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89 lines
2.8 KiB
Python
89 lines
2.8 KiB
Python
"""低波动龙头 — 正动量 + 低波动 + MA20上方"""
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import numpy as np
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from app.backtest.matrix import (
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MarketDataMatrix,
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SignalMatrix,
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make_signal_matrix,
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matrix_feature,
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)
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from app.backtest.matrix import (
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valid_shift as shift,
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)
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META = {
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"id": "low_volatility_leader",
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"name": "低波动龙头",
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"description": "20日动量为正 + 年化波动 < 30% + MA20上方",
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"tags": ["低波动", "龙头"],
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"asset_types": ["stock", "etf"],
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"timeframes": ["1d"],
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"params": [
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{
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"id": "require_positive_momentum",
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"label": "要求20日动量为正",
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"type": "bool",
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"default": True,
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},
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{"id": "use_volatility_filter", "label": "启用波动率过滤", "type": "bool", "default": True},
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{
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"id": "vol_max",
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"label": "最大年化波动",
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"type": "float",
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"default": 0.30,
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"min": 0.05,
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"max": 1.0,
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"step": 0.01,
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},
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{
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"id": "require_above_ma20",
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"label": "要求收盘价在MA20上方",
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"type": "bool",
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"default": True,
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},
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],
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"scoring": {"momentum_60d": 0.4, "momentum_20d": 0.3, "turnover_rate": 0.3},
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"order_by": "score",
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"descending": True,
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"limit": 100,
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}
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EXECUTION_BACKEND = "matrix_native"
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ENTRY_SIGNALS = ["signal_ma20_breakout"]
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EXIT_SIGNALS = ["signal_ma20_breakdown"]
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STOP_LOSS = -0.05
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MAX_HOLD_DAYS = 30
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class LowVolatilityLeaderMatrixStrategy:
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def required_fields(self) -> frozenset[str]:
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return frozenset({"close"})
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def required_warmup_bars(self, params: dict) -> int:
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del params
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return 60
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def compute_signals(self, market: MarketDataMatrix, params: dict) -> SignalMatrix:
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ma20 = matrix_feature(market, "ma20")
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entry = np.ones(market.shape, dtype=bool)
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if params.get("require_positive_momentum", True):
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entry &= matrix_feature(market, "momentum_20d") > 0
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if params.get("use_volatility_filter", True):
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entry &= matrix_feature(market, "annual_vol_20d") < float(params.get("vol_max", 0.30))
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if params.get("require_above_ma20", True):
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entry &= market.close > ma20
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exit_ = (market.close < ma20) & (shift(market.close, 1) >= shift(ma20, 1))
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return make_signal_matrix(
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market.shape,
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entry=entry.astype(np.uint8),
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exit=exit_.astype(np.uint8),
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entry_signal_code=np.where(entry, 0, -1).astype(np.int16),
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exit_signal_code=np.where(exit_, 0, -1).astype(np.int16),
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entry_signal_ids=("signal_ma20_breakout",),
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exit_signal_ids=("signal_ma20_breakdown",),
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)
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MATRIX_STRATEGY = LowVolatilityLeaderMatrixStrategy()
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