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https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
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shy3130
58f8d7b883
- 趋势/形态: 均线粘合突破 · 平台整理突破 · 放量创60日新高 - 量价/涨停: 涨停基因活跃股 (max_change_pct 参数过滤当日已大涨) - 反转/波动: MACD 零下回升 · 长下影反击 (close_position>=0.5 兼容假阴线) · RSI 中轴回踩 - 阈值统一小数制口径 (change_pct/momentum 除以 100), 一致性测试计数 26
100 lines
3.2 KiB
Python
100 lines
3.2 KiB
Python
"""平台缩量整理突破 — 窄幅横盘蓄势后放量突破平台上沿"""
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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": "platform_consolidation_breakout",
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"name": "平台整理突破",
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"description": "近N日窄幅横盘 (振幅收敛) 后放量突破平台上沿, 蓄势变盘",
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"tags": ["形态", "平台", "突破"],
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"asset_types": ["stock"],
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"timeframes": ["1d"],
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"params": [
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{
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"id": "platform_days",
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"label": "平台天数",
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"type": "int",
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"default": 10,
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"min": 5,
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"max": 30,
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"step": 1,
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},
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{
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"id": "range_pct_max",
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"label": "平台振幅上限%",
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"type": "float",
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"default": 8.0,
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"min": 3.0,
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"max": 20.0,
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"step": 0.5,
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},
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{
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"id": "vol_ratio_min",
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"label": "突破日最低量比",
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"type": "float",
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"default": 1.5,
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"min": 1.0,
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"max": 5.0,
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"step": 0.1,
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},
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],
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"scoring": {"vol_ratio_5d": 0.4, "momentum_20d": 0.3, "change_pct": 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_platform_breakout"]
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EXIT_SIGNALS = ["signal_platform_fail_ma20"]
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STOP_LOSS = -0.06
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MAX_HOLD_DAYS = 15
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class PlatformConsolidationBreakoutMatrixStrategy:
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def required_fields(self) -> frozenset[str]:
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return frozenset({"high", "low", "close", "volume"})
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def required_warmup_bars(self, params: dict) -> int:
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return int(params.get("platform_days", 10)) + 10
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def compute_signals(self, market: MarketDataMatrix, params: dict) -> SignalMatrix:
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days = max(4, int(params.get("platform_days", 10)))
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# 平台区间: 前 days 日 (不含今日) 的最高/最低 (滚动窗口平移)
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prior_high = shift(market.high, 1)
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prior_low = shift(market.low, 1)
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for k in range(2, days + 1):
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prior_high = np.fmax(prior_high, shift(market.high, k))
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prior_low = np.fmin(prior_low, shift(market.low, k))
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range_pct = (prior_high - prior_low) / market.close * 100.0
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# 平台成立 + 今日放量突破平台上沿
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entry = range_pct <= float(params.get("range_pct_max", 8.0))
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entry &= market.close > prior_high
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entry &= matrix_feature(market, "vol_ratio_5d") >= float(params.get("vol_ratio_min", 1.5))
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exit_ = market.close < matrix_feature(market, "ma20")
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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_platform_breakout",),
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exit_signal_ids=("signal_platform_fail_ma20",),
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)
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MATRIX_STRATEGY = PlatformConsolidationBreakoutMatrixStrategy()
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