Calcul 20210101-20250714 971.767 300.846$ => 13,21 max 11 mises ETH / 7 mises BTC

Zeus_8_3_2_B_4_2.py

@@ -1052,7 +1052,7 @@ 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))
@@ -1360,11 +1360,12 @@ class Zeus_8_3_2_B_4_2(IStrategy):
         return adjusted_stake_amount
 
     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 / 10))  # 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}")