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Calcul 2020-2025 4796 168$ mise moyenne profit

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Jérôme Delacotte
2025-05-16 21:56:14 +02:00
parent 0c849ebdd6
commit c0b02ef157
3 changed files with 5792 additions and 5086 deletions
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46
Zeus_8_3_2_B_4_2.py
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@@ -418,7 +418,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
baisse = self.pairs[pair]['max_profit'] - current_profit
mx = self.pairs[pair]['max_profit'] / 5
if (baisse > mx) & (current_profit > expected_profit): #last_candle['min_max200'] / 3):
if (baisse > mx) & (current_profit > expected_profit):
self.trades = list()
return 'mx_' + str(count_of_buys)
if (last_candle['percent12'] <= -0.01) & (current_profit >= expected_profit):
@@ -570,12 +570,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
dataframe['max200'] = talib.MAX(dataframe['close'], timeperiod=200)
dataframe['max50'] = talib.MAX(dataframe['close'], timeperiod=50)
dataframe['max144'] = talib.MAX(dataframe['close'], timeperiod=144)
dataframe['min_max50'] = (dataframe['max50'] - dataframe['min50']) / dataframe['min50']
dataframe['min_max200'] = (dataframe['max200'] - dataframe['min200']) / dataframe['min200']
dataframe['max200_diff'] = (dataframe['max200'] - dataframe['close']) / dataframe['close']
dataframe['max50_diff'] = (dataframe['max50'] - dataframe['close']) / dataframe['close']
dataframe['sma5'] = talib.SMA(dataframe, timeperiod=5)
dataframe['sma10'] = talib.SMA(dataframe, timeperiod=10)
@@ -589,12 +584,9 @@ class Zeus_8_3_2_B_4_2(IStrategy):
dataframe["percent3"] = (dataframe["close"] - dataframe["open"].shift(3)) / dataframe["open"].shift(3)
dataframe["percent5"] = (dataframe["close"] - dataframe["open"].shift(5)) / dataframe["open"].shift(5)
dataframe["percent12"] = (dataframe["close"] - dataframe["open"].shift(12)) / dataframe["open"].shift(12)
dataframe["percent24"] = (dataframe["close"] - dataframe["open"].shift(24)) / dataframe["open"].shift(24)
dataframe["percent48"] = (dataframe["close"] - dataframe["open"].shift(48)) / dataframe["open"].shift(48)
dataframe["percent_max_144"] = (dataframe["close"] - dataframe["max144"]) / dataframe["close"]
dataframe = self.calculateTendency(dataframe, window=12)
dataframe = self.calculateTendency(dataframe, window=144, suffixe="_144", factor_1=1000, factor_2=10)
dataframe = self.calculateTendency(dataframe, window=48, suffixe="_144", factor_1=1000, factor_2=10)
# print(metadata['pair'])
dataframe['rsi'] = talib.RSI(dataframe['close'], timeperiod=14)
@@ -1098,20 +1090,20 @@ class Zeus_8_3_2_B_4_2(IStrategy):
df = dataframe.copy()
regression_fit = []
deriv1 = []
deriv2 = []
# deriv1 = []
# deriv2 = []
regression_future_fit = []
regression_future_deriv1 = []
regression_future_deriv2 = []
# regression_future_deriv1 = []
# regression_future_deriv2 = []
for i in range(len(df)):
if i < window or i + future_offset >= len(df):
regression_fit.append(np.nan)
deriv1.append(np.nan)
deriv2.append(np.nan)
# deriv1.append(np.nan)
# deriv2.append(np.nan)
regression_future_fit.append(np.nan)
regression_future_deriv1.append(np.nan)
regression_future_deriv2.append(np.nan)
# regression_future_deriv1.append(np.nan)
# regression_future_deriv2.append(np.nan)
continue
y = df[column].iloc[i - window:i].values
@@ -1124,20 +1116,20 @@ class Zeus_8_3_2_B_4_2(IStrategy):
x_future = x_now + future_offset
regression_fit.append(poly(x_now))
deriv1.append(np.polyder(poly, 1)(x_now))
deriv2.append(np.polyder(poly, 2)(x_now))
# deriv1.append(np.polyder(poly, 1)(x_now))
# deriv2.append(np.polyder(poly, 2)(x_now))
regression_future_fit.append(poly(x_future))
regression_future_deriv1.append(np.polyder(poly, 1)(x_future))
regression_future_deriv2.append(np.polyder(poly, 2)(x_future))
# regression_future_deriv1.append(np.polyder(poly, 1)(x_future))
# regression_future_deriv2.append(np.polyder(poly, 2)(x_future))
df['regression_fit'] = regression_fit
df['regression_deriv1'] = deriv1
df['regression_deriv2'] = deriv2
# df['regression_fit'] = regression_fit
# df['regression_deriv1'] = deriv1
# df['regression_deriv2'] = deriv2
df['regression_future_fit'] = regression_future_fit
df['regression_future_deriv1'] = regression_future_deriv1
df['regression_future_deriv2'] = regression_future_deriv2
# df['regression_future_deriv1'] = regression_future_deriv1
# df['regression_future_deriv2'] = regression_future_deriv2
return df