12d235a1f1
Phase 1: - Real-time signal alerts (Discord/Telegram webhook) - Trading journal with entry/exit tracking - Position sizing calculator (Fixed/Kelly/ATR) Phase 2: - Pension asset allocation (DC/IRP 70% risk limit) - Drawdown monitoring with SVG gauge - Benchmark dashboard (portfolio vs KOSPI vs deposit) Phase 3: - Tax benefit simulation (Korean pension tax rules) - Correlation matrix heatmap - Parameter optimizer with grid search + overfit detection
54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
"""
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Trading journal models.
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"""
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import enum
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from datetime import datetime
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from sqlalchemy import (
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Column, Integer, String, Numeric, DateTime, Date,
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Text, Enum as SQLEnum, ForeignKey,
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)
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from sqlalchemy.orm import relationship
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from app.core.database import Base
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class TradeType(str, enum.Enum):
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BUY = "buy"
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SELL = "sell"
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class JournalStatus(str, enum.Enum):
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OPEN = "open"
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CLOSED = "closed"
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class TradeJournal(Base):
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__tablename__ = "trade_journals"
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id = Column(Integer, primary_key=True, index=True)
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user_id = Column(Integer, ForeignKey("users.id"), nullable=False, index=True)
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stock_code = Column(String(20), nullable=False, index=True)
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stock_name = Column(String(100))
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trade_type = Column(SQLEnum(TradeType), nullable=False)
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entry_price = Column(Numeric(12, 2))
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target_price = Column(Numeric(12, 2))
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stop_loss_price = Column(Numeric(12, 2))
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exit_price = Column(Numeric(12, 2))
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entry_date = Column(Date, nullable=False, index=True)
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exit_date = Column(Date)
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quantity = Column(Integer)
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profit_loss = Column(Numeric(14, 2))
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profit_loss_pct = Column(Numeric(8, 4))
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entry_reason = Column(Text)
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exit_reason = Column(Text)
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scenario = Column(Text)
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lessons_learned = Column(Text)
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emotional_state = Column(Text)
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strategy_id = Column(Integer)
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status = Column(SQLEnum(JournalStatus), default=JournalStatus.OPEN, index=True)
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created_at = Column(DateTime, default=datetime.utcnow)
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updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
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user = relationship("User", backref="trade_journals")
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