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/LeveragedStrategy.py

@@ -0,0 +1,64 @@
+# pragma pylint: disable=missing-docstring, invalid-name, too-few-public-methods
+"""
+LeveragedStrategy — DÉMONSTRATION du risque du levier (NE PAS utiliser en réel).
+
+Même logique technique que SampleStrategy, mais en futures avec levier 10x.
+But : montrer empiriquement que le levier crée des semaines à +10 % ET des semaines
+catastrophiques — donc « +10 % chaque semaine » reste impossible, et le levier ruine.
+"""
+from __future__ import annotations
+
+import talib.abstract as ta
+from pandas import DataFrame
+
+from freqtrade.strategy import IStrategy
+
+
+class LeveragedStrategy(IStrategy):
+    INTERFACE_VERSION = 3
+    timeframe = "1h"
+    can_short = False
+
+    minimal_roi = {"0": 0.05, "120": 0.03, "360": 0.01, "720": 0}
+    stoploss = -0.10
+    trailing_stop = True
+    trailing_stop_positive = 0.02
+    trailing_stop_positive_offset = 0.03
+    trailing_only_offset_is_reached = True
+
+    startup_candle_count: int = 50
+    process_only_new_candles = True
+    use_exit_signal = True
+
+    def leverage(self, pair, current_time, current_rate, proposed_leverage,
+                 max_leverage, entry_tag, side, **kwargs) -> float:
+        return min(5.0, max_leverage)  # 5x
+
+    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