New Issue
Block a user