galaxis-po/backend/app/schemas/backtest.py

"""
Backtest related Pydantic schemas.
"""
from datetime import date, datetime
from decimal import Decimal
from typing import Optional, List, Dict, Any
from enum import Enum

from pydantic import BaseModel, Field

from app.schemas.portfolio import FloatDecimal


class RebalancePeriod(str, Enum):
    MONTHLY = "monthly"
    QUARTERLY = "quarterly"
    SEMI_ANNUAL = "semi_annual"
    ANNUAL = "annual"


class BacktestStatus(str, Enum):
    PENDING = "pending"
    RUNNING = "running"
    COMPLETED = "completed"
    FAILED = "failed"


class BacktestCreate(BaseModel):
    """Request to create a new backtest."""
    strategy_type: str = Field(..., description="multi_factor, quality, value_momentum, or kjb")
    strategy_params: Dict[str, Any] = Field(default_factory=dict)
    start_date: date
    end_date: date
    rebalance_period: RebalancePeriod = RebalancePeriod.QUARTERLY
    initial_capital: Decimal = Field(default=Decimal("100000000"), gt=0)
    commission_rate: Decimal = Field(default=Decimal("0.00015"), ge=0, le=1)
    slippage_rate: Decimal = Field(default=Decimal("0.001"), ge=0, le=1)
    benchmark: str = Field(default="KOSPI")
    top_n: int = Field(default=30, ge=1, le=100)


class BacktestMetrics(BaseModel):
    """Backtest result metrics."""
    total_return: FloatDecimal
    cagr: FloatDecimal
    mdd: FloatDecimal
    sharpe_ratio: FloatDecimal
    volatility: FloatDecimal
    benchmark_return: FloatDecimal
    excess_return: FloatDecimal


class BacktestResponse(BaseModel):
    """Backtest response with status and optional results."""
    id: int
    user_id: int
    strategy_type: str
    strategy_params: Dict[str, Any]
    start_date: date
    end_date: date
    rebalance_period: str
    initial_capital: FloatDecimal
    commission_rate: FloatDecimal
    slippage_rate: FloatDecimal
    benchmark: str
    status: str
    created_at: datetime
    completed_at: Optional[datetime] = None
    error_message: Optional[str] = None
    result: Optional[BacktestMetrics] = None

    class Config:
        from_attributes = True


class BacktestListItem(BaseModel):
    """Backtest item for list view."""
    id: int
    strategy_type: str
    start_date: date
    end_date: date
    rebalance_period: str
    status: str
    created_at: datetime
    total_return: Optional[FloatDecimal] = None
    cagr: Optional[FloatDecimal] = None
    mdd: Optional[FloatDecimal] = None

    class Config:
        from_attributes = True


class EquityCurvePoint(BaseModel):
    """Single point in equity curve."""
    date: date
    portfolio_value: FloatDecimal
    benchmark_value: FloatDecimal
    drawdown: FloatDecimal

    class Config:
        from_attributes = True


class HoldingItem(BaseModel):
    """Single holding at a rebalance date."""
    ticker: str
    name: str
    weight: FloatDecimal
    shares: int
    price: FloatDecimal


class RebalanceHoldings(BaseModel):
    """Holdings at a specific rebalance date."""
    rebalance_date: date
    holdings: List[HoldingItem]


class TransactionItem(BaseModel):
    """Single transaction."""
    id: int
    date: date
    ticker: str
    name: str | None = None
    action: str
    shares: int
    price: FloatDecimal
    commission: FloatDecimal

    class Config:
        from_attributes = True


class WalkForwardRequest(BaseModel):
    """Request to run walk-forward analysis."""
    train_months: int = Field(default=12, ge=3, le=60)
    test_months: int = Field(default=3, ge=1, le=24)
    step_months: int = Field(default=3, ge=1, le=24)


class WalkForwardWindowResult(BaseModel):
    """Single walk-forward window result."""
    window_index: int
    train_start: date
    train_end: date
    test_start: date
    test_end: date
    test_return: FloatDecimal | None = None
    test_sharpe: FloatDecimal | None = None
    test_mdd: FloatDecimal | None = None

    class Config:
        from_attributes = True


class WalkForwardResponse(BaseModel):
    """Walk-forward analysis results."""
    backtest_id: int
    windows: List[WalkForwardWindowResult]