87 lines
2.7 KiB
Python
87 lines
2.7 KiB
Python
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"""
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Correlation analysis API endpoints.
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"""
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from fastapi import APIRouter, Depends, HTTPException
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from sqlalchemy.orm import Session
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from app.core.database import get_db
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from app.api.deps import CurrentUser
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from app.schemas.correlation import (
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CorrelationMatrixRequest,
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CorrelationMatrixResponse,
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DiversificationResponse,
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HighCorrelationPair,
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)
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from app.services.correlation import CorrelationService
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router = APIRouter(prefix="/api/correlation", tags=["correlation"])
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@router.post("/matrix", response_model=CorrelationMatrixResponse)
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async def calculate_correlation_matrix(
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request: CorrelationMatrixRequest,
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current_user: CurrentUser,
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db: Session = Depends(get_db),
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):
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"""종목 간 수익률 상관 행렬 계산."""
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service = CorrelationService(db)
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result = service.get_correlation_data(request.stock_codes, request.period_days)
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return CorrelationMatrixResponse(
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stock_codes=result["stock_codes"],
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matrix=result["matrix"],
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high_correlation_pairs=[
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HighCorrelationPair(**p) for p in result["high_correlation_pairs"]
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],
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)
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@router.get("/portfolio/{portfolio_id}", response_model=DiversificationResponse)
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async def get_portfolio_diversification(
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portfolio_id: int,
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current_user: CurrentUser,
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db: Session = Depends(get_db),
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):
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"""포트폴리오 분산 효과 점수 조회."""
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service = CorrelationService(db)
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try:
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score = service.calculate_portfolio_diversification(portfolio_id)
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except ValueError as e:
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raise HTTPException(status_code=404, detail=str(e))
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# Get holdings for correlation data
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from app.models.portfolio import Portfolio, PortfolioSnapshot
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portfolio = db.query(Portfolio).filter(
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Portfolio.id == portfolio_id,
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Portfolio.user_id == current_user.id,
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).first()
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if not portfolio:
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raise HTTPException(status_code=404, detail="Portfolio not found")
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snapshot = (
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db.query(PortfolioSnapshot)
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.filter(PortfolioSnapshot.portfolio_id == portfolio_id)
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.order_by(PortfolioSnapshot.snapshot_date.desc())
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.first()
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)
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high_pairs = []
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stock_count = 0
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if snapshot and snapshot.holdings:
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tickers = [h.ticker for h in snapshot.holdings]
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stock_count = len(tickers)
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if len(tickers) >= 2:
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corr_data = service.get_correlation_data(tickers, period_days=60)
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high_pairs = [
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HighCorrelationPair(**p) for p in corr_data["high_correlation_pairs"]
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]
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return DiversificationResponse(
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portfolio_id=portfolio_id,
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diversification_score=score,
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stock_count=stock_count,
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high_correlation_pairs=high_pairs,
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)
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