changement calcul expected profit à partir du 1er prix d'achat
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@@ -773,7 +773,7 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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dataframe.loc[
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dataframe.loc[
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(
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(
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(dataframe['low'] < dataframe['min200'])
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(dataframe['low'] < dataframe['min200'])
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& (dataframe['min50'] == dataframe['min200'].shift(3))
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& (dataframe['min50'] == dataframe['min50'].shift(3))
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# & (dataframe['tendency'] != "B--")
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# & (dataframe['tendency'] != "B--")
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# & (dataframe['tendency'] != "B-")
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# & (dataframe['tendency'] != "B-")
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), ['enter_long', 'enter_tag']] = (1, 'low')
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), ['enter_long', 'enter_tag']] = (1, 'low')
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@@ -965,21 +965,12 @@ class Zeus_8_3_2_B_4_2(IStrategy):
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# # Retourner le stoploss dynamique en pourcentage du prix actuel
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# # Retourner le stoploss dynamique en pourcentage du prix actuel
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# return (atr_stoploss / current_rate) - 1
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# return (atr_stoploss / current_rate) - 1
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def expectedProfit(self, pair: str, dataframe: DataFrame):
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def expectedProfit(self, pair: str, last_candle: DataFrame):
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current_price = dataframe['last_price'] # dataframe['close']
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first_price = last_candle['first_price']
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first_max = (last_candle['max200'] - first_price) / first_price
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# trade = self.getTrade(pair)
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expected_profit = min(0.01, first_max * 0.5)
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# if trade:
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# current_price = trade.open_rate
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# Calculer le max des 14 derniers jours
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min_14_days = dataframe['lowest_1d']
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max_14_days = dataframe['highest_1d']
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percent = (max_14_days - current_price) / (min_14_days)
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min_max = dataframe['pct_min_max_1d'] # (max_14_days - min_14_days) / min_14_days
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expected_profit = min(0.01, max(0.01, dataframe['min_max200'] * 0.5))
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# print(
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# print(
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# f"Expected profit price={current_price:.4f} min_max={min_max:.4f} min_14={min_14_days:.4f} max_14={max_14_days:.4f} percent={percent:.4f} expected_profit={expected_profit:.4f}")
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# f"Expected profit price={current_price:.4f} min_max={min_max:.4f} min_14={min_14_days:.4f} max_14={max_14_days:.4f} percent={percent:.4f} expected_profit={expected_profit:.4f}")
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