feat: Add core trading modules for risk management, backtesting, and execution algorithms, alongside a new ML transparency widget and related frontend dependencies.

backend/core/schemas.py

@@ -46,6 +46,17 @@ class OrderCreate(BaseModel):
     price: Optional[Decimal] = None
     strategy_id: Optional[int] = None
     paper_trading: bool = True
+    # Advanced order parameters
+    take_profit_price: Optional[Decimal] = None
+    stop_loss_price: Optional[Decimal] = None
+    trail_percent: Optional[Decimal] = None  # For trailing stop (e.g., 0.02 for 2%)
+    # For bracket orders
+    bracket_take_profit: Optional[Decimal] = None
+    bracket_stop_loss: Optional[Decimal] = None
+    # For OCO orders
+    oco_price: Optional[Decimal] = None  # Second order price for OCO
+    # For iceberg orders
+    visible_quantity: Optional[Decimal] = None  # Visible quantity for iceberg
 
 
 class OrderResponse(BaseModel):
@@ -168,6 +179,36 @@ class BacktestRequest(BaseModel):
     fee_rate: float = 0.001
 
 
+class WalkForwardRequest(BaseModel):
+    """Walk-forward analysis request."""
+    strategy_id: int
+    symbol: str
+    exchange: str
+    timeframe: str
+    start_date: datetime
+    end_date: datetime
+    train_period_days: int = 90
+    test_period_days: int = 30
+    step_days: int = 30
+    initial_capital: Decimal = Decimal("10000.0")
+    parameter_grid: Optional[Dict[str, List[Any]]] = None
+    optimization_metric: str = "sharpe_ratio"
+
+
+class MonteCarloRequest(BaseModel):
+    """Monte Carlo simulation request."""
+    strategy_id: int
+    symbol: str
+    exchange: str
+    timeframe: str
+    start_date: datetime
+    end_date: datetime
+    initial_capital: Decimal = Decimal("10000.0")
+    num_simulations: int = 1000
+    parameter_ranges: Optional[Dict[str, List[float]]] = None  # {param_name: [min, max]}
+    random_seed: Optional[int] = None
+
+
 class BacktestResponse(BaseModel):
     """Backtest response."""
     backtest_id: Optional[int] = None