DaM
f85c522f22
- Implemented portfolio engine with risk-based allocation (50/50) - Added equity-based metrics for system-level evaluation - Validated portfolio against standalone strategies - Reduced max drawdown and volatility at system level - Quantitative decision closed before paper trading phase
71 lines
1.9 KiB
Python
71 lines
1.9 KiB
Python
# src/risk/stops/trailing_stop.py
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import pandas as pd
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from src.risk.stops.base import StopLoss
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from src.core.trade import TradeType, Position
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class TrailingStop(StopLoss):
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"""
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Trailing Stop porcentual basado en el precio de cierre.
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- LONG: el stop solo sube
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- SHORT: el stop solo baja
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"""
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def __init__(self, trailing_fraction: float):
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"""
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Args:
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trailing_fraction: ej 0.05 = 5%
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"""
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if trailing_fraction <= 0 or trailing_fraction >= 1:
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raise ValueError("trailing_fraction debe estar entre 0 y 1")
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self.trailing_fraction = trailing_fraction
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def get_stop_price(
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self,
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*,
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data: pd.DataFrame,
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idx: int,
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entry_price: float,
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trade_type: TradeType
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) -> float:
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"""
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Stop inicial al abrir la posición
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"""
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if trade_type == TradeType.LONG:
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return entry_price * (1 - self.trailing_fraction)
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elif trade_type == TradeType.SHORT:
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return entry_price * (1 + self.trailing_fraction)
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else:
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raise ValueError(f"TradeType no soportado: {trade_type}")
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def update_stop(
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self,
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*,
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data: pd.DataFrame,
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idx: int,
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position: Position
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) -> float | None:
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"""
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Calcula un nuevo stop si el precio ha mejorado.
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Devuelve None si el stop no debe moverse.
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"""
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current_price = data.iloc[idx]["close"]
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if position.trade_type == TradeType.LONG:
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candidate = current_price * (1 - self.trailing_fraction)
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if position.stop_price is None or candidate > position.stop_price:
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return candidate
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elif position.trade_type == TradeType.SHORT:
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candidate = current_price * (1 + self.trailing_fraction)
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if position.stop_price is None or candidate < position.stop_price:
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return candidate
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return None
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