80 lines
3.1 KiB
Python
80 lines
3.1 KiB
Python
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"""Moving Average Crossover strategy."""
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import pandas as pd
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from decimal import Decimal
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from typing import Optional, Dict, Any
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from src.strategies.base import BaseStrategy, StrategySignal, SignalType
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from src.data.indicators import get_indicators
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class MovingAverageStrategy(BaseStrategy):
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"""Moving average crossover strategy."""
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def __init__(self, name: str, parameters: Optional[Dict[str, Any]] = None, timeframes: Optional[list] = None):
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"""Initialize moving average strategy.
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Parameters:
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fast_period: Fast MA period (default 10)
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slow_period: Slow MA period (default 30)
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ma_type: MA type - 'sma' or 'ema' (default 'ema')
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"""
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super().__init__(name, parameters, timeframes)
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self.fast_period = self.parameters.get('fast_period', 10)
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self.slow_period = self.parameters.get('slow_period', 30)
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self.ma_type = self.parameters.get('ma_type', 'ema')
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self.indicators = get_indicators()
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self._price_history = []
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async def on_tick(self, symbol: str, price: Decimal, timeframe: str, data: Dict[str, Any]) -> Optional[StrategySignal]:
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"""Generate signal based on MA crossover."""
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# Add price to history
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self._price_history.append(float(price))
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if len(self._price_history) < self.slow_period + 1:
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return None
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# Calculate MAs
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prices = pd.Series(self._price_history[-self.slow_period-1:])
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if self.ma_type == 'sma':
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fast_ma = self.indicators.sma(prices, self.fast_period)
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slow_ma = self.indicators.sma(prices, self.slow_period)
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else:
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fast_ma = self.indicators.ema(prices, self.fast_period)
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slow_ma = self.indicators.ema(prices, self.slow_period)
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if len(fast_ma) < 2 or len(slow_ma) < 2:
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return None
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# Check for crossover
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fast_current = fast_ma.iloc[-1]
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fast_prev = fast_ma.iloc[-2]
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slow_current = slow_ma.iloc[-1]
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slow_prev = slow_ma.iloc[-2]
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# Bullish crossover
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if fast_prev <= slow_prev and fast_current > slow_current:
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return StrategySignal(
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signal_type=SignalType.BUY,
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symbol=symbol,
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strength=min(1.0, (fast_current - slow_current) / slow_current),
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price=price,
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metadata={'fast_ma': float(fast_current), 'slow_ma': float(slow_current)}
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)
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# Bearish crossover
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elif fast_prev >= slow_prev and fast_current < slow_current:
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return StrategySignal(
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signal_type=SignalType.SELL,
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symbol=symbol,
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strength=min(1.0, (slow_current - fast_current) / slow_current),
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price=price,
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metadata={'fast_ma': float(fast_current), 'slow_ma': float(slow_current)}
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)
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return None
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def on_signal(self, signal: StrategySignal) -> Optional[StrategySignal]:
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"""Process signal."""
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return signal if self.should_execute(signal) else None
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