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
56 lines
1.4 KiB
Python
56 lines
1.4 KiB
Python
"""
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Benchmark comparison schemas.
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"""
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import enum
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from datetime import date
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from typing import List, Optional
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from pydantic import BaseModel, Field
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class BenchmarkType(str, enum.Enum):
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KOSPI = "kospi"
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DEPOSIT = "deposit"
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class PeriodType(str, enum.Enum):
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ONE_MONTH = "1m"
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THREE_MONTHS = "3m"
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SIX_MONTHS = "6m"
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ONE_YEAR = "1y"
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ALL = "all"
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class BenchmarkIndexInfo(BaseModel):
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code: str
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name: str
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description: str
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class TimeSeriesPoint(BaseModel):
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date: date
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portfolio_return: Optional[float] = None
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benchmark_return: Optional[float] = None
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deposit_return: Optional[float] = None
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class PerformanceMetrics(BaseModel):
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cumulative_return: float = Field(..., description="누적 수익률 (%)")
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annualized_return: float = Field(..., description="연환산 수익률 (%)")
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sharpe_ratio: Optional[float] = Field(None, description="샤프 비율")
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max_drawdown: float = Field(..., description="최대 낙폭 (%)")
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class BenchmarkCompareResponse(BaseModel):
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portfolio_name: str
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benchmark_type: str
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period: str
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start_date: date
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end_date: date
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time_series: List[TimeSeriesPoint]
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portfolio_metrics: PerformanceMetrics
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benchmark_metrics: PerformanceMetrics
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deposit_metrics: PerformanceMetrics
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alpha: float = Field(..., description="초과 수익률 (포트폴리오 - 벤치마크) (%)")
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information_ratio: Optional[float] = Field(None, description="정보 비율")
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