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/models/backtest_result.py

@@ -0,0 +1,32 @@
+from datetime import datetime
+from typing import Optional
+
+from sqlalchemy import Float, Integer, String, DateTime, JSON
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.core.database import Base
+
+
+class BacktestResult(Base):
+    __tablename__ = "backtest_results"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    instrument: Mapped[str] = mapped_column(String(20))
+    granularity: Mapped[str] = mapped_column(String(10))
+    start_date: Mapped[datetime] = mapped_column(DateTime)
+    end_date: Mapped[datetime] = mapped_column(DateTime)
+    initial_balance: Mapped[float] = mapped_column(Float, default=10000.0)
+    final_balance: Mapped[float] = mapped_column(Float)
+    total_pnl: Mapped[float] = mapped_column(Float)
+    total_trades: Mapped[int] = mapped_column(Integer)
+    winning_trades: Mapped[int] = mapped_column(Integer)
+    losing_trades: Mapped[int] = mapped_column(Integer)
+    win_rate: Mapped[float] = mapped_column(Float)
+    max_drawdown: Mapped[float] = mapped_column(Float)
+    sharpe_ratio: Mapped[Optional[float]] = mapped_column(Float, nullable=True)
+    expectancy: Mapped[float] = mapped_column(Float)
+    # Courbe d'équité [{time, balance}] stockée en JSON
+    equity_curve: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True)
+    # Paramètres de la stratégie utilisés
+    strategy_params: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True)
+    created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)

backend/app/models/candle.py

@@ -0,0 +1,25 @@
+from datetime import datetime
+
+from sqlalchemy import Float, Integer, String, DateTime, UniqueConstraint
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.core.database import Base
+
+
+class Candle(Base):
+    __tablename__ = "candles"
+    __table_args__ = (
+        # Garantit INSERT OR IGNORE sur (instrument, granularity, time)
+        UniqueConstraint("instrument", "granularity", "time", name="uq_candle"),
+    )
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    instrument: Mapped[str] = mapped_column(String(20), index=True)
+    granularity: Mapped[str] = mapped_column(String(10))
+    time: Mapped[datetime] = mapped_column(DateTime, index=True)
+    open: Mapped[float] = mapped_column(Float)
+    high: Mapped[float] = mapped_column(Float)
+    low: Mapped[float] = mapped_column(Float)
+    close: Mapped[float] = mapped_column(Float)
+    volume: Mapped[int] = mapped_column(Integer, default=0)
+    complete: Mapped[bool] = mapped_column(default=True)

backend/app/models/trade.py

@@ -0,0 +1,34 @@
+from datetime import datetime
+from typing import Optional
+
+from sqlalchemy import Float, Integer, String, DateTime
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.core.database import Base
+
+
+class Trade(Base):
+    __tablename__ = "trades"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    # "live" | "backtest"
+    source: Mapped[str] = mapped_column(String(10), default="live")
+    # identifiant OANDA du trade live (si applicable)
+    oanda_trade_id: Mapped[Optional[str]] = mapped_column(String(50), nullable=True)
+    instrument: Mapped[str] = mapped_column(String(20), index=True)
+    # "buy" | "sell"
+    direction: Mapped[str] = mapped_column(String(4))
+    units: Mapped[float] = mapped_column(Float)
+    entry_price: Mapped[float] = mapped_column(Float)
+    stop_loss: Mapped[float] = mapped_column(Float)
+    take_profit: Mapped[float] = mapped_column(Float)
+    exit_price: Mapped[Optional[float]] = mapped_column(Float, nullable=True)
+    pnl: Mapped[Optional[float]] = mapped_column(Float, nullable=True)
+    # "open" | "closed" | "cancelled"
+    status: Mapped[str] = mapped_column(String(10), default="open")
+    # Signal ayant déclenché le trade
+    signal_type: Mapped[Optional[str]] = mapped_column(String(50), nullable=True)
+    opened_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
+    closed_at: Mapped[Optional[datetime]] = mapped_column(DateTime, nullable=True)
+    # ID du backtest parent (si applicable)
+    backtest_id: Mapped[Optional[int]] = mapped_column(Integer, nullable=True, index=True)