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/SampleStrategy.py

@@ -0,0 +1,75 @@
+# pragma pylint: disable=missing-docstring, invalid-name, too-few-public-methods
+"""
+SampleStrategy — stratégie de base MidasBot (Phase 1).
+
+Croisement de moyennes mobiles exponentielles (EMA) avec filtre RSI.
+Sert à valider le pipeline Freqtrade (dry-run, backtesting, FreqUI) avant
+d'ajouter la couche IA (cf. AiBiasStrategy, Phase 3).
+"""
+from __future__ import annotations
+
+import talib.abstract as ta
+from pandas import DataFrame
+
+from freqtrade.strategy import IStrategy
+
+
+class SampleStrategy(IStrategy):
+    INTERFACE_VERSION = 3
+
+    # Timeframe d'analyse
+    timeframe = "1h"
+
+    # Take-profit échelonné (ROI minimal par durée, en minutes)
+    minimal_roi = {
+        "0": 0.05,
+        "120": 0.03,
+        "360": 0.01,
+        "720": 0,
+    }
+
+    # Stop-loss dur
+    stoploss = -0.10
+
+    # Trailing stop
+    trailing_stop = True
+    trailing_stop_positive = 0.02
+    trailing_stop_positive_offset = 0.03
+    trailing_only_offset_is_reached = True
+
+    # Nombre de bougies nécessaires avant de produire un signal
+    startup_candle_count: int = 50
+
+    # Ordres
+    process_only_new_candles = True
+    use_exit_signal = True
+    exit_profit_only = False
+
+    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["rsi"] = ta.RSI(dataframe, timeperiod=14)
+        return dataframe
+
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                (dataframe["ema_fast"] > dataframe["ema_slow"])
+                & (dataframe["ema_fast"].shift(1) <= dataframe["ema_slow"].shift(1))
+                & (dataframe["rsi"] < 70)
+                & (dataframe["volume"] > 0)
+            ),
+            "enter_long",
+        ] = 1
+        return dataframe
+
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                (dataframe["ema_fast"] < dataframe["ema_slow"])
+                & (dataframe["ema_fast"].shift(1) >= dataframe["ema_slow"].shift(1))
+                & (dataframe["volume"] > 0)
+            ),
+            "exit_long",
+        ] = 1
+        return dataframe