Calcul 20240101-20250714 4061.673 280.29$ Max 8

Zeus_8_3_2_B_4_2.py

@@ -1101,15 +1101,15 @@ class Zeus_8_3_2_B_4_2(IStrategy):
                 pct_max = - pct
 
         if pair in ('BTC/USDT', 'BTC/USDC') or count_of_buys <= 2:
-            lim = - pct - (count_of_buys * 0.001)
+            lim = - pct - (count_of_buys * 0.003)
             #lim = self.getLimitBuy(pair, last_candle, pct)
             # lim = - (0.012 * (1 + round(count_of_buys / 5)) + 0.001 * (count_of_buys - 1))
             # lim = - (0.012 + 0.001 * (count_of_buys - 1) + (0.002 * count_of_buys if count_of_buys > 10 else 0.001 * count_of_buys if count_of_buys > 5 else 0))
 
         else:
-            pct = 0.05
-            lim = - pct - (count_of_buys * 0.005)
-            #lim = self.getLimitBuy(pair, last_candle, pct)
+            pct = 0.025
+            # lim = - pct - (count_of_buys * 0.001)
+            lim = self.getLimitBuy(pair, last_candle, pct)
 
         if (len(dataframe) < 1):
             print("skip dataframe")
@@ -1387,21 +1387,34 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         # Calculer le minimum des 14 derniers jours
         base_stake_amount = self.config.get('stake_amount')  # Montant de base configuré
 
-        if not pair in ('BTC/USDT', 'BTC/USDC'):
-            # factors = [1, 1.2, 1.3, 1.4]
-            adjusted_stake_amount = base_stake_amount
-        else :
-            first_price = self.pairs[pair]['first_buy']
-            if (first_price == 0):
-                first_price = last_candle['close']
+        # last_candle['max60_1d'] - last_candle['min60_1d']
+        last_max = self.pairs[pair]['last_max']
+        last_min = self.pairs[pair]['last_min']
 
-            last_max = last_candle['max12_1d']
-            pct = 5
-            if last_max > 0:
-                pct = 100 * (last_max - first_price) / last_max
+        ecart = 1
+        if (last_max > 0 and last_min > 0):
+            ecart = 1 + (last_max - last_min) / last_max
 
-            factor = self.multi_step_interpolate(pct, self.thresholds, self.factors)
-            adjusted_stake_amount = base_stake_amount * factor  # max(base_stake_amount, min(100, base_stake_amount * percent_4))
+        adjusted_stake_amount = base_stake_amount * ecart
+
+        # if not pair in ('BTC/USDT', 'BTC/USDC'):
+        #     # factors = [1, 1.2, 1.3, 1.4]
+        #     adjusted_stake_amount = base_stake_amount
+        # else :
+        #     # full = self.wallets.get_total_stake_amount()
+        #     # base_stake_amount = min(100, full / self.stakes)
+        #
+        #     first_price = self.pairs[pair]['first_buy']
+        #     if (first_price == 0):
+        #         first_price = last_candle['close']
+        #
+        #     last_max = last_candle['max12_1d']
+        #     pct = 5
+        #     if last_max > 0:
+        #         pct = 100 * (last_max - first_price) / last_max
+        #
+        #     factor = self.multi_step_interpolate(pct, self.thresholds, self.factors)
+        #     adjusted_stake_amount = base_stake_amount * factor  # max(base_stake_amount, min(100, base_stake_amount * percent_4))
 
         # pct = 100 * abs(self.getPctFirstBuy(pair, last_candle))
         #
@@ -1453,11 +1466,12 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         return out_max - position * (out_max - out_min)
 
     def expectedProfit(self, pair: str, last_candle: DataFrame):
+        pct_to_max = 0.004
+        max_60 = last_candle['max60_1d']
+        if last_candle['close'] < max_60:
+            pct_to_max = 0.25 * (max_60 - last_candle['close']) / max_60
 
-        count_of_buys = self.pairs[pair]['count_of_buys']
-        pct_first = self.getPctFirstBuy(pair, last_candle)
-
-        expected_profit = max(0.004, abs(pct_first / 3))  # 0.004 + 0.002 * self.pairs[pair]['count_of_buys'] #min(0.01, first_max)
+        expected_profit = pct_to_max # 0.004 + 0.002 * self.pairs[pair]['count_of_buys'] #min(0.01, first_max)
 
         # print(
         #     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}")
@@ -1975,11 +1989,11 @@ class Zeus_8_3_2_B_4_2(IStrategy):
 
         limit = 3
 
-        if pair.startswith('BTC'):
+        if pair.startswith('BTC') or self.pairs[pair]['count_of_buys'] == 0:
             return True  # BTC toujours autorisé
 
             # Filtrer les paires non-BTC
-        non_btc_pairs = [p for p in self.pairs if not p.startswith('BTC')]
+        non_btc_pairs = [p for p in self.pairs] # if not p.startswith('BTC')]
 
         # Compter les positions actives sur les paires non-BTC
         max_nb_trades = 0
@@ -1991,11 +2005,11 @@ class Zeus_8_3_2_B_4_2(IStrategy):
                 max_pair = p
             total_non_btc += self.pairs[p]['count_of_buys']
 
-        pct_max = self.getPctFirstBuy(pair, last_candle) #self.getPctLastBuy(pair, last_candle)
+        pct_max = self.getPctLastBuy(pair, last_candle)
 
-        val = self.getProbaHausseSma5d(last_candle)
-        if (val < 15):
-            return False
+        # val = self.getProbaHausse(last_candle)
+        # if (val < 40):
+        #     return False
 
         # if count_decrease == len(non_btc_pairs):
         #     self.should_enter_trade_count += 1
@@ -2006,6 +2020,6 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         self.should_enter_trade_count = 0
 
         if max_pair != '' :
-            return max_pair == pair or pct_max < - 0.25
+            return (max_pair == pair and self.pairs[pair]['count_of_buys'] <= 5) or pct_max < - 0.1
         else:
             return True