feat: trading bot MVP — ICT Order Block + Liquidity Sweep strategy

Full-stack trading bot with:
- FastAPI backend with ICT strategy (Order Block + Liquidity Sweep detection)
- Backtester engine with rolling window, spread simulation, and performance metrics
- Hybrid market data service (yfinance + TwelveData with rate limiting + SQLite cache)
- Simulated exchange for paper trading
- React/TypeScript frontend with TradingView lightweight-charts v5
- Live dashboard with candlestick chart, OHLC legend, trade markers
- Backtest page with configurable parameters, equity curve, and trade table
- WebSocket support for real-time updates
- Bot runner with asyncio loop for automated trading

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/core/strategy/base.py

@@ -0,0 +1,66 @@
+from abc import ABC, abstractmethod
+from dataclasses import dataclass, field
+from typing import Optional
+
+import pandas as pd
+
+
+@dataclass
+class OrderBlockZone:
+    """Zone Order Block à surveiller."""
+    id: str
+    direction: str          # "bullish" | "bearish"
+    top: float              # Haut de la zone
+    bottom: float           # Bas de la zone
+    origin_time: pd.Timestamp
+    mitigated: bool = False  # True si le prix a traversé la zone
+
+
+@dataclass
+class LiquidityLevel:
+    """Niveau de liquidité (Equal H/L)."""
+    id: str
+    direction: str          # "high" | "low"
+    price: float
+    origin_time: pd.Timestamp
+    swept: bool = False     # True si le prix a dépassé ce niveau
+
+
+@dataclass
+class TradeSignal:
+    """Signal de trading généré par la stratégie."""
+    direction: str          # "buy" | "sell"
+    entry_price: float
+    stop_loss: float
+    take_profit: float
+    signal_type: str        # description du setup
+    time: pd.Timestamp
+    order_block: Optional[OrderBlockZone] = None
+    liquidity_level: Optional[LiquidityLevel] = None
+
+
+@dataclass
+class AnalysisResult:
+    """Résultat complet de l'analyse de la stratégie."""
+    order_blocks: list[OrderBlockZone] = field(default_factory=list)
+    liquidity_levels: list[LiquidityLevel] = field(default_factory=list)
+    signals: list[TradeSignal] = field(default_factory=list)
+
+
+class AbstractStrategy(ABC):
+    """Interface commune pour toutes les stratégies."""
+
+    @abstractmethod
+    def analyze(self, df: pd.DataFrame) -> AnalysisResult:
+        """
+        Analyse un DataFrame de candles et retourne les zones,
+        niveaux de liquidité et signaux d'entrée.
+
+        df doit avoir les colonnes : time, open, high, low, close, volume
+        """
+        ...
+
+    @abstractmethod
+    def get_params(self) -> dict:
+        """Retourne les paramètres configurables de la stratégie."""
+        ...