56 lines
2.2 KiB
Python
56 lines
2.2 KiB
Python
"""仅用已收盘日线计算指标，避免把盘中未完成的日线混入信号。"""
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from dataclasses import dataclass
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from datetime import date, datetime
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from decimal import Decimal, ROUND_CEILING
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import math
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from statistics import fmean, pstdev
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from .config import ETFConfig
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@dataclass(frozen=True)
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class Indicators:
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day: str
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ma60: float
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atr: float
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lower: float
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middle: float
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upper: float
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grid: float
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def calculate(rows: list[dict], today: date, cfg: ETFConfig) -> Indicators:
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"""MA60 + Wilder ATR + BOLL（总体标准差），格距向上取整到 0.001 元。"""
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bars = {}
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for row in rows:
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day = datetime.strptime(str(row['date']), '%Y%m%d').date()
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if day >= today:
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continue
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if day in bars:
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raise ValueError('日线包含重复日期')
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high, low, close = (float(row[key]) for key in ('high', 'low', 'close'))
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if not all(math.isfinite(v) and v > 0 for v in (high, low, close)) or not low <= close <= high:
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raise ValueError('日线价格无效')
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bars[day] = (high, low, close)
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days = sorted(bars)
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if len(days) < max(60, cfg.atr_period + 1, cfg.boll_period):
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raise ValueError('已收盘日线不足，至少需要 60 根且能计算 ATR')
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# 长期停牌或历史缓存未补齐时不使用过期信号；春节等长假允许 15 个自然日。
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if (today - days[-1]).days > 15:
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raise ValueError('最近日线超过 15 个自然日，需补齐行情')
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values = [bars[d] for d in days]
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closes = [v[2] for v in values]
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tr = [max(h - l, abs(h - closes[i - 1]), abs(l - closes[i - 1]))
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for i, (h, l, _) in enumerate(values) if i > 0]
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n = cfg.atr_period
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atr = fmean(tr[:n])
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for value in tr[n:]:
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atr = (atr * (n - 1) + value) / n
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ma = fmean(closes[-60:])
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window = closes[-cfg.boll_period:]
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middle, width = fmean(window), cfg.boll_std * pstdev(window)
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raw_grid = max(atr * cfg.atr_multiplier, ma * cfg.min_grid_pct / 100, 0.001)
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grid = float(Decimal(str(raw_grid)).quantize(Decimal('0.001'), rounding=ROUND_CEILING))
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return Indicators(days[-1].strftime('%Y%m%d'), ma, atr, middle - width, middle, middle + width, grid)
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