MidasBot: bot trading crypto IA + stratégies Ichimoku validées

- Infra: Freqtrade (futures dry-run) + Redis + dashboard + Docker Compose
- Couche IA: ai_analyzer (Claude via abonnement, MCP TradingView, backfill biais)
- Stratégies: SampleStrategy, AiBiasStrategy, IchimokuLS (long/short, validée
  train/test + données vierges + walk-forward), MTFIchimoku, variantes hyperopt
- Arbitrage CEX (dry-run), backtesting, walk-forward, volatility targeting
- IchimokuLS en dry-run live (config_live.json)

Claude-Session: https://claude.ai/code/session_01VHETcFacdnDhQzthLpdYFR

freqtrade/user_data/strategies/TrendMomentumStrategy.py

@@ -0,0 +1,68 @@
+# pragma pylint: disable=missing-docstring, invalid-name, too-few-public-methods
+"""
+TrendMomentumStrategy — tentative d'amélioration du rendement (vs SampleStrategy).
+
+Idée : n'entrer que sur des tendances confirmées et fortes (filtre EMA50 + ADX),
+laisser courir les gains (ROI plus haut + trailing), couper vite les perdants.
+Objectif : meilleur rendement ajusté du risque — PAS de promesse de +10 %/semaine.
+"""
+from __future__ import annotations
+
+import talib.abstract as ta
+from pandas import DataFrame
+
+from freqtrade.strategy import IStrategy
+
+
+class TrendMomentumStrategy(IStrategy):
+    INTERFACE_VERSION = 3
+    timeframe = "1h"
+
+    # Laisser courir : on vise des gains plus gros, on attend plus longtemps.
+    minimal_roi = {"0": 0.12, "240": 0.06, "720": 0.03, "1440": 0}
+    stoploss = -0.06  # on coupe vite les perdants
+    trailing_stop = True
+    trailing_stop_positive = 0.025
+    trailing_stop_positive_offset = 0.04
+    trailing_only_offset_is_reached = True
+
+    startup_candle_count: int = 60
+    process_only_new_candles = True
+    use_exit_signal = True
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe["ema_fast"] = ta.EMA(dataframe, timeperiod=9)
+        dataframe["ema_slow"] = ta.EMA(dataframe, timeperiod=21)
+        dataframe["ema_trend"] = ta.EMA(dataframe, timeperiod=50)
+        dataframe["adx"] = ta.ADX(dataframe, timeperiod=14)
+        dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
+        macd = ta.MACD(dataframe)
+        dataframe["macd"] = macd["macd"]
+        dataframe["macdsignal"] = macd["macdsignal"]
+        return dataframe
+
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                (dataframe["ema_fast"] > dataframe["ema_slow"])        # tendance courte haussière
+                & (dataframe["close"] > dataframe["ema_trend"])        # au-dessus tendance MT
+                & (dataframe["adx"] > 25)                              # tendance forte
+                & (dataframe["macd"] > dataframe["macdsignal"])        # momentum haussier
+                & (dataframe["rsi"] > 50)
+                & (dataframe["rsi"] < 75)                              # pas en surachat extrême
+                & (dataframe["volume"] > 0)
+            ),
+            "enter_long",
+        ] = 1
+        return dataframe
+
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                (dataframe["macd"] < dataframe["macdsignal"])          # momentum se retourne
+                & (dataframe["close"] < dataframe["ema_slow"])
+                & (dataframe["volume"] > 0)
+            ),
+            "exit_long",
+        ] = 1
+        return dataframe