91 lines
2.6 KiB
Python
91 lines
2.6 KiB
Python
# src/strategies/rsi_strategy.py
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"""
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Estrategia basada en RSI
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"""
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import pandas as pd
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from ..core.strategy import Strategy, Signal, calculate_rsi
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class RSIStrategy(Strategy):
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"""
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Estrategia basada en RSI (Relative Strength Index)
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Señales:
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- BUY: Cuando RSI < oversold_threshold (mercado sobrevendido)
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- SELL: Cuando RSI > overbought_threshold (mercado sobrecomprado)
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- HOLD: RSI en zona neutral
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Parámetros:
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rsi_period: Periodo del RSI (default: 14)
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oversold_threshold: Umbral de sobreventa (default: 30)
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overbought_threshold: Umbral de sobrecompra (default: 70)
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"""
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strategy_id = "rsi"
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def __init__(self, rsi_period: int = 14, oversold_threshold: float = 30, overbought_threshold: float = 70):
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params = {
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'rsi_period': rsi_period,
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'oversold': oversold_threshold,
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'overbought': overbought_threshold
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}
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super().__init__(name="RSI Strategy", params=params)
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self.rsi_period = rsi_period
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self.oversold = oversold_threshold
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self.overbought = overbought_threshold
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@classmethod
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def parameters_schema(cls) -> dict:
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return {
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"rsi_period": {
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"type": "int",
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"min": 1,
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"max": 200,
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"default": 14,
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},
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"oversold": {
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"type": "float",
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"min": 0,
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"max": 100,
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"default": 30,
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},
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"overbought": {
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"type": "float",
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"min": 0,
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"max": 100,
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"default": 70,
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},
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}
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def init_indicators(self, data: pd.DataFrame) -> pd.DataFrame:
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"""
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Calcula el RSI
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"""
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data['rsi'] = calculate_rsi(data['close'], self.rsi_period)
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return data
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def generate_signal(self, idx: int) -> Signal:
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"""
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Genera señal basada en niveles de RSI
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"""
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if self.data is None:
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raise ValueError("Data no establecida")
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rsi = self.data.iloc[idx]['rsi']
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# Verificar que RSI está calculado
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if pd.isna(rsi):
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return Signal.HOLD
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# Sobreventa: señal de compra
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if rsi < self.oversold and self.current_position <= 0:
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return Signal.BUY
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# Sobrecompra: señal de venta
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elif rsi > self.overbought and self.current_position >= 0:
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return Signal.SELL
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return Signal.HOLD |