Frictrade

Frictrade.py

@@ -41,7 +41,7 @@ RESET = "\033[0m"
 
 
 class Frictrade(IStrategy):
-    startup_candle_count = 60 * 24
+    startup_candle_count = 180
 
     # ROI table:
     minimal_roi = {
@@ -103,6 +103,19 @@ class Frictrade(IStrategy):
     trades = list()
     max_profit_pairs = {}
 
+    btc_ath_history = [
+        {"date": "2011-06-09", "price_usd": 26.15, "note": "pic 2011 (early breakout)"},
+        {"date": "2013-11-29", "price_usd": 1132.00, "note": "bull run fin 2013"},
+        {"date": "2017-12-17", "price_usd": 19783.00, "note": "ATH décembre 2017 (crypto bubble)"},
+        {"date": "2020-12-31", "price_usd": 29001.72, "note": "fin 2020, nouveau record après accumulation)"},
+        {"date": "2021-11-10", "price_usd": 68742.00, "note": "record novembre 2021 (institutional demand)"},
+        {"date": "2024-03-05", "price_usd": 69000.00,
+         "note": "nouveau pic début 2024 (source presse, valeur indicative)"},
+        {"date": "2025-07-11", "price_usd": 118755.00, "note": "pic juillet 2025 (valeur rapportée par la presse)"},
+        {"date": "2025-10-06", "price_usd": 126198.07,
+         "note": "pic oct. 2025 (source agrégée, à vérifier selon l'exchange)"}
+    ]
+
     def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, time_in_force: str,
                             current_time: datetime, entry_tag: Optional[str], **kwargs) -> bool:
 
@@ -292,7 +305,7 @@ class Frictrade(IStrategy):
         if self.columns_logged % 10 == 0:
             self.printLog(
                 f"| {'Date':<16} | {'Action':<10} |{'Pair':<5}| {'Trade Type':<18} |{'Rate':>8} | {'Dispo':>6} | {'Profit':>8} "
-                f"| {'Pct':>6} | {'max_touch':>11} | {'last_lost':>12} | {'last_max':>7}| {'last_max':>7}|{'Buys':>5}| {'Stake':>5} |"
+                f"| {'Pct':>6} | {'max_touch':>11} | {'last_lost':>12} | {'last_max':>7}| {'last_min':>7}|{'Buys':>5}| {'Stake':>5} |"
                 f"{'rsi':>6}" #|Distmax|s201d|s5_1d|s5_2d|s51h|s52h|smt1h|smt2h|tdc1d|tdc1h"
             )
             self.printLineLog()
@@ -539,13 +552,18 @@ class Frictrade(IStrategy):
     #     return adjusted_stake_amount
 
     def adjust_stake_amount(self, pair: str, last_candle: DataFrame):
+
+        ath = max(self.pairs[pair]['last_max'], self.get_last_ath_before_candle(last_candle))
+
+        ath_dist = 100 * (ath - last_candle["mid"]) / ath
+
         # Calcule max/min 180
         low180 = last_candle["min180"]
         high180 = last_candle["max180"]
 
         mult = 1 - ((last_candle["mid"] - low180) / (high180 - low180))
 
-        print(f"low={low180} mid={last_candle['mid']} high={high180} mult={mult}")
+        print(f"low={low180} mid={last_candle['mid']} high={high180} mult={mult} ath={ath} ath_dist={round(ath_dist, 2)}" )
         # base_size = montant de base que tu veux utiliser (ex: stake_amount ou autre)
         base_size = 2 * self.config.get('stake_amount')  # exemple fraction du portefeuille; adapte selon ton code
         # new stake proportionnel à mult
@@ -612,7 +630,7 @@ class Frictrade(IStrategy):
         #     stake_amount = last_amount * current_rate * 0.5
         #     return stake_amount
 
-        condition = last_candle['hapercent'] > 0 and last_candle['sma60_deriv1'] > 0
+        condition = last_candle['hapercent'] > 0 and last_candle['sma24_deriv1'] > 0
         limit_buy = 40
         if decline >= dca_threshold and condition:
             try:
@@ -760,11 +778,11 @@ class Frictrade(IStrategy):
         if zone == 0:
             current_trailing_stop_positive = self.trailing_stop_positive
             current_trailing_stop_positive_offset = self.trailing_stop_positive_offset * 2
+        if minutes > 1440:
+            current_trailing_only_offset_is_reached = False
+            current_trailing_stop_positive_offset = self.trailing_stop_positive_offset
         # if zone == 1:
 
-
-        if last_candle['sma24_deriv1'] > 0: # and last_candle['sma5_deriv1'] > -0.15:
-            return None
         # ----- 5) Calcul du trailing stop dynamique -----
         # Exemple : offset=0.321 => stop à +24.8%
 
@@ -773,7 +791,7 @@ class Frictrade(IStrategy):
         if max_profit:
             baisse = (max_profit - profit) / max_profit
 
-        if minutes % 15 == 0:
+        if minutes % 12 == 0:
             self.log_trade(
                 last_candle=last_candle,
                 date=current_time,
@@ -781,12 +799,15 @@ class Frictrade(IStrategy):
                 dispo=dispo,
                 pair=pair,
                 rate=last_candle['close'],
-                trade_type=f"{round(profit, 2)} {round(max_profit, 2)} {round(trailing_stop,2)}",
+                trade_type=f"{round(profit, 2)} {round(max_profit, 2)} {round(trailing_stop,2)} {minutes}",
                 profit=round(profit, 2),
                 buys=count_of_buys,
                 stake=0
             )
 
+        if last_candle['sma24_deriv1'] > 0 and minutes < 180: # and last_candle['sma5_deriv1'] > -0.15:
+            return None
+
         # ----- 4) OFFSET : faut-il attendre de dépasser trailing_stop_positive_offset ? -----
         if current_trailing_only_offset_is_reached:
             # Max profit pas atteint ET perte < 2 * current_trailing_stop_positive
@@ -797,7 +818,7 @@ class Frictrade(IStrategy):
 
         # ----- 6) Condition de vente -----
         if profit > 0 and profit <= trailing_stop and last_candle['mid'] < last_candle['sma5']:
-            return f"stop_{count_of_buys}"
+            return f"stop_{count_of_buys}_{self.pairs[pair]['has_gain']}"
         return None
 
     def informative_pairs(self):
@@ -892,3 +913,19 @@ class Frictrade(IStrategy):
 
         return dataframe
 
+    import pandas as pd
+
+    def to_utc_ts(self, x):
+        return pd.to_datetime(x, utc=True)
+
+    # suppose self.btc_ath_history exists (liste de dict)
+    def get_last_ath_before_candle(self, last_candle):
+        candle_date = self.to_utc_ts(last_candle['date'])  # ou to_utc_ts(last_candle.name)
+        best = None
+        for a in self.btc_ath_history: #getattr(self, "btc_ath_history", []):
+            ath_date = self.to_utc_ts(a["date"])
+            if ath_date <= candle_date:
+                if best is None or ath_date > best[0]:
+                    best = (ath_date, a["price_usd"])
+        return best[1] if best is not None else None
+