4483f6e4ba
Add dc_only parameter to all strategy endpoints. When true, filters results to include only tickers present in the ETF table, supporting DC pension investment constraints where only ETFs are allowed. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
141 lines
3.7 KiB
Python
141 lines
3.7 KiB
Python
"""
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Quant strategy related Pydantic schemas.
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"""
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from datetime import date
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from decimal import Decimal
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from typing import Optional, List, Dict
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from pydantic import BaseModel, Field
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from app.schemas.portfolio import FloatDecimal
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class FactorWeights(BaseModel):
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"""Factor weights for multi-factor strategy."""
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value: FloatDecimal = Field(default=Decimal("0.25"), ge=0, le=1)
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quality: FloatDecimal = Field(default=Decimal("0.25"), ge=0, le=1)
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momentum: FloatDecimal = Field(default=Decimal("0.25"), ge=0, le=1)
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low_vol: FloatDecimal = Field(default=Decimal("0.25"), ge=0, le=1)
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class UniverseFilter(BaseModel):
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"""Stock universe filtering criteria."""
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markets: List[str] = ["KOSPI", "KOSDAQ"]
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min_market_cap: Optional[int] = None # in 억원
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max_market_cap: Optional[int] = None
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exclude_stock_types: List[str] = ["spac", "preferred", "reit"]
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exclude_sectors: List[str] = []
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class StrategyRequest(BaseModel):
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"""Base request for running a strategy."""
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universe: UniverseFilter = UniverseFilter()
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top_n: int = Field(default=30, ge=1, le=100)
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base_date: Optional[date] = None
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dc_only: bool = False
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class MultiFactorRequest(StrategyRequest):
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"""Multi-factor strategy request."""
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weights: FactorWeights = FactorWeights()
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class QualityRequest(StrategyRequest):
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"""Super Quality strategy request."""
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min_fscore: int = Field(default=7, ge=0, le=9)
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class ValueMomentumRequest(StrategyRequest):
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"""Value-Momentum strategy request."""
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value_weight: FloatDecimal = Field(default=Decimal("0.5"), ge=0, le=1)
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momentum_weight: FloatDecimal = Field(default=Decimal("0.5"), ge=0, le=1)
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class KJBRequest(StrategyRequest):
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"""KJB strategy request."""
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pass
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class StockFactor(BaseModel):
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"""Factor scores for a single stock."""
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ticker: str
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name: str
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market: str
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sector_name: Optional[str] = None
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market_cap: Optional[int] = None
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close_price: Optional[FloatDecimal] = None
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# Raw metrics
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per: Optional[FloatDecimal] = None
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pbr: Optional[FloatDecimal] = None
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psr: Optional[FloatDecimal] = None
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pcr: Optional[FloatDecimal] = None
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dividend_yield: Optional[FloatDecimal] = None
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roe: Optional[FloatDecimal] = None
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# Factor scores (z-scores)
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value_score: Optional[FloatDecimal] = None
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quality_score: Optional[FloatDecimal] = None
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momentum_score: Optional[FloatDecimal] = None
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# Composite
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total_score: Optional[FloatDecimal] = None
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rank: Optional[int] = None
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fscore: Optional[int] = None
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class StrategyResult(BaseModel):
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"""Result from running a strategy."""
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strategy_name: str
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base_date: date
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universe_count: int
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result_count: int
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stocks: List[StockFactor]
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class StockInfo(BaseModel):
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"""Detailed stock information."""
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ticker: str
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name: str
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market: str
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sector_name: Optional[str] = None
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stock_type: str
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close_price: Optional[FloatDecimal] = None
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market_cap: Optional[int] = None
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# Valuation
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per: Optional[FloatDecimal] = None
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pbr: Optional[FloatDecimal] = None
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psr: Optional[FloatDecimal] = None
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pcr: Optional[FloatDecimal] = None
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dividend_yield: Optional[FloatDecimal] = None
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# Per-share data
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eps: Optional[FloatDecimal] = None
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bps: Optional[FloatDecimal] = None
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base_date: Optional[date] = None
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class Config:
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from_attributes = True
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class StockSearchResult(BaseModel):
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"""Stock search result."""
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ticker: str
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name: str
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market: str
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class PriceData(BaseModel):
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"""Price data point."""
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date: date
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open: FloatDecimal
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high: FloatDecimal
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low: FloatDecimal
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close: FloatDecimal
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volume: int
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class Config:
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from_attributes = True
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